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Comm|Scope

Build Status

CUDA- and NUMA-Aware Multi-CPU / Multi-GPU communication benchmarks.

Prerequisites

  • CMake 3.17+
  • g++ >= 4.9
  • CUDA toolkit >= 8.0

Getting started

Recursive git clone:

git clone --recursive https://github.com/c3sr/comm_scope.git

Or, if you cloned without recursiveness:

<dowload or clone Comm|Scope>
git submodule update --init --recursive

Build and list supported benchmarks:

mkdir build && cd build
cmake ..
make
./comm_scope --benchmark_list_tests=true

To choose specific benchmarks, filter by regex:

./comm_scope --benchmark_list_tests --benchmark_filter=<regex>

Once the desired benchmarks are selected, run them

./comm_scope --benchmark_filter=<regex>

Advanced

CSV Output (will still print on console):

./comm_scope --benchmark_out=file.csv --benchmark_out_format=csv

To limit the visible GPUs, use the --cuda option:

./comm_scope --cuda 0 --cuda 1

To limit the visible NUMA nodes, use the --numa option:

./comm_scope --numa 8

Comm|Scope will attempt to control CPU clocks. Either run with elevated permissions, or you will see:

[2020-07-15 17:58:00.763] [scope] [error] unable to disable CPU turbo: no permission. Run with higher privileges?
[2020-07-15 17:58:00.763] [scope] [error] unable to set OS CPU governor to maximum: no permission. Run with higher privileges?

If you are willing to accept reduced accuracy, or are on a system where CPU clocks do not need to be controlled, you can ignore this error.

Warning: Inconsistent Console Reporting Suffixes

Google Benchmark will format the console output in the following way, with an inconsistency. The bytes suffixes (k, M, G) are powers of 10 (1e3, 1e6, 1e9), while the bytes_per_second suffixes are powers of 2 (2^10, 2^20, 2^30). For example, the raw values for line 12 are bytes=4096 and bytes_per_second=1.33407e+09. Using the csv reporter prints the raw values to the file: --benchmark_out=file.csv and --benchmark_out_format=csv.

----------------------------------------------------------------------------------------------------------------------------
Benchmark                                                                  Time             CPU   Iterations UserCounters...
----------------------------------------------------------------------------------------------------------------------------
Comm_cudaMemcpyAsync_PinnedToGPU/0/0/log2(N):8/manual_time              2804 ns   1065385791 ns       251315 bytes=256 bytes_per_second=87.0571M/s cuda_id=0 numa_id=0
Comm_cudaMemcpyAsync_PinnedToGPU/0/0/log2(N):9/manual_time              2806 ns   1059562408 ns       250053 bytes=512 bytes_per_second=173.985M/s cuda_id=0 numa_id=0
Comm_cudaMemcpyAsync_PinnedToGPU/0/0/log2(N):10/manual_time             2871 ns   1055014030 ns       246220 bytes=1024 bytes_per_second=340.196M/s cuda_id=0 numa_id=0
Comm_cudaMemcpyAsync_PinnedToGPU/0/0/log2(N):11/manual_time             3033 ns   1070865035 ns       241507 bytes=2.048k bytes_per_second=643.883M/s cuda_id=0 numa_id=0
Comm_cudaMemcpyAsync_PinnedToGPU/0/0/log2(N):12/manual_time             3070 ns    984282144 ns       224948 bytes=4.096k bytes_per_second=1.24245G/s cuda_id=0 numa_id=0

OLCF Summit

Get a launch node: bsub -W 2:00 -nnodes 1 -P csc362 -Is /bin/zsh

You will need to load a newer gcc, as well as CUDA, to build and run Comm|Scope

module load cuda
module load gcc/5.4.0

Then to build, do

cmake ..
make -j

Example job submission scripts are in scripts/summit.

You may ignore messages like the following, where libscope fails to control CPU turbo and the governor. On managed systems like Summit, this is not necessary.

[2020-07-15 17:58:00.763] [scope] [error] unable to disable CPU turbo: no permission. Run with higher privileges?
[2020-07-15 17:58:00.763] [scope] [error] unable to set OS CPU governor to maximum: no permission. Run with higher privileges?

FAQ / Troubleshooting

** I get CMake Error: Remove failed on file: <blah>: System Error: Device or resource busy**

This somtimes happens on network file systems. You can retry, or do the build on a local disk.

** I get -- The CXX compiler identification is GNU 4.8.5 after module load gcc/5.4.0.

A different version of GCC may be in the CMake cache. Try running cmake -DCMAKE_CXX_COMPILER=g++ -DCMAKE_C_COMPILER=gcc, or deleting your build directory and restarting.

** I get a PTX JIT compilation failed **

set CUDAFLAGS to be the appropriate -arch=sm_xx for your system. e.g. export CUDAFLAGS=-arch=sm_80 for ThetaGPU.

Bumping the Version

Update the changelog and commit the changes.

Install bump2version

pip install --user bump2version

Check that everything seems good (minor version, for example)

bump2version --dry-run minor --verbose

Actually bump the version

bump2version minor

Push the changes

git push && git push --tags

Contributing

Any work on the underlying cwpearson/libscope library will probably benefit from changing the submodule from http to SSH:

cd thirdparty/libscope
git remote set-url origin git@github.com:cwpearson/libscope.git

Contributors

Changelog

v0.11.2 (July 17 2020)

  • cwpearson/libscope v1.1.2
  • silence some warnings

v0.11.1 (July 17 2020)

  • cwpearson/libscope v1.1.1

v0.11.0 (July 17 2020)

  • cwpearson/libscope v1.1.0
  • cudaGraphInstantiate and cudaGraphLaunch
  • Reduce maximum cudaMemcpyPeerAsync size, since it is not truly async above ~2^27 which breaks the measurement strategy.

v0.10.0 (June 23 2020)

  • Rely on cwpearson/libscope instead of c3sr/scope
  • cwpearson/libscope v1.0.0
  • Remove dependence on sugar
  • Add 3D strided memory transfer benchmarks
  • Add CUDA runtime microbenchmarks
  • Remove some duplicate NUMA-/non-NUMA-aware implementations of cudaMemcpyAsync benchmarks

v0.9.0 (June 5 2020)

  • Add CPU-GPU and GPU-GPU sparse data transfer benchmarks
    • cudaMemcpy3DAsync
    • cudaMemcpy3DPeerAsync
    • cudaMemcpy2DAsync
    • custom 3D kernel
    • pack / cudaMemcpyPeerAsync / unpack

v0.8.2 (March 6 2020)

  • Fix a event-device mismatch in multi-GPU unidirectional cudaMemcpyPeer benchmarks

v0.8.1 (March 5 2020)

  • Disable peer access in non-peer cudaMemcpyPeer benchmarks

v0.8.0 (March 5 2020)

  • Add cudaMemcpyPeer uni/bidirectional benchmarks.

v0.7.2 (April 8 2019)

  • Add memory to the clobber list for for x86 and ppc64le cache flushing.

v0.7.1 (April 5 2019)

  • Add v0.7.0 and v0.7.1 changelog

v0.7.0 (April 5 2019)

  • Make POWER's cache flushing code match the linux kernel.
  • rename "Coherence" benchmarks to "Demand"
  • remove cudaStreamSynchronize from the timing path of zerocopy-duplex, demand-duplex, and prefetch-duplex
  • Transition to better use of CMake's CUDA language support
  • Use NVCC's compiler defines to check the CUDA version
  • Disable Comm|Scope by default during Scope compilation

v0.6.3 (Dec 20 2018)

  • Add USE_NUMA CMake option
  • Fix compile errors when USE_NUMA=0 or NUMA cannot be found

v0.6.2

  • Fix checking non-existent cudaDeviceProp field in CUDA < 9

v0.6.1

  • Conform to updated SCOPE_REGSITER_AFTER_INIT

v0.6.0

  • Add unified memory allocation benchmarks
  • Flush CPU caches in zero-copy benchmarks
  • Add zerocopy duplex benchmarks
  • Add unified memory prefetch duplex benchmark
  • Add unified memory demand duplex benchmark
  • Conform to updated SCOPE_REGSITER_AFTER_INIT

v0.5.0

  • Add zero-copy benchmarks
  • Don't use nvToolsExt

v0.4.0

  • Add multithreaded Coherence GPU to Host benchmark
  • Programatically register most benchmarks based on system configuration
  • use cudaMemcpyAsync in numa-memcpy
  • Add travis and Dockerfiles
  • Use aligned_alloc in numa-memcpy/pinned-to-gpu
  • Add x86 and POWER cache control functions

v0.3.0

  • Rework documentation
  • Use target_include_scope_directories and target_link_scope_libraries.
  • Use Clara for flags.
  • Remove numa/rd and numa/wr.

v0.2.0

  • Add --numa_ids command line flag.
  • Use --cuda_device_ids and --numa_ids to select CUDA and NUMA devices for benchmarks.