Results on system SCC2-Diablo

Author: YfLi03

open/scc2/code/stable-diffusion-xl/README.md

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+TBD

open/scc2/measurements/f2ea47b0a016-nvidia_original-gpu-tensorrt-vdefault-scc24-main/README.md

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+| Model               | Scenario   | Accuracy             |   Throughput | Latency (in ms)   |
+|---------------------|------------|----------------------|--------------|-------------------|
+| stable-diffusion-xl | offline    | (16.6316, 234.62921) |        7.465 | -                 |

open/scc2/measurements/f2ea47b0a016-nvidia_original-gpu-tensorrt-vdefault-scc24-main/stable-diffusion-xl/offline/README.md

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+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-6.1.0-27-amd64-x86_64-with-glibc2.29
+* CPU version: x86_64
+* Python version: 3.8.10 (default, Sep 11 2024, 16:02:53) 
+[GCC 9.4.0]
+* MLCommons CM version: 3.3.3
+
+## 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=f72ffc1c4ac088b2f78855b05b3ade8ffb2ca497
+
+cm run script \
+	--tags=run-mlperf,inference,_r4.1-dev,_short,_scc24-main \
+	--model=sdxl \
+	--implementation=nvidia \
+	--framework=tensorrt \
+	--category=datacenter \
+	--scenario=Offline \
+	--execution_mode=test \
+	--device=cuda \
+	--min_query_count=528 \
+	--adr.nvidia-harness.use_graphs=True \
+	--adr.nvidia-harness.gpu_inference_streams=4 \
+	--adr.nvidia-harness.gpu_copy_streams=2 \
+	--rerun \
+	--clean \
+	--quiet
+```
+*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: f2ea47b0a016-nvidia_original-gpu-tensorrt-vdefault-scc24-main
+
+Model Precision: int8
+
+### Accuracy Results 
+`CLIP_SCORE`: `16.6316`, Required accuracy for closed division `>= 31.68632` and `<= 31.81332`
+`FID_SCORE`: `234.62921`, Required accuracy for closed division `>= 23.01086` and `<= 23.95008`
+
+### Performance Results 
+`Samples per second`: `7.46497`