57 lines
1.8 KiB
Markdown
57 lines
1.8 KiB
Markdown
GPU-STREAM
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==========
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Measure memory transfer rates to/from global device memory on GPUs.
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This benchmark is similar in spirit, and based on, the STREAM benchmark [1] for CPUs.
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Unlike other GPU memory bandwidth benchmarks this does *not* include the PCIe transfer time.
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Usage
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-----
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Build the OpenCL and CUDA binaries with `make` (CUDA version requires CUDA >= v6.5)
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Run the OpenCL version with `./gpu-stream-ocl` and the CUDA version with `./gpu-stream-cuda`
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Android
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-------
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Assuming you have a recent Android NDK available, you can use the
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toolchain that it provides to build GPU-STREAM. You should first
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use the NDK to generate a standalone toolchain:
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# Select a directory to install the toolchain to
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ANDROID_NATIVE_TOOLCHAIN=/path/to/toolchain
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${NDK}/build/tools/make-standalone-toolchain.sh \
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--platform=android-14 \
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--toolchain=arm-linux-androideabi-4.8 \
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--install-dir=${ANDROID_NATIVE_TOOLCHAIN}
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Make sure that the OpenCL headers and library (libOpenCL.so) are
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available in `${ANDROID_NATIVE_TOOLCHAIN}/sysroot/usr/`.
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You should then be able to build GPU-STREAM:
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make CXX=${ANDROID_NATIVE_TOOLCHAIN}/bin/arm-linux-androideabi-g++
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Copy the executable and OpenCL kernels to the device:
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adb push gpu-stream-ocl /data/local/tmp
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adb push ocl-stream-kernels.cl /data/local/tmp
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Run GPU-STREAM from an adb shell:
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adb shell
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cd /data/local/tmp
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# Use float if device doesn't support double, and reduce array size
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./gpu-stream-ocl --float -n 6 -s 10000000
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Results
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-------
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Sample results can be found in the `results` subdirectory. If you would like to submit updated results, please submit a Pull Request.
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[1]: McCalpin, John D., 1995: "Memory Bandwidth and Machine Balance in Current High Performance Computers", IEEE Computer Society Technical Committee on Computer Architecture (TCCA) Newsletter, December 1995.
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