diff --git a/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/README.md b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/README.md
new file mode 100644
index 0000000..7feae32
--- /dev/null
+++ b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/README.md
@@ -0,0 +1,3 @@
+| Model               | Scenario   | Accuracy             |   Throughput | Latency (in ms)   |
+|---------------------|------------|----------------------|--------------|-------------------|
+| stable-diffusion-xl | offline    | (15.22477, 84.24318) |        0.848 | -                 |
\ No newline at end of file
diff --git a/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/README.md b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/README.md
new file mode 100644
index 0000000..a52d873
--- /dev/null
+++ b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/README.md
@@ -0,0 +1,59 @@
+This experiment is generated using the [MLCommons Collective Mind automation framework (CM)](https://github.com/mlcommons/cm4mlops).
+
+*Check [CM MLPerf docs](https://docs.mlcommons.org/inference) for more details.*
+
+## Host platform
+
+* OS version: Linux-5.14.0-427.42.1.el9_4.x86_64-x86_64-with-glibc2.35
+* CPU version: x86_64
+* Python version: 3.10.15 (main, Oct  3 2024, 07:27:34) [GCC 11.2.0]
+* MLCommons CM version: 3.4.1
+
+## CM Run Command
+
+See [CM installation guide](https://docs.mlcommons.org/inference/install/).
+
+```bash
+pip install -U cmind
+
+cm rm cache -f
+
+cm pull repo mlcommons@cm4mlops --checkout=b32ded2a4c3039ad16dadc734bee03dd1a97f228
+
+cm run script \
+	--tags=run-mlperf,inference,_r4.1-dev,_scc24-main \
+	--model=sdxl \
+	--framework=pytorch \
+	--category=datacenter \
+	--scenario=Offline \
+	--execution_mode=test \
+	--device=rocm \
+	--quiet \
+	--precision=float16 \
+	--adr.mlperf-implementation.tags=_branch.multinode-test,_repo.https://github.com/zixianwang2022/mlperf-scc24 \
+	--adr.mlperf-implementation.version=custom \
+	--env.CM_GET_PLATFORM_DETAILS=no \
+	--target_qps=1.8
+```
+*Note that if you want to use the [latest automation recipes](https://docs.mlcommons.org/inference) for MLPerf (CM scripts),
+ you should simply reload mlcommons@cm4mlops without checkout and clean CM cache as follows:*
+
+```bash
+cm rm repo mlcommons@cm4mlops
+cm pull repo mlcommons@cm4mlops
+cm rm cache -f
+
+```
+
+## Results
+
+Platform: aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main
+
+Model Precision: fp32
+
+### Accuracy Results 
+`CLIP_SCORE`: `15.22477`, Required accuracy for closed division `>= 31.68632` and `<= 31.81332`
+`FID_SCORE`: `84.24318`, Required accuracy for closed division `>= 23.01086` and `<= 23.95008`
+
+### Performance Results 
+`Samples per second`: `0.847525`
diff --git a/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy_console.out b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy_console.out
new file mode 100644
index 0000000..7882180
--- /dev/null
+++ b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy_console.out
@@ -0,0 +1,12 @@
+INFO:main:Namespace(sut_server=['http://10.0.0.14:8008', 'http://10.0.0.12:8008'], dataset='coco-1024', dataset_path='/root/CM/repos/local/cache/61dd835801c542a3/install', profile='stable-diffusion-xl-pytorch', scenario='Offline', max_batchsize=1, threads=1, accuracy=True, find_peak_performance=False, backend='pytorch', model_name='stable-diffusion-xl', output='/root/CM/repos/local/cache/d549713c4a534705/test_results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy', qps=None, model_path='/root/CM/repos/local/cache/c4b6bbbebe504f28/stable_diffusion_fp16', dtype='fp16', device='cuda', latent_framework='torch', mlperf_conf='mlperf.conf', user_conf='/root/CM/repos/mlcommons@cm4mlops/script/generate-mlperf-inference-user-conf/tmp/6626c9658bff4d2291e3121038a4cfca.conf', audit_conf='audit.config', ids_path='/root/CM/repos/local/cache/61dd835801c542a3/install/sample_ids.txt', time=None, count=10, debug=False, performance_sample_count=5000, max_latency=None, samples_per_query=8)
+WARNING:backend-pytorch:Model path not provided, running with default hugging face weights
+This may not be valid for official submissions
+Keyword arguments {'safety_checker': None} are not expected by StableDiffusionXLPipeline and will be ignored.
+
Loading pipeline components...:   0%|          | 0/7 [00:00<?, ?it/s]Using the `SDPA` attention implementation on multi-gpu setup with ROCM may lead to performance issues due to the FA backend. Disabling it to use alternative backends.
+
Loading pipeline components...:  57%|█████▋    | 4/7 [00:00<00:00, 12.44it/s]
Loading pipeline components...:  86%|████████▌ | 6/7 [00:00<00:00,  7.56it/s]
Loading pipeline components...: 100%|██████████| 7/7 [00:00<00:00,  9.15it/s]
+RETURNED from requests.post on predict at time 	 1731969667.0400865
+BEFORE lg.QuerySamplesComplete(response)
+AFTER lg.QuerySamplesComplete(response)
+RETURNED from requests.post on predict at time 	 1731969689.698808
+BEFORE lg.QuerySamplesComplete(response)
+AFTER lg.QuerySamplesComplete(response)
diff --git a/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main.json b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main.json
new file mode 100644
index 0000000..07589d2
--- /dev/null
+++ b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main.json
@@ -0,0 +1,7 @@
+{
+  "starting_weights_filename": "https://github.com/mlcommons/inference/tree/master/text_to_image#download-model",
+  "retraining": "no",
+  "input_data_types": "fp32",
+  "weight_data_types": "fp32",
+  "weight_transformations": "no"
+}
\ No newline at end of file
diff --git a/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/cm-version-info.json b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/cm-version-info.json
new file mode 100644
index 0000000..12cb5ff
--- /dev/null
+++ b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/cm-version-info.json
@@ -0,0 +1,504 @@
+{
+  "app-mlperf-inference,d775cac873ee4231:reference,sdxl,pytorch,rocm,test,r4.1-dev_default,float16,offline": [
+    {
+      "detect,os": {
+        "script_uid": "863735b7db8c44fc",
+        "script_alias": "detect-os",
+        "script_tags": "detect-os,detect,os,info",
+        "script_variations": "",
+        "version": "",
+        "parent": "app-mlperf-inference,d775cac873ee4231 ( reference,_sdxl,_pytorch,_rocm,_test,_r4.1-dev_default,_float16,_offline )"
+      }
+    },
+    {
+      "detect,os": {
+        "script_uid": "863735b7db8c44fc",
+        "script_alias": "detect-os",
+        "script_tags": "detect-os,detect,os,info",
+        "script_variations": "",
+        "version": "",
+        "parent": "get-sys-utils-cm,bc90993277e84b8e"
+      }
+    },
+    {
+      "get,python": {
+        "script_uid": "d0b5dd74373f4a62",
+        "script_alias": "get-python3",
+        "script_tags": "get,python,python3,get-python,get-python3",
+        "script_variations": "",
+        "version": "3.10.15",
+        "parent": "app-mlperf-inference,d775cac873ee4231 ( reference,_sdxl,_pytorch,_rocm,_test,_r4.1-dev_default,_float16,_offline )"
+      }
+    },
+    {
+      "get,mlcommons,inference,src": {
+        "script_uid": "4b57186581024797",
+        "script_alias": "get-mlperf-inference-src",
+        "script_tags": "get,src,source,inference,inference-src,inference-source,mlperf,mlcommons",
+        "script_variations": "",
+        "version": "master-git-4763c6b5e7c3ad904c461bc1053674c448771ec4",
+        "parent": "app-mlperf-inference,d775cac873ee4231 ( reference,_sdxl,_pytorch,_rocm,_test,_r4.1-dev_default,_float16,_offline )"
+      }
+    },
+    {
+      "get,mlperf,inference,src": {
+        "script_uid": "4b57186581024797",
+        "script_alias": "get-mlperf-inference-src",
+        "script_tags": "get,src,source,inference,inference-src,inference-source,mlperf,mlcommons",
+        "script_variations": "",
+        "version": "master-git-4763c6b5e7c3ad904c461bc1053674c448771ec4",
+        "parent": "get-mlperf-inference-utils,e341e5f86d8342e5"
+      }
+    },
+    {
+      "get,mlperf,inference,utils": {
+        "script_uid": "e341e5f86d8342e5",
+        "script_alias": "get-mlperf-inference-utils",
+        "script_tags": "get,mlperf,inference,util,utils,functions",
+        "script_variations": "",
+        "version": "",
+        "parent": "app-mlperf-inference,d775cac873ee4231 ( reference,_sdxl,_pytorch,_rocm,_test,_r4.1-dev_default,_float16,_offline )"
+      }
+    },
+    {
+      "detect,os": {
+        "script_uid": "863735b7db8c44fc",
+        "script_alias": "detect-os",
+        "script_tags": "detect-os,detect,os,info",
+        "script_variations": "",
+        "version": "",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "detect,os": {
+        "script_uid": "863735b7db8c44fc",
+        "script_alias": "detect-os",
+        "script_tags": "detect-os,detect,os,info",
+        "script_variations": "",
+        "version": "",
+        "parent": "detect-cpu,586c8a43320142f7"
+      }
+    },
+    {
+      "detect,cpu": {
+        "script_uid": "586c8a43320142f7",
+        "script_alias": "detect-cpu",
+        "script_tags": "detect,cpu,detect-cpu,info",
+        "script_variations": "",
+        "version": "",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "detect,os": {
+        "script_uid": "863735b7db8c44fc",
+        "script_alias": "detect-os",
+        "script_tags": "detect-os,detect,os,info",
+        "script_variations": "",
+        "version": "",
+        "parent": "get-sys-utils-cm,bc90993277e84b8e"
+      }
+    },
+    {
+      "get,python": {
+        "script_uid": "d0b5dd74373f4a62",
+        "script_alias": "get-python3",
+        "script_tags": "get,python,python3,get-python,get-python3",
+        "script_variations": "",
+        "version": "3.10.15",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "get,generic-python-lib,_torch,_rocm": {
+        "script_uid": "94b62a682bc44791",
+        "script_alias": "get-generic-python-lib",
+        "script_tags": "get,install,generic,generic-python-lib",
+        "script_variations": "torch,rocm",
+        "version": "2.6.0.dev20241118",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "get,ml-model,stable-diffusion,text-to-image,sdxl,raw,_pytorch,_fp16": {
+        "script_uid": "22c6516b2d4d4c23",
+        "script_alias": "get-ml-model-stable-diffusion",
+        "script_tags": "get,raw,ml-model,stable-diffusion,sdxl,text-to-image",
+        "script_variations": "pytorch,fp16",
+        "version": "",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "get,python3": {
+        "script_uid": "d0b5dd74373f4a62",
+        "script_alias": "get-python3",
+        "script_tags": "get,python,python3,get-python,get-python3",
+        "script_variations": "",
+        "version": "3.10.15",
+        "parent": "get-dataset-coco2014,3f7ad9d42f4040f8 ( validation,_with-sample-ids,_size.500 )"
+      }
+    },
+    {
+      "get,generic-python-lib,_package.tqdm": {
+        "script_uid": "94b62a682bc44791",
+        "script_alias": "get-generic-python-lib",
+        "script_tags": "get,install,generic,generic-python-lib",
+        "script_variations": "package.tqdm",
+        "version": "4.67.0",
+        "parent": "get-dataset-coco2014,3f7ad9d42f4040f8 ( validation,_with-sample-ids,_size.500 )"
+      }
+    },
+    {
+      "get,generic-python-lib,_package.pandas": {
+        "script_uid": "94b62a682bc44791",
+        "script_alias": "get-generic-python-lib",
+        "script_tags": "get,install,generic,generic-python-lib",
+        "script_variations": "package.pandas",
+        "version": "2.2.3",
+        "parent": "get-dataset-coco2014,3f7ad9d42f4040f8 ( validation,_with-sample-ids,_size.500 )"
+      }
+    },
+    {
+      "detect,os": {
+        "script_uid": "863735b7db8c44fc",
+        "script_alias": "detect-os",
+        "script_tags": "detect-os,detect,os,info",
+        "script_variations": "",
+        "version": "",
+        "parent": "get-mlperf-inference-src,4b57186581024797"
+      }
+    },
+    {
+      "get,python3": {
+        "script_uid": "d0b5dd74373f4a62",
+        "script_alias": "get-python3",
+        "script_tags": "get,python,python3,get-python,get-python3",
+        "script_variations": "",
+        "version": "3.10.15",
+        "parent": "get-mlperf-inference-src,4b57186581024797"
+      }
+    },
+    {
+      "get,git,repo,_branch.master,_repo.https://github.com/mlcommons/inference": {
+        "script_uid": "ed603e7292974f10",
+        "script_alias": "get-git-repo",
+        "script_tags": "get,git,repo,repository,clone",
+        "script_variations": "branch.master,repo.https://github.com/mlcommons/inference",
+        "version": "",
+        "parent": "get-mlperf-inference-src,4b57186581024797"
+      }
+    },
+    {
+      "mlperf,inference,source": {
+        "script_uid": "4b57186581024797",
+        "script_alias": "get-mlperf-inference-src",
+        "script_tags": "get,src,source,inference,inference-src,inference-source,mlperf,mlcommons",
+        "script_variations": "",
+        "version": "master-git-4763c6b5e7c3ad904c461bc1053674c448771ec4",
+        "parent": "get-dataset-coco2014,3f7ad9d42f4040f8 ( validation,_with-sample-ids,_size.500 )"
+      }
+    },
+    {
+      "get,dataset,coco2014,_validation,_with-sample-ids,_size.500": {
+        "script_uid": "3f7ad9d42f4040f8",
+        "script_alias": "get-dataset-coco2014",
+        "script_tags": "get,dataset,coco2014,object-detection,original",
+        "script_variations": "validation,with-sample-ids,size.500",
+        "version": "",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "detect,os": {
+        "script_uid": "863735b7db8c44fc",
+        "script_alias": "detect-os",
+        "script_tags": "detect-os,detect,os,info",
+        "script_variations": "",
+        "version": "",
+        "parent": "generate-mlperf-inference-user-conf,3af4475745964b93"
+      }
+    },
+    {
+      "detect,os": {
+        "script_uid": "863735b7db8c44fc",
+        "script_alias": "detect-os",
+        "script_tags": "detect-os,detect,os,info",
+        "script_variations": "",
+        "version": "",
+        "parent": "detect-cpu,586c8a43320142f7"
+      }
+    },
+    {
+      "detect,cpu": {
+        "script_uid": "586c8a43320142f7",
+        "script_alias": "detect-cpu",
+        "script_tags": "detect,cpu,detect-cpu,info",
+        "script_variations": "",
+        "version": "",
+        "parent": "generate-mlperf-inference-user-conf,3af4475745964b93"
+      }
+    },
+    {
+      "get,python": {
+        "script_uid": "d0b5dd74373f4a62",
+        "script_alias": "get-python3",
+        "script_tags": "get,python,python3,get-python,get-python3",
+        "script_variations": "",
+        "version": "3.10.15",
+        "parent": "generate-mlperf-inference-user-conf,3af4475745964b93"
+      }
+    },
+    {
+      "get,mlcommons,inference,src": {
+        "script_uid": "4b57186581024797",
+        "script_alias": "get-mlperf-inference-src",
+        "script_tags": "get,src,source,inference,inference-src,inference-source,mlperf,mlcommons",
+        "script_variations": "",
+        "version": "master-git-4763c6b5e7c3ad904c461bc1053674c448771ec4",
+        "parent": "generate-mlperf-inference-user-conf,3af4475745964b93"
+      }
+    },
+    {
+      "get,cache,dir,_name.mlperf-inference-sut-configs": {
+        "script_uid": "48f4622e059b45ce",
+        "script_alias": "get-cache-dir",
+        "script_tags": "get,cache,dir,directory",
+        "script_variations": "name.mlperf-inference-sut-configs",
+        "version": "",
+        "parent": "get-mlperf-inference-sut-configs,c2fbf72009e2445b"
+      }
+    },
+    {
+      "get,sut,configs": {
+        "script_uid": "c2fbf72009e2445b",
+        "script_alias": "get-mlperf-inference-sut-configs",
+        "script_tags": "get,mlperf,inference,sut,configs,sut-configs",
+        "script_variations": "",
+        "version": "",
+        "parent": "generate-mlperf-inference-user-conf,3af4475745964b93"
+      }
+    },
+    {
+      "generate,user-conf,mlperf,inference": {
+        "script_uid": "3af4475745964b93",
+        "script_alias": "generate-mlperf-inference-user-conf",
+        "script_tags": "generate,mlperf,inference,user-conf,inference-user-conf",
+        "script_variations": "",
+        "version": "",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "get,loadgen": {
+        "script_uid": "64c3d98d0ba04950",
+        "script_alias": "get-mlperf-inference-loadgen",
+        "script_tags": "get,loadgen,inference,inference-loadgen,mlperf,mlcommons",
+        "script_variations": "",
+        "version": "master",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "get,mlcommons,inference,src": {
+        "script_uid": "4b57186581024797",
+        "script_alias": "get-mlperf-inference-src",
+        "script_tags": "get,src,source,inference,inference-src,inference-source,mlperf,mlcommons",
+        "script_variations": "",
+        "version": "master-git-4763c6b5e7c3ad904c461bc1053674c448771ec4",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "detect,os": {
+        "script_uid": "863735b7db8c44fc",
+        "script_alias": "detect-os",
+        "script_tags": "detect-os,detect,os,info",
+        "script_variations": "",
+        "version": "",
+        "parent": "get-mlperf-inference-src,4b57186581024797 ( branch.multinode-test,_repo.https://github.com/zixianwang2022/mlperf-scc24 )"
+      }
+    },
+    {
+      "get,python3": {
+        "script_uid": "d0b5dd74373f4a62",
+        "script_alias": "get-python3",
+        "script_tags": "get,python,python3,get-python,get-python3",
+        "script_variations": "",
+        "version": "3.10.15",
+        "parent": "get-mlperf-inference-src,4b57186581024797 ( branch.multinode-test,_repo.https://github.com/zixianwang2022/mlperf-scc24 )"
+      }
+    },
+    {
+      "detect,os": {
+        "script_uid": "863735b7db8c44fc",
+        "script_alias": "detect-os",
+        "script_tags": "detect-os,detect,os,info",
+        "script_variations": "",
+        "version": "",
+        "parent": "get-git-repo,ed603e7292974f10 ( branch.multinode-test,_repo.https://github.com/zixianwang2022/mlperf-scc24 )"
+      }
+    },
+    {
+      "get,git,repo,_branch.multinode-test,_repo.https://github.com/zixianwang2022/mlperf-scc24": {
+        "script_uid": "ed603e7292974f10",
+        "script_alias": "get-git-repo",
+        "script_tags": "get,git,repo,repository,clone",
+        "script_variations": "branch.multinode-test,repo.https://github.com/zixianwang2022/mlperf-scc24",
+        "version": "",
+        "parent": "get-mlperf-inference-src,4b57186581024797 ( branch.multinode-test,_repo.https://github.com/zixianwang2022/mlperf-scc24 )"
+      }
+    },
+    {
+      "get,mlcommons,inference,src,_branch.multinode-test,_repo.https://github.com/zixianwang2022/mlperf-scc24": {
+        "script_uid": "4b57186581024797",
+        "script_alias": "get-mlperf-inference-src",
+        "script_tags": "get,src,source,inference,inference-src,inference-source,mlperf,mlcommons",
+        "script_variations": "branch.multinode-test,repo.https://github.com/zixianwang2022/mlperf-scc24",
+        "version": "custom",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "get,generic-python-lib,_package.psutil": {
+        "script_uid": "94b62a682bc44791",
+        "script_alias": "get-generic-python-lib",
+        "script_tags": "get,install,generic,generic-python-lib",
+        "script_variations": "package.psutil",
+        "version": "6.1.0",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "get,generic-python-lib,_package.diffusers": {
+        "script_uid": "94b62a682bc44791",
+        "script_alias": "get-generic-python-lib",
+        "script_tags": "get,install,generic,generic-python-lib",
+        "script_variations": "package.diffusers",
+        "version": "0.31.0",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "get,generic-python-lib,_package.transformers": {
+        "script_uid": "94b62a682bc44791",
+        "script_alias": "get-generic-python-lib",
+        "script_tags": "get,install,generic,generic-python-lib",
+        "script_variations": "package.transformers",
+        "version": "4.46.2",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "get,generic-python-lib,_package.torchvision,_rocm": {
+        "script_uid": "94b62a682bc44791",
+        "script_alias": "get-generic-python-lib",
+        "script_tags": "get,install,generic,generic-python-lib",
+        "script_variations": "package.torchvision,rocm",
+        "version": "0.20.0.dev20241113",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "get,generic-python-lib,_package.accelerate": {
+        "script_uid": "94b62a682bc44791",
+        "script_alias": "get-generic-python-lib",
+        "script_tags": "get,install,generic,generic-python-lib",
+        "script_variations": "package.accelerate",
+        "version": "1.1.1",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "get,generic-python-lib,_package.torchmetrics": {
+        "script_uid": "94b62a682bc44791",
+        "script_alias": "get-generic-python-lib",
+        "script_tags": "get,install,generic,generic-python-lib",
+        "script_variations": "package.torchmetrics",
+        "version": "1.6.0",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "get,generic-python-lib,_package.torch-fidelity": {
+        "script_uid": "94b62a682bc44791",
+        "script_alias": "get-generic-python-lib",
+        "script_tags": "get,install,generic,generic-python-lib",
+        "script_variations": "package.torch-fidelity",
+        "version": "0.3.0",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "get,generic-python-lib,_package.open_clip_torch": {
+        "script_uid": "94b62a682bc44791",
+        "script_alias": "get-generic-python-lib",
+        "script_tags": "get,install,generic,generic-python-lib",
+        "script_variations": "package.open_clip_torch",
+        "version": "2.29.0",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "get,generic-python-lib,_package.opencv-python": {
+        "script_uid": "94b62a682bc44791",
+        "script_alias": "get-generic-python-lib",
+        "script_tags": "get,install,generic,generic-python-lib",
+        "script_variations": "package.opencv-python",
+        "version": "4.10.0.84",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "get,generic-python-lib,_package.scipy": {
+        "script_uid": "94b62a682bc44791",
+        "script_alias": "get-generic-python-lib",
+        "script_tags": "get,install,generic,generic-python-lib",
+        "script_variations": "package.scipy",
+        "version": "1.10.1",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    },
+    {
+      "detect,os": {
+        "script_uid": "863735b7db8c44fc",
+        "script_alias": "detect-os",
+        "script_tags": "detect-os,detect,os,info",
+        "script_variations": "",
+        "version": "",
+        "parent": "detect-cpu,586c8a43320142f7"
+      }
+    },
+    {
+      "detect,cpu": {
+        "script_uid": "586c8a43320142f7",
+        "script_alias": "detect-cpu",
+        "script_tags": "detect,cpu,detect-cpu,info",
+        "script_variations": "",
+        "version": "",
+        "parent": "benchmark-program,19f369ef47084895"
+      }
+    },
+    {
+      "benchmark-program,program": {
+        "script_uid": "19f369ef47084895",
+        "script_alias": "benchmark-program",
+        "script_tags": "program,benchmark,benchmark-program",
+        "script_variations": "",
+        "version": "",
+        "parent": "benchmark-program-mlperf,cfff0132a8aa4018"
+      }
+    },
+    {
+      "benchmark-mlperf": {
+        "script_uid": "cfff0132a8aa4018",
+        "script_alias": "benchmark-program-mlperf",
+        "script_tags": "mlperf,benchmark-mlperf",
+        "script_variations": "",
+        "version": "",
+        "parent": "app-mlperf-inference-mlcommons-python,ff149e9781fc4b65 ( rocm,_offline,_pytorch,_sdxl,_float16 )"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git a/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/cpu_info.json b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/cpu_info.json
new file mode 100644
index 0000000..3dbee47
--- /dev/null
+++ b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/cpu_info.json
@@ -0,0 +1,27 @@
+{
+  "CM_HOST_CPU_WRITE_PROTECT_SUPPORT": "yes",
+  "CM_HOST_CPU_MICROCODE": "0xa101148",
+  "CM_HOST_CPU_FPU_SUPPORT": "yes",
+  "CM_HOST_CPU_FPU_EXCEPTION_SUPPORT": "yes",
+  "CM_HOST_CPU_BUGS": "sysret_ss_attrs spectre_v1 spectre_v2 spec_store_bypass srso",
+  "CM_HOST_CPU_TLB_SIZE": "3584 4K pages",
+  "CM_HOST_CPU_CFLUSH_SIZE": "64",
+  "CM_HOST_CPU_ARCHITECTURE": "x86_64",
+  "CM_HOST_CPU_TOTAL_CORES": "64",
+  "CM_HOST_CPU_ON_LINE_CPUS_LIST": "0-63",
+  "CM_HOST_CPU_VENDOR_ID": "AuthenticAMD",
+  "CM_HOST_CPU_MODEL_NAME": "AMD EPYC 9354 32-Core Processor",
+  "CM_HOST_CPU_FAMILY": "25",
+  "CM_HOST_CPU_THREADS_PER_CORE": "1",
+  "CM_HOST_CPU_PHYSICAL_CORES_PER_SOCKET": "32",
+  "CM_HOST_CPU_SOCKETS": "2",
+  "CM_HOST_CPU_MAX_MHZ": "3799.0720",
+  "CM_HOST_CPU_L1D_CACHE_SIZE": "2 MiB (64 instances)",
+  "CM_HOST_CPU_L1I_CACHE_SIZE": "2 MiB (64 instances)",
+  "CM_HOST_CPU_L2_CACHE_SIZE": "64 MiB (64 instances)",
+  "CM_HOST_CPU_L3_CACHE_SIZE": "512 MiB (16 instances)",
+  "CM_HOST_CPU_NUMA_NODES": "16",
+  "CM_HOST_CPU_TOTAL_LOGICAL_CORES": "64",
+  "CM_HOST_MEMORY_CAPACITY": "773G",
+  "CM_HOST_DISK_CAPACITY": "4.9T"
+}
\ No newline at end of file
diff --git a/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/mlperf.conf b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/mlperf.conf
new file mode 100644
index 0000000..10f7ae7
--- /dev/null
+++ b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/mlperf.conf
@@ -0,0 +1,98 @@
+# The format of this config file is 'key = value'.
+# The key has the format 'model.scenario.key'. Value is mostly int64_t.
+# Model maybe '*' as wildcard. In that case the value applies to all models.
+# All times are in milli seconds
+
+# Set performance_sample_count for each model.
+# User can optionally set this to higher values in user.conf.
+resnet50.*.performance_sample_count_override = 1024
+ssd-mobilenet.*.performance_sample_count_override = 256
+retinanet.*.performance_sample_count_override = 64
+bert.*.performance_sample_count_override = 10833
+dlrm.*.performance_sample_count_override = 204800
+dlrm-v2.*.performance_sample_count_override = 204800
+rnnt.*.performance_sample_count_override = 2513
+gptj.*.performance_sample_count_override = 13368
+llama2-70b.*.performance_sample_count_override = 24576
+stable-diffusion-xl.*.performance_sample_count_override = 5000
+# set to 0 to let entire sample set to be performance sample
+3d-unet.*.performance_sample_count_override = 0
+
+# Set seeds. The seeds will be distributed two weeks before the submission.
+*.*.qsl_rng_seed = 3066443479025735752
+*.*.sample_index_rng_seed = 10688027786191513374
+*.*.schedule_rng_seed = 14962580496156340209
+# Set seeds for TEST_05. The seeds will be distributed two weeks before the submission.
+*.*.test05_qsl_rng_seed = 16799458546791641818
+*.*.test05_sample_index_rng_seed = 5453809927556429288
+*.*.test05_schedule_rng_seed = 5435552105434836064
+
+
+*.SingleStream.target_latency_percentile = 90
+*.SingleStream.min_duration = 600000
+
+*.MultiStream.target_latency_percentile = 99
+*.MultiStream.samples_per_query = 8
+*.MultiStream.min_duration = 600000
+*.MultiStream.min_query_count = 662
+retinanet.MultiStream.target_latency = 528
+
+# 3D-UNet uses equal issue mode because it has non-uniform inputs
+3d-unet.*.sample_concatenate_permutation = 1
+
+# LLM benchmarks have non-uniform inputs and outputs, and use equal issue mode for all latency scenario
+gptj.*.sample_concatenate_permutation = 1
+llama2-70b.*.sample_concatenate_permutation = 1
+mixtral-8x7b.*.sample_concatenate_permutation = 1
+
+*.Server.target_latency = 10
+*.Server.target_latency_percentile = 99
+*.Server.target_duration = 0
+*.Server.min_duration = 600000
+resnet50.Server.target_latency = 15
+retinanet.Server.target_latency = 100
+bert.Server.target_latency = 130
+dlrm.Server.target_latency = 60
+dlrm-v2.Server.target_latency = 60
+rnnt.Server.target_latency = 1000
+gptj.Server.target_latency = 20000
+stable-diffusion-xl.Server.target_latency = 20000
+# Llama2-70b benchmarks measures token latencies
+llama2-70b.*.use_token_latencies = 1
+mixtral-8x7b.*.use_token_latencies = 1
+# gptj benchmark infers token latencies
+gptj.*.infer_token_latencies = 1
+gptj.*.token_latency_scaling_factor = 69
+# Only ttft and tpot are tracked for the llama2-70b & mixtral-8x7B benchmark therefore target_latency = 0
+llama2-70b.Server.target_latency = 0
+llama2-70b.Server.ttft_latency = 2000
+llama2-70b.Server.tpot_latency = 200
+
+mixtral-8x7b.Server.target_latency = 0
+mixtral-8x7b.Server.ttft_latency = 2000
+mixtral-8x7b.Server.tpot_latency = 200
+
+*.Offline.target_latency_percentile = 90
+*.Offline.min_duration = 600000
+
+# In Offline scenario, we always have one query. But LoadGen maps this to
+# min_sample_count internally in Offline scenario. If the dataset size is larger 
+# than 24576 we limit the min_query_count to 24576 and otherwise we use 
+# the dataset size as the limit
+
+resnet50.Offline.min_query_count = 24576
+retinanet.Offline.min_query_count = 24576
+dlrm-v2.Offline.min_query_count = 24576
+bert.Offline.min_query_count = 10833
+gptj.Offline.min_query_count = 13368
+rnnt.Offline.min_query_count = 2513
+3d-unet.Offline.min_query_count = 43
+stable-diffusion-xl.Offline.min_query_count = 5000
+llama2-70b.Offline.min_query_count = 24576
+mixtral-8x7b.Offline.min_query_count = 15000
+
+# These fields should be defined and overridden by user.conf.
+*.SingleStream.target_latency = 10
+*.MultiStream.target_latency = 80
+*.Server.target_qps = 1.0
+*.Offline.target_qps = 1.0
diff --git a/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/model-info.json b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/model-info.json
new file mode 100644
index 0000000..07589d2
--- /dev/null
+++ b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/model-info.json
@@ -0,0 +1,7 @@
+{
+  "starting_weights_filename": "https://github.com/mlcommons/inference/tree/master/text_to_image#download-model",
+  "retraining": "no",
+  "input_data_types": "fp32",
+  "weight_data_types": "fp32",
+  "weight_transformations": "no"
+}
\ No newline at end of file
diff --git a/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/os_info.json b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/os_info.json
new file mode 100644
index 0000000..12947e1
--- /dev/null
+++ b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/os_info.json
@@ -0,0 +1,30 @@
+{
+  "CM_HOST_OS_TYPE": "linux",
+  "CM_HOST_OS_BITS": "64",
+  "CM_HOST_OS_FLAVOR": "ubuntu",
+  "CM_HOST_OS_FLAVOR_LIKE": "debian",
+  "CM_HOST_OS_VERSION": "22.04",
+  "CM_HOST_OS_KERNEL_VERSION": "5.14.0-427.42.1.el9_4.x86_64",
+  "CM_HOST_OS_GLIBC_VERSION": "2.35",
+  "CM_HOST_OS_MACHINE": "x86_64",
+  "CM_HOST_OS_PACKAGE_MANAGER": "apt",
+  "CM_HOST_OS_PACKAGE_MANAGER_INSTALL_CMD": "DEBIAN_FRONTEND=noninteractive apt-get install -y",
+  "CM_HOST_OS_PACKAGE_MANAGER_UPDATE_CMD": "apt-get update -y",
+  "+CM_HOST_OS_DEFAULT_LIBRARY_PATH": [
+    "/usr/local/lib/x86_64-linux-gnu",
+    "/lib/x86_64-linux-gnu",
+    "/usr/lib/x86_64-linux-gnu",
+    "/usr/lib/x86_64-linux-gnu64",
+    "/usr/local/lib64",
+    "/lib64",
+    "/usr/lib64",
+    "/usr/local/lib",
+    "/lib",
+    "/usr/lib",
+    "/usr/x86_64-linux-gnu/lib64",
+    "/usr/x86_64-linux-gnu/lib"
+  ],
+  "CM_HOST_PLATFORM_FLAVOR": "x86_64",
+  "CM_HOST_PYTHON_BITS": "64",
+  "CM_HOST_SYSTEM_NAME": "aqua"
+}
\ No newline at end of file
diff --git a/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/performance_console.out b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/performance_console.out
new file mode 100644
index 0000000..bf5aab3
--- /dev/null
+++ b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/performance_console.out
@@ -0,0 +1,12 @@
+INFO:main:Namespace(sut_server=['http://10.0.0.14:8008', 'http://10.0.0.12:8008'], dataset='coco-1024', dataset_path='/root/CM/repos/local/cache/61dd835801c542a3/install', profile='stable-diffusion-xl-pytorch', scenario='Offline', max_batchsize=1, threads=1, accuracy=False, find_peak_performance=False, backend='pytorch', model_name='stable-diffusion-xl', output='/root/CM/repos/local/cache/d549713c4a534705/test_results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/performance/run_1', qps=None, model_path='/root/CM/repos/local/cache/c4b6bbbebe504f28/stable_diffusion_fp16', dtype='fp16', device='cuda', latent_framework='torch', mlperf_conf='mlperf.conf', user_conf='/root/CM/repos/mlcommons@cm4mlops/script/generate-mlperf-inference-user-conf/tmp/4230b77fd5cb4bafb0486eb50444b67d.conf', audit_conf='audit.config', ids_path='/root/CM/repos/local/cache/61dd835801c542a3/install/sample_ids.txt', time=None, count=None, debug=False, performance_sample_count=5000, max_latency=None, samples_per_query=8)
+WARNING:backend-pytorch:Model path not provided, running with default hugging face weights
+This may not be valid for official submissions
+Keyword arguments {'safety_checker': None} are not expected by StableDiffusionXLPipeline and will be ignored.
+
Loading pipeline components...:   0%|          | 0/7 [00:00<?, ?it/s]Using the `SDPA` attention implementation on multi-gpu setup with ROCM may lead to performance issues due to the FA backend. Disabling it to use alternative backends.
+
Loading pipeline components...:  57%|█████▋    | 4/7 [00:00<00:00, 17.02it/s]
Loading pipeline components...:  86%|████████▌ | 6/7 [00:00<00:00,  7.51it/s]
Loading pipeline components...: 100%|██████████| 7/7 [00:00<00:00,  9.41it/s]
+RETURNED from requests.post on predict at time 	 1731969085.0292747
+BEFORE lg.QuerySamplesComplete(response)
+AFTER lg.QuerySamplesComplete(response)
+RETURNED from requests.post on predict at time 	 1731969315.4215434
+BEFORE lg.QuerySamplesComplete(response)
+AFTER lg.QuerySamplesComplete(response)
diff --git a/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/pip_freeze.json b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/pip_freeze.json
new file mode 100644
index 0000000..6d40759
--- /dev/null
+++ b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/pip_freeze.json
@@ -0,0 +1,68 @@
+{
+  "pip_freeze": {
+    "absl-py": "2.1.0",
+    "accelerate": "1.1.1",
+    "blinker": "1.9.0",
+    "certifi": "2024.8.30",
+    "charset-normalizer": "3.4.0",
+    "click": "8.1.7",
+    "cm4mlops": "0.3.26",
+    "cmind": "3.4.1",
+    "diffusers": "0.31.0",
+    "dmiparser": "5.1",
+    "filelock": "3.16.1",
+    "Flask": "3.1.0",
+    "fsspec": "2024.10.0",
+    "ftfy": "6.3.1",
+    "giturlparse": "0.12.0",
+    "huggingface-hub": "0.26.2",
+    "idna": "3.10",
+    "ijson": "3.3.0",
+    "importlib_metadata": "8.5.0",
+    "itsdangerous": "2.2.0",
+    "Jinja2": "3.1.4",
+    "lightning-utilities": "0.11.8",
+    "MarkupSafe": "2.1.5",
+    "mpmath": "1.3.0",
+    "networkx": "3.4.2",
+    "numpy": "1.26.4",
+    "open_clip_torch": "2.29.0",
+    "opencv-python": "4.10.0.84",
+    "opencv-python-headless": "4.10.0.84",
+    "packaging": "24.2",
+    "pandas": "2.2.3",
+    "pillow": "11.0.0",
+    "psutil": "6.1.0",
+    "pyarrow": "18.0.0",
+    "pybind11": "2.13.6",
+    "python-dateutil": "2.9.0.post0",
+    "pytorch-triton-rocm": "3.1.0+cf34004b8a",
+    "pytz": "2024.2",
+    "PyYAML": "6.0.2",
+    "regex": "2024.11.6",
+    "requests": "2.32.3",
+    "safetensors": "0.4.5",
+    "scipy": "1.10.1",
+    "setuptools": "75.1.0",
+    "six": "1.16.0",
+    "sympy": "1.13.1",
+    "tabulate": "0.9.0",
+    "timm": "1.0.11",
+    "tokenizers": "0.20.3",
+    "torch": "2.6.0.dev20241113+rocm6.2",
+    "torch-fidelity": "0.3.0",
+    "torchaudio": "2.5.0.dev20241113+rocm6.2",
+    "torchmetrics": "1.6.0",
+    "torchvision": "0.20.0.dev20241113+rocm6.2",
+    "tqdm": "4.67.0",
+    "transformers": "4.46.2",
+    "typing_extensions": "4.12.2",
+    "tzdata": "2024.2",
+    "urllib3": "2.2.3",
+    "wcwidth": "0.2.13",
+    "Werkzeug": "3.1.3",
+    "wheel": "0.44.0",
+    "XlsxWriter": "3.2.0",
+    "zipp": "3.21.0"
+  }
+}
\ No newline at end of file
diff --git a/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/user.conf b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/user.conf
new file mode 100644
index 0000000..8249e4c
--- /dev/null
+++ b/open/UCSD/measurements/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/user.conf
@@ -0,0 +1,5 @@
+stable-diffusion-xl.Offline.target_qps = 0.05
+stable-diffusion-xl.Offline.max_query_count = 500
+stable-diffusion-xl.Offline.min_query_count = 500
+stable-diffusion-xl.Offline.min_duration = 0
+stable-diffusion-xl.Offline.sample_concatenate_permutation = 0
diff --git a/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/accuracy.txt b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/accuracy.txt
new file mode 100644
index 0000000..a3f070b
--- /dev/null
+++ b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/accuracy.txt
@@ -0,0 +1,2 @@
+Accuracy Results: {'FID_SCORE': 84.24318228239224, 'CLIP_SCORE': 15.224773076921702}
+hash=d89890c5a0e710c9348cf48b041af2e6f6b2cfd8f7d5cef064a0a7ea43cc49bf
diff --git a/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/109.png b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/109.png
new file mode 100644
index 0000000..441edf5
Binary files /dev/null and b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/109.png differ
diff --git a/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/262.png b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/262.png
new file mode 100644
index 0000000..c31ff73
Binary files /dev/null and b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/262.png differ
diff --git a/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/279.png b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/279.png
new file mode 100644
index 0000000..371bbb1
Binary files /dev/null and b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/279.png differ
diff --git a/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/337.png b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/337.png
new file mode 100644
index 0000000..9b96116
Binary files /dev/null and b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/337.png differ
diff --git a/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/368.png b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/368.png
new file mode 100644
index 0000000..d071dda
Binary files /dev/null and b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/368.png differ
diff --git a/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/413.png b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/413.png
new file mode 100644
index 0000000..ab34c62
Binary files /dev/null and b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/413.png differ
diff --git a/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/44.png b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/44.png
new file mode 100644
index 0000000..3a29a63
Binary files /dev/null and b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/44.png differ
diff --git a/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/449.png b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/449.png
new file mode 100644
index 0000000..7f521d5
Binary files /dev/null and b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/449.png differ
diff --git a/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/47.png b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/47.png
new file mode 100644
index 0000000..eb19795
Binary files /dev/null and b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/47.png differ
diff --git a/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/9.png b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/9.png
new file mode 100644
index 0000000..0bd1009
Binary files /dev/null and b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/9.png differ
diff --git a/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/captions.txt b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/captions.txt
new file mode 100644
index 0000000..34cba8e
--- /dev/null
+++ b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/images/captions.txt
@@ -0,0 +1,10 @@
+47  An orange cat is laying on the couch.
+44  A boat that looks like a car moves through the water.
+9  A random plane in the sky flying alone
+279  Three zebras standing next to each other in a meadow with other zebras visible behind them
+337  A car and a bus are near a street light at night.
+262  A group of people stand out side with umbrellas.
+109  People walking toward an airplane to board it.
+413  A bathroom with a large white tub and his and her sinks.
+449  A huge airplane looks small against a wide open concrete area.
+368  a bathroom with two sinks two mirrors and a bath tub
diff --git a/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json
new file mode 100644
index 0000000..5d506bc
--- /dev/null
+++ b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_accuracy.json
@@ -0,0 +1,7 @@
+[
+{ "seq_id" : 124, "qsl_idx" : 235, "data" : "C1C2C1C0C1C1C1C2C2C2C2C2C1C2C1C3C3C2C4C5C4C3C4C3C3C4C4C4C5C5C6C6C6C7C7C7C6C6C7C6C5C6C6C7C6C8C7C7C9C9C8C8C8C8C7C7C8C7C7C8C7C7C8C7C7C8CACACAC8C8C8C9C9C9C6C6C7C8C8C8CACAC9CCCBCACBCBCACCCDCBCCCDCCCDCECECECFCECDCDCDCCCDCCCDCECECCCCCDCFCECFCECDCDD1D0D0CECCCDCFCECFD0D0CFD0D1D0CDCECDCED0CDCDCDCCCECFCECDCECECCCDCDCCCCCCCBCBCBCCCCCCCCCCCDCCCCCDCCCDCECACBCCCBCCCCCBCCCCCBCCCBCBCCCBCCCDCDCBCCCCCFCFCFCECECECFCDCECECDCED0CFD0D0CFD1D1CFD1D2D0D0D2D0D1D2D0D1D3D1D3D2D1D3D3D3D5D2D2D4D3D3D4D4D4D4D3D4D3D3D5D4D4D6D5D4D6D5D4D5D6D5D7D7D3D5D5D4D6D6D4D6D6D5D7D7D4D5D5D6D7D7D7D7D8D7D7D9D4D5D7D8D8DAD7D7D9D7D7D9D8D8D9D7D7D8D9D9D9D9D9DAD9D9DAD8DADADADCDCD7D9DAD7D9DADADCDCD9DBDCDBDCDDDADBDCD9D9DAD9DADADCDCDCDADBDBDADBDBDADBDCD7D8DAD8D8D9DBDBDBDADADAD9D9D9DADADAD9DADAD9DADAD9DADAD9D9D8D8D8D7D9DAD9D8D9D8D9DAD9D9DAD9D9DAD9D8D8D8D9DAD8D9DAD8DADBD9D9DAD9D8D9D9D9DAD8D8D9D8D8D9D8D9DAD9DADBDAD9DAD9DADBDAD9DAD9D9DBD9DBDCDBDADADADADBDAD9D9D8DBDCDAD9DAD9DADBDADBDBDADBDCDADADBD9DBDCDADBDDDADBDDDADBDDDADADCD9DBDDDADBDDDBDADBDADADAD9DBDCDADBDCD9DADAD8DCDCDADDDCDADBDBDADBDBDADBDBDBD9D9D9DDDDDCDADADADBDBDADBDBDADBDADADBDADADCDCDCDBDCDBDCDDDCDADCDBDADBDBDCDCDBDCDCDCDBDADBDCDCDCDCDCDDDBDADCDADADCDBDCDCDADBDCDADADADBDBDBD9DADBDBDBDDDADADCDADADCD9D9DBD9DADCDADBDCDADBDCDADBDCDBDBDCDADBDCDBDBDCDBDBDDDBDCDDDBDBDDDADBDDDADBDCDBDBDCDBDBDCDBDBDDDBDBDDDBDCDEDADADDDADBDDDADBDCDCDCDDDBDBDDDCDCDDDBDBDDDBDBDDDCDCDEDBDBDDDBDBDDDDDCDDDCDBDDDBDBDDDCDCDEDBDBDCDCDBDDDADADBD9DADBD9DADAD9DADBD7D8D9D7D9D9D8D9D9D7D8D8D7D7D7D8D8D8D8D8D8D6D6D6D6D6D6D6D7D7D6D7D6D6D8D7D6D7D7D6D7D7D5D6D6D5D7D7D5D6D7D4D5D6D6D6D7D4D5D6D5D5D6D5D5D7D5D6D6D6D7D7D5D6D6D4D5D6D4D6D6D4D6D7D4D6D7D4D6D6D4D5D5D5D7D6D5D6D7D6D7D7D6D7D7D5D6D7D3D4D5D4D6D6D6D6D6D5D5D5D5D6D6D4D4D6D4D6D7D3D5D7D2D4D6D3D3D5D4D4D5D4D5D5D3D4D5D2D4D5D3D5D6D2D3D5D0D0D2D2D3D3D2D2D2D1D2D2D1D2D2D1D2D1D0D1D0D1D3D2CFD1D1D0D1D0CFD0CFD0D0D0CECECED0D0D0D0D1D0D0D0D0CECFCFCFD0D0D0D1D1CFCFD0CED0D0CECFD0CFD1D1CED0D0CFD1D0CDCFCECCCECCCDCFCECED0CECDCFCECDCFCECDCFCFCCCECECCCDCDCDCECDCFD0CFCDCFCDCED0CECCCECDCFD1D0CCCDCDCCCDCDCFCFCFCDCDCDCCCCCDCDCFCDCCCECCCDCECDCCCDCCCCCECCCBCDCBCCCECDC9CBCBCACDCCCACBCBCCCECDCACBCBCED0CECDCDCDCBCBCBCBCBCBCBCCCCCECFCECCCDCDCBCCCCCBCCCCCDCECCCCCDCDCACCCCCBCCCCCCCCCCCBCBCACACACACBCCCACBCCCAC9CAC9C9CAC9C7C8C7C7C9C7C9CBC9C7C8C7C9CBC9C8C9C8C7C9C8C5C7C7C7C9C8C8C9C8C7C8C8C6C7C7C7C8C8C8C9C8C7C9C8C6C8C7C6C8C7C7C9C7C6C8C7C8CAC8C6C8C6C7C9C7C7CAC6C9CAC7C8CAC8C8CAC9C8C9C9C7C9C9C8C9C9C8C9C8C8CAC8C8CBC9C8CBC9C8C9C7C8CAC7C5C7C6C8CAC8C8CBC8C6C8C6C5C7C5C6C8C6C6C8C5C6C8C7C6C8C7C6C8C6C6C7C6C6C6C5C5C6C5C5C5C5C4C5C4C4C4C4C4C6C4C5C7C5C5C5C3C2C3C2C3C5C4C2C4C2C4C5C3C5C8C5C2C4C2C2C4C2C3C4C2C1C2C1C2C4C2C3C4C3C3C6C3C3C5C3C1C2C0C2C3C2C3C4C3C3C3C2C0C1C1C0C2C1C0C2C1BFC1C0C2C3C2C0C1C0C1C3C1C1C4C3BFC1C1C0C0C1C0C0C0C1C2C2BFC0C1C1C2C2C2C2C1C1C2C2C1C2C2C4C5C4C3C4C3C2C3C2C0C2C2C1C4C3C3C4C3C2C3C2C3C4C3C3C4C3C2C4C4C3C5C5C4C6C6C2C3C4C3C4C3C4C5C5C2C4C4C3C3C4C4C4C3C3C4C4C0C2C3C1C3C3C2C4C3C0C1C0BEC0BFBDBFBEBDC0BEBEC1BFBDBFBEBCBEBDBDBEBDBEC0BFBDBFBEBDBEBEBEC0BEBDBFBDBCBEBDBEC0BFBFC1BFBEC0BFBCBFBFBEC0C0BFC2C2BFC0C1C0C1C1C0C0C0C0C1C1C1C2C1BFC0C0BEC0BFBEC0BFBFC1C0BDBFBFBEC0C0BEC0BFBFC1C1BDBFC0BCBDBFBEBEBFBDBEBDBEBFBFBDBEBEC2C4C2BFC2C2BBBEBEBDBFBFBDBFBFBDC0BFC0C3C2BDBFBFBEC0C0BEC0C0BEC0C0C0C2C2BFC1C0BEC0C0BDBFC0BDBFBFC2C4C2BFC0C1BDBFBFBCBEBEBDBFBEBBBDBDBEC1C0BCBDBCBBBBBABABAB9B8B8B8B7B9BAB9BABAB9BCBBB9BCBCB7B9BAB9BBBBB9BCBAB9BDBBB9BDBBBABEBCB9BCBBB8BBBAB7B9B8B8B9B8B9BBBAB9BBBAB8BABAB6B8B7B6B9B8B6B7B8B9B9B9BABAB9B7B8B8B4B6B6B6B7B6B7B8B7B5B6B5B5B7B6B7B9B7B9BAB8B5B5B3B5B6B4B4B4B4B6B7B6B4B5B4B5B6B6B5B6B6B9BAB9B5B5B5B4B7B7B4B5B5B5B5B5B3B4B3B6B7B5B6B7B7B5B7B6B3B6B6B2B5B5B1B4B3B4B7B5B3B6B5B4B7B6B3B5B4B4B6B5B3B6B5B2B4B4B4B6B5B3B5B5B0B2B3B2B4B6B3B4B5B4B4B5B5B6B7AFB1B2B2B4B4B3B5B4B2B4B3B3B4B5B4B5B5B4B5B5B3B3B5B4B6B6B2B3B4B2B3B3B2B5B4B2B4B5B4B6B6B3B5B5B2B4B4B1B3B4B2B4B5B2B4B4B3B5B6B0B2B4B2B4B4B2B3B3B1B2B3B1B4B4AFB1B3B2B3B5B1B2B3B1B3B3B2B3B3B1B2B2B5B7B6B0B2B3B0B1B2B0B1B2B2B5B4B1B3B2AFB0B1B2B4B4B2B3B4B0B2B3AFB0B1B2B4B3AFB0B1ADB1B2AFB2B3B1B3B4AEAFB1ADAFB0ACAFB0AFB1B1ADAFAFACB0B0ABB0AEAEB0B0ACADADADAFAFADB0B0ACAFAFABAEB0ABAEB0ABACAFAEAEAFADADAFABAEAFABAEA
+
+...
+
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}
+]
diff --git a/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_detail.txt b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_detail.txt
new file mode 100644
index 0000000..2ca89e9
--- /dev/null
+++ b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_detail.txt
@@ -0,0 +1,71 @@
+:::MLLOG {"key": "error_invalid_config", "value": "Multiple conf files are used. This is not valid for official submission.", "time_ms": 18446744073709.223600, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": true, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 539, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "loadgen_version", "value": "4.1.23 @ 4763c6b5e7", "time_ms": 0.007660, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 53, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-11-18T21:39:51.630673", "time_ms": 0.007660, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 55, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "loadgen_build_date_utc", "value": "2024-11-18T21:39:51.630681", "time_ms": 0.007660, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 56, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "loadgen_git_commit_date", "value": "2024-11-15T21:09:48+00:00", "time_ms": 0.007660, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 57, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "loadgen_git_log_message", "value": "4763c6b5e7c3ad904c461bc1053674c448771ec4 Removed TEST05 compliance requirement (#1925)\ne398b90e85f9e64d34d6c67fe4b04d6cb7145c98 Update requirements.txt (#1907)\n97122a2aa017eb737fa9ab2f2508683073e8d247 Fix typo in fid_score.py, fail_safe for SDXL short runs, fix argument error in DLRMv2 implementation #1909, fixes preprocess_submission (#1910)\ndffd29273e98ffcbbfad0e66648c5d390d814509 Update artifact actions from v3 to v4 in build_wheels.yml (#1906)\nd3c01ed3de6618a8d39dc8a2a82871e598ea801f Update GNN reference implementation: add DGL backend (#1903)", "time_ms": 0.007660, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 58, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "loadgen_git_status_message", "value": "", "time_ms": 0.007660, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 60, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "loadgen_file_sha1", "value": {"/.clang-format":"012aad77e5206c89d50718c46c119d1f3cb056b2","/CMakeLists.txt":"d47a9d552d9f882a5250f1ba1e969f9ebca4281b","/MANIFEST.in":"ad32a45fd2cf9b05dcf9ffa884ae78b536237ba6","/README.md":"20a55bb946c2c0bbb564ced2af1e48efd096b3a8","/README_BUILD.md":"5f6c6a784e9cd6995db47f9b9f70b1769909c9d8","/README_FAQ.md":"01f9ae9887f50bc030dc6107e740f40c43ca388f","/VERSION.txt":"b704125a89b97a97513991ee33320e29d95916e2","/__init__.py":"d013101621ef06a0ddc5e7d9ce511918a8b2ebe6","/bindings/c_api.cc":"14d178b64c7fc45d090e038c08d9b78ca943c383","/bindings/c_api.h":"23d9f99e00b2d196e095fae0bb453a391c18d601","/bindings/python_api.cc":"9f538d2a5390c77ae0bc3f8a351bcdb2587bc66c","/diagram_network_submission.png":"53dba8ad4272190ceb6335c12fd25e53dc02a8cb","/diagram_submission.png":"84c2f79309b237cef652aef6a187ba8e875a3952","/early_stopping.cc":"0cd7b546a389deac73f7955cd39255ed76557d62","/early_stopping.h":"158fcae6a5f47e82150d6416fa1f7bcef37e77fe","/issue_query_controller.cc":"02fcfe6d9cf958eeb4b6f1f4dbe87ba7eb4d7dec","/issue_query_controller.h":"ed20934fd3507a15949d501ac154be38e766f6ab","/loadgen.cc":"42b50c087c6fea1005abbba369c22cb09d6a364a","/loadgen.h":"ce9fcb5d44951e7e9048a83b7c1a41c8b8e0f7d8","/loadgen_integration_diagram.svg":"47f748307536f80cfc606947b440dd732afc2637","/logging.cc":"49e63158ebca654fa4b7c5f3321054cf4d6c3a30","/logging.h":"5f6cc9ed4c4859641e05b1bb6a0ef860c852fcd8","/mlperf.conf":"0a4daef277bb3151139980e484dd5e644bf36e18","/mlperf_conf.h":"1813988201e2ff86f4fa8cf4c01685782e933c27","/pyproject.toml":"712fab87b72ba67ef2a068d0f9f47da65130342f","/query_dispatch_library.h":"1f18e9cd3ee4dc89a387cf462de1d0ceb1ece975","/query_sample.h":"c4f399103bc3d172079bbd4cd2b0ca0f22eebc4f","/query_sample_library.h":"8323a2225be1dff31f08ecc86b76eb3de06568bc","/requirements.txt":"a5ff7e77caa6e9e22ada90f0de0c865c987bf167","/results.cc":"239835696a1abe2cac9e866122d1dddc367e3548","/results.h":"fce22d5a588d91fd968a6b25c27896dba87bc276","/setup.py":"a5eaa6f713bd3dfb6603be2c7928f0c295d7ee30","/system_under_test.h":"18d4809589dae33317d88d9beeb5491a6e1ccdec","/test_settings.h":"476ecd4032f3bafe6f201df25d68aca4e177f659","/test_settings_internal.cc":"8827ef7d70e6c9a43dd25b4f42a6d2a9cecda428","/test_settings_internal.h":"2bb9e9ae53904cb0ca221f4a5d49ca7d9ec3b0ca","/utils.cc":"3df8fdabf6eaea4697cf25d1dcb89cae88e36efd","/utils.h":"40775e32d619ea6356826ae5ea4174c7911f6894","/version.cc":"cbec2a5f98f9786c8c3d8b06b3d12df0b6550fa0","/version.h":"9d574baa64424e9c708fcfedd3dbb0b518a65fcc","/version_generator.py":"9f23d13276194588473120a8a6ecf5a6ed034a23"}, "time_ms": 0.007660, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 67, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "test_datetime", "value": "2024-11-18T22:35:28Z", "time_ms": 0.007930, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1193, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "sut_name", "value": "Multi-node SUT: N1, N2", "time_ms": 0.007930, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1194, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "get_sut_name_duration_ns", "value": 2910, "time_ms": 0.007930, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1195, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "qsl_name", "value": "PyQSL", "time_ms": 0.007930, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1196, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "qsl_reported_total_count", "value": 500, "time_ms": 0.007930, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1197, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "qsl_reported_performance_count", "value": 5000, "time_ms": 0.007930, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1198, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_scenario", "value": "Offline", "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 272, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_test_mode", "value": "AccuracyOnly", "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 273, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_offline_expected_qps", "value": 0.05, "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 310, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_min_duration_ms", "value": 0, "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 316, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_max_duration_ms", "value": 0, "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 317, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_min_query_count", "value": 500, "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 318, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_max_query_count", "value": 500, "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 319, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 320, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_sample_index_rng_seed", "value": 10688027786191513374, "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 321, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_schedule_rng_seed", "value": 14962580496156340209, "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 323, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_accuracy_log_rng_seed", "value": 0, "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 324, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_accuracy_log_probability", "value": 0, "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 326, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_accuracy_log_sampling_target", "value": 0, "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 328, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_print_timestamps", "value": false, "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 330, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_performance_issue_unique", "value": false, "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 331, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_performance_issue_same", "value": false, "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 333, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_performance_issue_same_index", "value": 0, "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 335, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_performance_sample_count_override", "value": 5000, "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 337, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "requested_sample_concatenate_permutation", "value": false, "time_ms": 0.015860, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 339, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_scenario", "value": "Offline", "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 418, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_test_mode", "value": "AccuracyOnly", "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 419, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_samples_per_query", "value": 500, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 421, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_target_qps", "value": 0.05, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 422, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_target_latency_ns", "value": 0, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 423, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_target_latency_percentile", "value": 0.99, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 424, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_max_async_queries", "value": 1, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 426, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_target_duration_ms", "value": 0, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 427, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_min_duration_ms", "value": 0, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 429, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_max_duration_ms", "value": 0, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 430, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_min_query_count", "value": 1, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 431, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_max_query_count", "value": 500, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 432, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_min_sample_count", "value": 500, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 433, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 434, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_sample_index_rng_seed", "value": 10688027786191513374, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 435, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_schedule_rng_seed", "value": 14962580496156340209, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 437, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_accuracy_log_rng_seed", "value": 0, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 438, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_accuracy_log_probability", "value": 0, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 440, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_accuracy_log_sampling_target", "value": 0, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 442, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_print_timestamps", "value": false, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 444, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_performance_issue_unique", "value": false, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 445, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_performance_issue_same", "value": false, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 447, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_performance_issue_same_index", "value": 0, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 449, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_performance_sample_count", "value": 5000, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 451, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "effective_sample_concatenate_permutation", "value": false, "time_ms": 0.016040, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 453, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "generic_message", "value": "Starting accuracy mode", "time_ms": 0.024070, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1084, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "loaded_qsl_set", "value": [230,119,189,383,406,142,291,87,220,70,135,496,371,77,206,427,85,243,193,29,372,499,249,443,200,473,157,167,279,165,326,27,259,79,400,363,123,262,316,437,101,6,128,62,151,252,92,257,381,425,467,429,308,342,290,12,148,483,455,276,409,366,67,176,153,282,216,97,407,359,448,199,158,118,324,271,452,114,379,256,0,384,219,127,489,277,160,338,162,420,21,353,121,186,435,368,145,7,494,390,234,203,221,445,471,141,349,397,412,318,440,137,296,242,264,335,105,273,117,68,306,428,129,154,235,116,240,488,57,265,41,80,367,424,43,32,78,223,447,399,300,341,22,244,402,422,347,149,491,239,204,317,17,245,284,497,333,174,212,36,140,37,385,96,418,236,138,311,120,272,396,71,292,346,16,498,312,65,136,169,241,474,289,191,198,469,228,54,253,46,183,431,395,139,354,325,266,468,155,109,246,217,387,307,446,163,376,490,337,441,106,415,270,388,481,58,459,286,267,464,351,91,170,327,336,112,362,24,301,147,166,84,472,168,294,274,104,181,15,386,438,269,180,205,179,143,99,208,394,475,2,484,410,404,102,268,398,38,439,187,89,261,182,373,430,126,211,115,479,453,321,313,81,188,356,339,238,426,482,350,310,485,3,480,225,130,131,382,355,132,48,331,13,173,315,175,466,298,375,302,492,232,280,303,55,389,133,14,393,192,51,8,172,436,370,74,88,60,207,161,184,171,125,357,107,361,49,10,369,177,365,278,314,103,93,34,450,196,226,30,75,380,237,416,20,408,320,159,86,477,156,231,50,457,319,83,194,215,465,61,248,40,434,281,328,213,210,323,487,295,332,33,190,413,403,164,419,98,150,113,152,476,432,414,39,72,417,1,218,275,26,495,309,299,348,122,442,486,69,28,322,340,451,82,95,411,100,254,250,374,124,360,391,460,146,378,63,144,31,463,5,423,73,247,461,56,330,185,456,90,23,329,209,4,493,18,343,9,44,352,110,76,364,258,229,345,11,470,358,283,25,47,201,334,52,178,108,227,288,444,233,111,59,263,304,458,255,66,433,392,377,251,94,214,202,53,42,405,478,344,19,297,64,35,287,222,454,462,197,293,134,285,260,401,224,421,195,45,449,305], "time_ms": 0.032380, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 607, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "generated_query_count", "value": 1, "time_ms": 15.868068, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 426, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "generated_samples_per_query", "value": 500, "time_ms": 15.868068, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 427, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "generated_query_duration", "value": 20000000000, "time_ms": 15.868068, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 428, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "logger_swap_request_slots_retry_count", "value": 0, "time_ms": 363325.255112, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 902, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "logger_swap_request_slots_retry_retry_count", "value": 0, "time_ms": 363325.255112, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 904, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 363325.255112, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 906, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 363325.255112, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 908, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 363325.255112, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 910, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 363325.255112, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 912, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "power_begin", "value": "11-18-2024 22:35:28.790", "time_ms": 363325.257122, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 561, "pid": 15818, "tid": 15818}}
+:::MLLOG {"key": "power_end", "value": "11-18-2024 22:41:29.856", "time_ms": 363325.257122, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 563, "pid": 15818, "tid": 15818}}
diff --git a/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt
new file mode 100644
index 0000000..c725ef9
--- /dev/null
+++ b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/accuracy/mlperf_log_summary.txt
@@ -0,0 +1,4 @@
+
+No warnings encountered during test.
+
+1 ERROR encountered. See detailed log.
diff --git a/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json
new file mode 100644
index 0000000..0d4f101
--- /dev/null
+++ b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_accuracy.json
@@ -0,0 +1,2 @@
+[
+]
diff --git a/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt
new file mode 100644
index 0000000..4a41866
--- /dev/null
+++ b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_detail.txt
@@ -0,0 +1,88 @@
+:::MLLOG {"key": "error_invalid_config", "value": "Multiple conf files are used. This is not valid for official submission.", "time_ms": 18446744073709.206219, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": true, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 539, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "loadgen_version", "value": "4.1.23 @ 4763c6b5e7", "time_ms": 0.007650, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 53, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "loadgen_build_date_local", "value": "2024-11-18T21:39:51.630673", "time_ms": 0.007650, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 55, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "loadgen_build_date_utc", "value": "2024-11-18T21:39:51.630681", "time_ms": 0.007650, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 56, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "loadgen_git_commit_date", "value": "2024-11-15T21:09:48+00:00", "time_ms": 0.007650, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 57, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "loadgen_git_log_message", "value": "4763c6b5e7c3ad904c461bc1053674c448771ec4 Removed TEST05 compliance requirement (#1925)\ne398b90e85f9e64d34d6c67fe4b04d6cb7145c98 Update requirements.txt (#1907)\n97122a2aa017eb737fa9ab2f2508683073e8d247 Fix typo in fid_score.py, fail_safe for SDXL short runs, fix argument error in DLRMv2 implementation #1909, fixes preprocess_submission (#1910)\ndffd29273e98ffcbbfad0e66648c5d390d814509 Update artifact actions from v3 to v4 in build_wheels.yml (#1906)\nd3c01ed3de6618a8d39dc8a2a82871e598ea801f Update GNN reference implementation: add DGL backend (#1903)", "time_ms": 0.007650, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 58, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "loadgen_git_status_message", "value": "", "time_ms": 0.007650, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 60, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "loadgen_file_sha1", "value": {"/.clang-format":"012aad77e5206c89d50718c46c119d1f3cb056b2","/CMakeLists.txt":"d47a9d552d9f882a5250f1ba1e969f9ebca4281b","/MANIFEST.in":"ad32a45fd2cf9b05dcf9ffa884ae78b536237ba6","/README.md":"20a55bb946c2c0bbb564ced2af1e48efd096b3a8","/README_BUILD.md":"5f6c6a784e9cd6995db47f9b9f70b1769909c9d8","/README_FAQ.md":"01f9ae9887f50bc030dc6107e740f40c43ca388f","/VERSION.txt":"b704125a89b97a97513991ee33320e29d95916e2","/__init__.py":"d013101621ef06a0ddc5e7d9ce511918a8b2ebe6","/bindings/c_api.cc":"14d178b64c7fc45d090e038c08d9b78ca943c383","/bindings/c_api.h":"23d9f99e00b2d196e095fae0bb453a391c18d601","/bindings/python_api.cc":"9f538d2a5390c77ae0bc3f8a351bcdb2587bc66c","/diagram_network_submission.png":"53dba8ad4272190ceb6335c12fd25e53dc02a8cb","/diagram_submission.png":"84c2f79309b237cef652aef6a187ba8e875a3952","/early_stopping.cc":"0cd7b546a389deac73f7955cd39255ed76557d62","/early_stopping.h":"158fcae6a5f47e82150d6416fa1f7bcef37e77fe","/issue_query_controller.cc":"02fcfe6d9cf958eeb4b6f1f4dbe87ba7eb4d7dec","/issue_query_controller.h":"ed20934fd3507a15949d501ac154be38e766f6ab","/loadgen.cc":"42b50c087c6fea1005abbba369c22cb09d6a364a","/loadgen.h":"ce9fcb5d44951e7e9048a83b7c1a41c8b8e0f7d8","/loadgen_integration_diagram.svg":"47f748307536f80cfc606947b440dd732afc2637","/logging.cc":"49e63158ebca654fa4b7c5f3321054cf4d6c3a30","/logging.h":"5f6cc9ed4c4859641e05b1bb6a0ef860c852fcd8","/mlperf.conf":"0a4daef277bb3151139980e484dd5e644bf36e18","/mlperf_conf.h":"1813988201e2ff86f4fa8cf4c01685782e933c27","/pyproject.toml":"712fab87b72ba67ef2a068d0f9f47da65130342f","/query_dispatch_library.h":"1f18e9cd3ee4dc89a387cf462de1d0ceb1ece975","/query_sample.h":"c4f399103bc3d172079bbd4cd2b0ca0f22eebc4f","/query_sample_library.h":"8323a2225be1dff31f08ecc86b76eb3de06568bc","/requirements.txt":"a5ff7e77caa6e9e22ada90f0de0c865c987bf167","/results.cc":"239835696a1abe2cac9e866122d1dddc367e3548","/results.h":"fce22d5a588d91fd968a6b25c27896dba87bc276","/setup.py":"a5eaa6f713bd3dfb6603be2c7928f0c295d7ee30","/system_under_test.h":"18d4809589dae33317d88d9beeb5491a6e1ccdec","/test_settings.h":"476ecd4032f3bafe6f201df25d68aca4e177f659","/test_settings_internal.cc":"8827ef7d70e6c9a43dd25b4f42a6d2a9cecda428","/test_settings_internal.h":"2bb9e9ae53904cb0ca221f4a5d49ca7d9ec3b0ca","/utils.cc":"3df8fdabf6eaea4697cf25d1dcb89cae88e36efd","/utils.h":"40775e32d619ea6356826ae5ea4174c7911f6894","/version.cc":"cbec2a5f98f9786c8c3d8b06b3d12df0b6550fa0","/version.h":"9d574baa64424e9c708fcfedd3dbb0b518a65fcc","/version_generator.py":"9f23d13276194588473120a8a6ecf5a6ed034a23"}, "time_ms": 0.007650, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "version.cc", "line_no": 67, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "test_datetime", "value": "2024-11-18T22:25:25Z", "time_ms": 0.007890, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1193, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "sut_name", "value": "Multi-node SUT: N1, N2", "time_ms": 0.007890, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1194, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "get_sut_name_duration_ns", "value": 3140, "time_ms": 0.007890, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1195, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "qsl_name", "value": "PyQSL", "time_ms": 0.007890, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1196, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "qsl_reported_total_count", "value": 500, "time_ms": 0.007890, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1197, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "qsl_reported_performance_count", "value": 5000, "time_ms": 0.007890, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 1198, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_scenario", "value": "Offline", "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 272, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_test_mode", "value": "PerformanceOnly", "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 273, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_offline_expected_qps", "value": 0.05, "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 310, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_min_duration_ms", "value": 0, "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 316, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_max_duration_ms", "value": 0, "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 317, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_min_query_count", "value": 500, "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 318, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_max_query_count", "value": 500, "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 319, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 320, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_sample_index_rng_seed", "value": 10688027786191513374, "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 321, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_schedule_rng_seed", "value": 14962580496156340209, "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 323, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_accuracy_log_rng_seed", "value": 0, "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 324, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_accuracy_log_probability", "value": 0, "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 326, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_accuracy_log_sampling_target", "value": 0, "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 328, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_print_timestamps", "value": false, "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 330, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_performance_issue_unique", "value": false, "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 331, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_performance_issue_same", "value": false, "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 333, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_performance_issue_same_index", "value": 0, "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 335, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_performance_sample_count_override", "value": 5000, "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 337, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "requested_sample_concatenate_permutation", "value": false, "time_ms": 0.015020, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 339, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_scenario", "value": "Offline", "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 418, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_test_mode", "value": "PerformanceOnly", "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 419, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_samples_per_query", "value": 500, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 421, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_target_qps", "value": 0.05, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 422, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_target_latency_ns", "value": 0, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 423, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_target_latency_percentile", "value": 0.99, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 424, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_max_async_queries", "value": 1, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 426, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_target_duration_ms", "value": 0, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 427, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_min_duration_ms", "value": 0, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 429, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_max_duration_ms", "value": 0, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 430, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_min_query_count", "value": 1, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 431, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_max_query_count", "value": 500, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 432, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_min_sample_count", "value": 500, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 433, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_qsl_rng_seed", "value": 3066443479025735752, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 434, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_sample_index_rng_seed", "value": 10688027786191513374, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 435, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_schedule_rng_seed", "value": 14962580496156340209, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 437, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_accuracy_log_rng_seed", "value": 0, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 438, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_accuracy_log_probability", "value": 0, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 440, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_accuracy_log_sampling_target", "value": 0, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 442, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_print_timestamps", "value": false, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 444, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_performance_issue_unique", "value": false, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 445, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_performance_issue_same", "value": false, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 447, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_performance_issue_same_index", "value": 0, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 449, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_performance_sample_count", "value": 5000, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 451, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "effective_sample_concatenate_permutation", "value": false, "time_ms": 0.015180, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "test_settings_internal.cc", "line_no": 453, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "generic_message", "value": "Starting performance mode", "time_ms": 0.023500, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 835, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "loaded_qsl_set", "value": [230,119,189,383,406,142,291,87,220,70,135,496,371,77,206,427,85,243,193,29,372,499,249,443,200,473,157,167,279,165,326,27,259,79,400,363,123,262,316,437,101,6,128,62,151,252,92,257,381,425,467,429,308,342,290,12,148,483,455,276,409,366,67,176,153,282,216,97,407,359,448,199,158,118,324,271,452,114,379,256,0,384,219,127,489,277,160,338,162,420,21,353,121,186,435,368,145,7,494,390,234,203,221,445,471,141,349,397,412,318,440,137,296,242,264,335,105,273,117,68,306,428,129,154,235,116,240,488,57,265,41,80,367,424,43,32,78,223,447,399,300,341,22,244,402,422,347,149,491,239,204,317,17,245,284,497,333,174,212,36,140,37,385,96,418,236,138,311,120,272,396,71,292,346,16,498,312,65,136,169,241,474,289,191,198,469,228,54,253,46,183,431,395,139,354,325,266,468,155,109,246,217,387,307,446,163,376,490,337,441,106,415,270,388,481,58,459,286,267,464,351,91,170,327,336,112,362,24,301,147,166,84,472,168,294,274,104,181,15,386,438,269,180,205,179,143,99,208,394,475,2,484,410,404,102,268,398,38,439,187,89,261,182,373,430,126,211,115,479,453,321,313,81,188,356,339,238,426,482,350,310,485,3,480,225,130,131,382,355,132,48,331,13,173,315,175,466,298,375,302,492,232,280,303,55,389,133,14,393,192,51,8,172,436,370,74,88,60,207,161,184,171,125,357,107,361,49,10,369,177,365,278,314,103,93,34,450,196,226,30,75,380,237,416,20,408,320,159,86,477,156,231,50,457,319,83,194,215,465,61,248,40,434,281,328,213,210,323,487,295,332,33,190,413,403,164,419,98,150,113,152,476,432,414,39,72,417,1,218,275,26,495,309,299,348,122,442,486,69,28,322,340,451,82,95,411,100,254,250,374,124,360,391,460,146,378,63,144,31,463,5,423,73,247,461,56,330,185,456,90,23,329,209,4,493,18,343,9,44,352,110,76,364,258,229,345,11,470,358,283,25,47,201,334,52,178,108,227,288,444,233,111,59,263,304,458,255,66,433,392,377,251,94,214,202,53,42,405,478,344,19,297,64,35,287,222,454,462,197,293,134,285,260,401,224,421,195,45,449,305], "time_ms": 0.032000, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 607, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "generated_query_count", "value": 1, "time_ms": 15.732631, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 426, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "generated_samples_per_query", "value": 500, "time_ms": 15.732631, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 427, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "generated_query_duration", "value": 20000000000, "time_ms": 15.732631, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 428, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "generic_message", "value": "Ending naturally: Minimum query count and test duration met.", "time_ms": 16.850512, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "issue_query_controller.cc", "line_no": 482, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "logger_swap_request_slots_retry_count", "value": 0, "time_ms": 589976.962898, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 902, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "logger_swap_request_slots_retry_retry_count", "value": 0, "time_ms": 589976.962898, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 904, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "logger_swap_request_slots_retry_reencounter_count", "value": 0, "time_ms": 589976.962898, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 906, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "logger_start_reading_entries_retry_count", "value": 0, "time_ms": 589976.962898, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 908, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "logger_tls_total_log_cas_fail_count", "value": 0, "time_ms": 589976.962898, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 910, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "logger_tls_total_swap_buffers_slot_retry_count", "value": 0, "time_ms": 589976.962898, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "logging.cc", "line_no": 912, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "power_begin", "value": "11-18-2024 22:25:25.616", "time_ms": 589976.965818, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 561, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "power_end", "value": "11-18-2024 22:35:15.569", "time_ms": 589976.965818, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "loadgen.cc", "line_no": 563, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "result_validity", "value": "VALID", "time_ms": 590236.562211, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 674, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "result_min_duration_met", "value": true, "time_ms": 590236.562211, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 679, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "result_min_queries_met", "value": true, "time_ms": 590236.562211, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 680, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "early_stopping_met", "value": true, "time_ms": 590236.562211, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 681, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "early_stopping_result", "value": "", "time_ms": 590236.562211, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 700, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "result_query_count", "value": 1, "time_ms": 590236.562211, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 712, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "result_samples_per_second", "value": 0.847525, "time_ms": 590236.562211, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 768, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "result_min_latency_ns", "value": 359583940663, "time_ms": 590236.562211, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 774, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "result_max_latency_ns", "value": 589953295927, "time_ms": 590236.562211, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 775, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "result_mean_latency_ns", "value": 474768618295, "time_ms": 590236.562211, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 776, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "result_50.00_percentile_latency_ns", "value": 589953295927, "time_ms": 590236.562211, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 778, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "result_90.00_percentile_latency_ns", "value": 589953295927, "time_ms": 590236.562211, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 778, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "result_95.00_percentile_latency_ns", "value": 589953295927, "time_ms": 590236.562211, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 778, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "result_97.00_percentile_latency_ns", "value": 589953295927, "time_ms": 590236.562211, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 778, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "result_99.00_percentile_latency_ns", "value": 589953295927, "time_ms": 590236.562211, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 778, "pid": 14366, "tid": 14366}}
+:::MLLOG {"key": "result_99.90_percentile_latency_ns", "value": 589953295927, "time_ms": 590236.562211, "namespace": "mlperf::logging", "event_type": "POINT_IN_TIME", "metadata": {"is_error": false, "is_warning": false, "file": "results.cc", "line_no": 778, "pid": 14366, "tid": 14366}}
diff --git a/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt
new file mode 100644
index 0000000..b443de2
--- /dev/null
+++ b/open/UCSD/results/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main/stable-diffusion-xl/offline/performance/run_1/mlperf_log_summary.txt
@@ -0,0 +1,51 @@
+================================================
+MLPerf Results Summary
+================================================
+SUT name : Multi-node SUT: N1, N2
+Scenario : Offline
+Mode     : PerformanceOnly
+Samples per second: 0.847525
+Result is : VALID
+  Min duration satisfied : Yes
+  Min queries satisfied : Yes
+  Early stopping satisfied: Yes
+
+================================================
+Additional Stats
+================================================
+Min latency (ns)                : 359583940663
+Max latency (ns)                : 589953295927
+Mean latency (ns)               : 474768618295
+50.00 percentile latency (ns)   : 589953295927
+90.00 percentile latency (ns)   : 589953295927
+95.00 percentile latency (ns)   : 589953295927
+97.00 percentile latency (ns)   : 589953295927
+99.00 percentile latency (ns)   : 589953295927
+99.90 percentile latency (ns)   : 589953295927
+
+================================================
+Test Parameters Used
+================================================
+samples_per_query : 500
+target_qps : 0.05
+target_latency (ns): 0
+max_async_queries : 1
+min_duration (ms): 0
+max_duration (ms): 0
+min_query_count : 1
+max_query_count : 500
+qsl_rng_seed : 3066443479025735752
+sample_index_rng_seed : 10688027786191513374
+schedule_rng_seed : 14962580496156340209
+accuracy_log_rng_seed : 0
+accuracy_log_probability : 0
+accuracy_log_sampling_target : 0
+print_timestamps : 0
+performance_issue_unique : 0
+performance_issue_same : 0
+performance_issue_same_index : 0
+performance_sample_count : 5000
+
+No warnings encountered during test.
+
+1 ERROR encountered. See detailed log.
diff --git a/open/UCSD/systems/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main.json b/open/UCSD/systems/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main.json
new file mode 100644
index 0000000..af044f4
--- /dev/null
+++ b/open/UCSD/systems/aqua-reference-rocm-pytorch-v2.6.0.dev20241118-scc24-main.json
@@ -0,0 +1,37 @@
+{
+  "accelerator_frequency": "",
+  "accelerator_host_interconnect": "N/A",
+  "accelerator_interconnect": "N/A",
+  "accelerator_interconnect_topology": "",
+  "accelerator_memory_capacity": "N/A",
+  "accelerator_memory_configuration": "N/A",
+  "accelerator_model_name": "N/A",
+  "accelerator_on-chip_memories": "",
+  "accelerators_per_node": "0",
+  "cooling": "air",
+  "division": "open",
+  "framework": "pytorch v2.6.0.dev20241118",
+  "host_memory_capacity": "773G",
+  "host_memory_configuration": "undefined",
+  "host_network_card_count": "1",
+  "host_networking": "Gig Ethernet",
+  "host_networking_topology": "N/A",
+  "host_processor_caches": "L1d cache: 2 MiB (64 instances), L1i cache: 2 MiB (64 instances), L2 cache: 64 MiB (64 instances), L3 cache: 512 MiB (16 instances)",
+  "host_processor_core_count": "32",
+  "host_processor_frequency": "3799.0720",
+  "host_processor_interconnect": "",
+  "host_processor_model_name": "AMD EPYC 9354 32-Core Processor",
+  "host_processors_per_node": "2",
+  "host_storage_capacity": "4.9T",
+  "host_storage_type": "SSD",
+  "hw_notes": "",
+  "number_of_nodes": "1",
+  "operating_system": "Ubuntu 22.04 (linux-5.14.0-427.42.1.el9_4.x86_64-glibc2.35)",
+  "other_software_stack": "Python: 3.10.15, LLVM-15.0.6",
+  "status": "available",
+  "submitter": "UCSD",
+  "sw_notes": "Automated by MLCommons CM v3.4.1. ",
+  "system_name": "aqua",
+  "system_type": "datacenter",
+  "system_type_detail": "edge server"
+}
\ No newline at end of file