[cudaautotune] Implementing an autotuning interface and script - #380
[cudaautotune] Implementing an autotuning interface and script#380asubah wants to merge 14 commits into
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asubah
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| export CUDA_CXXFLAGS := -I$(CUDA_BASE)/include | ||
| export CUDA_TEST_CXXFLAGS := -DGPU_DEBUG | ||
| export CUDA_LDFLAGS := -L$(CUDA_LIBDIR) -lcudart -lcudadevrt | ||
| export CUDA_LDFLAGS := -L$(CUDA_LIBDIR) -lcudart -lcudadevrt -lcudaautotunert |
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Could this library be added only in src/cudaautotune/Makefile?
| namespace cms { | ||
| namespace cuda { | ||
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| class ExecutionConfiguration { |
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Currently this class appears to be used only as a "namespace", because the objects have no state.
On the other hand, if I understood correctly, the launch parameters are read from the file for each kernel for each event. Would it be feasible to read each file only once in some way?
| file >> blockSize; | ||
| file.close(); | ||
| } else { | ||
| std::cout << "Error in opening file " + filename + "\n"; |
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Does it make sense to continue the program if a file can not be opened? (currently the function returns an indeterminate value)
| #ifdef __CUDACC__ | ||
| uint32_t *poff = (uint32_t *)((char *)(h) + offsetof(Histo, off)); | ||
| int32_t *ppsws = (int32_t *)((char *)(h) + offsetof(Histo, psws)); | ||
| cms::cuda::ExecutionConfiguration exec; |
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This doesn't seem to be used.
| TARGET_NAME := $(notdir $(TARGET_DIR)) | ||
| TARGET := $(BASE_DIR)/$(TARGET_NAME) | ||
| include Makefile.deps | ||
| EXTERNAL_DEPENDS := $(cuda_EXTERNAL_DEPENDS) |
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This should be
| EXTERNAL_DEPENDS := $(cuda_EXTERNAL_DEPENDS) | |
| EXTERNAL_DEPENDS := $(cudaautotune_EXTERNAL_DEPENDS) |
| @@ -0,0 +1,12 @@ | |||
| cuda_EXTERNAL_DEPENDS := TBB CUDA EIGEN BOOST BACKTRACE | |||
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This should be
| cuda_EXTERNAL_DEPENDS := TBB CUDA EIGEN BOOST BACKTRACE | |
| cudaautotune_EXTERNAL_DEPENDS := TBB CUDA EIGEN BOOST BACKTRACE |
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| import argparse | |||
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How about adding
| import argparse | |
| #!/usr/bin/env python3 | |
| import argparse |
so that the script could be run "directly" (./src/cudaautotune/autotuning/tuner.py)?
| parser.add_argument('-p', '--process', type=pathlib.Path, nargs=1, required=True, | ||
| help='path to the program to be autotuned') | ||
| parser.add_argument('-c', '--configurations', type=pathlib.Path, nargs=1, | ||
| default=[pathlib.Path('src/cudaautotune/autotuning/kernel_configs')], help='path to save the configurations for the tunable process to read them. Default = autotuning/kernel_configs/') |
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Why the default value is in a list? (same for the following two arguments too)
| status = "" | ||
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| cpu_threads = config[tunables["cpu_threads"]] | ||
| gpu_streams = cpu_threads + config[tunables["gpu_streams"]] |
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It is not clear to me why the number of concurrent events (--numberOfStreams below) is set to "number of CPU threads" + something named "GPU streams". Could you clarify what is the intended behavior here wrt. CPU threads and concurrent events?
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This PR introduces an autotuning interface and a python script to autotune the CUDA kernel launch configurations.
Refer to the
README.mdfor instructions on how to use the script.The interface is simple. It just reads the block size from a file in
src/cudaautotune/autotuning/kernel_configs.Tested on a node with Intel Xeon Silver 4214R and a single T4.
Baseline configuration:
src/cudaautotune/autotuning/tunables-baseline.csv.Average Throughput: 1,195.66 ± 1.96 events/s.
Best config found by autotuning:
src/cudaautotune/autotuning/tunables.csv.Average Throughput: 1,269.46 ± 3.52 events/s.
The search space is too big, hence, I selected a subset of the kernels that has the highest runtime and randomly autotuned them. Then fixed the configurations on the best found configuration, and tuned another set of kernels until all kernels are visited.
I appreciate your comments and suggestions regarding the interface or the script.