AC-SpGEMM

Public repository holding source code for AC-SpGEMM

General Information

This repository holds the implementation for AC-SpGEMM and three different executables used for testing. This framework can be used to setup AC-SpGEMM, run it with different matrices, test its performance against cuSparse (the other frameworks are not included in this public repository).

Tested Setup

Requirements

NVIDIA CUDA Toolkit, a C++14 enabled compiler, CMake, a reasonable modern GPU as well as NVIDIA CUB

Framework has been tested with the following versions:

CUDA 9.1/9.2/10.0
gcc-6/gcc-7 or MVSC (VS17) (c++14 support required)
CMake 3.2 or higher
GPU with CC 6.1
CUB v1.8.0

Set CUDACXX in setup.sh and CUDA_INCLUDE_PATH as well as CUDA_BUILD_CCXX in CMakeLists.txt to the appropriate values for your system. To download the matrices used for evaluation, download the ssgui tool from SuiteSparse, filtering the set of all matrices by setting the minimum number of non-zeros to 10000(i.e. only testing matrices of non-trivial size).

Linux:

Run setup.sh from top level directory.

Windows:

Download CUB (tested with v1.8.0), create folder external in include folder and extract contents into this folder. Create folder build in top-level directory. Setup CMake to setup project into this build folder.

Running project

After building the project, 3 executables should be present

HostTest
performTestCase
checkBitStability

Reproducing Results

To get the timing and memory data from the framework, simply run test/runall.sh(Linux)/.bat(Win), changing the folder parameter to a folder holding the matrices in .mtx format to test all the matrices in this folder with AC-SpGEMM and cuSparse. If detailed timing results and memory results should be required, the last parameter of the Multiply call has to be changed to true, this will disable streams, print out more information and gather individual stage timings and memory measurements.

HostTest

Sourcecode available in source/main.cpp, can be called as ./HostTest <matrix.mtx> [deviceID] [testing] (e.g. ./HostTest 1138_bus.mtx 0 0). Testing enabled will check the output matrix of AC-SpGEMM vs cuSparse.

performTestCase

Sourcecode available in source/performTestCase.cpp, can be called as ./performTestCase <folder_with_matrices> <runtests> <deviceID> <continue_run> <run_traits> <bitmask for run selection> <datatype (f/d)>

folder_with_matrices : A folder containing matrices to test
runtests : Enabled (1) if tests should be run, (0) only statistics run
deviceID : Which device to use (e.g. 0)
continue_run : Set to true for testing
run_traits : These traits are used to select a configuration, the parameters are
- Threads (256)
- BlocksPerMP (3)
- NNZPerThread (2)
- InputElementsPerThreads (4)
- RetainElementsPerThreads (4)
- MaxChunksToMerge (16)
- MaxChunksGeneralizedMerge (512)
- MergePathOptions (8)
bitmask for run selection : Select which approaches to run
- Bit 0: cuSparse
- Bit 1: AC-SpGEMM
- E.g.: To run both cuSparse + acSpGEMM : 3
datatype (f/d) : either float(f) or double(d)

Example: ./performTestCase folder 1 0 1 256,3,2,4,4,16,512,8 3 f. This testcase is typically called with a script (e.g. /test/runall.sh) which repeatedly calls this executable until all aproaches were tested on all matrices in the folder. The reason behind this strategy is to get a fresh launch for each individual testcase, such that a failing testcase is not able to use up resources for another testcase. To run a full testrun on a folder, change the folder in the test/runall.sh/bat script and run the script.

checkBitStability

Sourcecode available in source/checkBitStability.cpp. Works similarly to performTestCase, checks the approaches for bitstable results.

Important Information

AC-SpGEMM is highly configurable as can be seen with the traits in the performTestCase, these traits are implemented as template parameters. Hence, for all combinations used, the respective instantiation must be present. Instantiations can be created by modifying the call to Multiply in source/GPU/Multiply.cu in line 781, which is given as

bool called = 
	EnumOption<256, 256, 128, // Threads
	EnumOption<3, 4, 1, // BlocksPerMP
	EnumOption<2, 2, 1, // NNZPerThread
	EnumOption<4, 4, 1, // InputElementsPerThreads
	EnumOption<4, 4, 1, // RetainElementsPerThreads
	EnumOption<16, 16, 8, // MaxChunksToMerge
	EnumOption<256, 512, 256, // MaxChunksGeneralizedMerge
	EnumOption<8, 8, 8, // MergePathOptions
	EnumOption<0, 1, 1>>>>>>>>> // DebugMode
			::call(Selection<MultiplyCall<DataType>>(call), scheduling_traits.Threads, scheduling_traits.BlocksPerMp, scheduling_traits.NNZPerThread, scheduling_traits.InputElementsPerThreads, scheduling_traits.RetainElementsPerThreads, scheduling_traits.MaxChunksToMerge, scheduling_traits.MaxChunksGeneralizedMerge, scheduling_traits.MergePathOptions, (int)Debug_Mode);

This expanding template will instantiate variants of MultiplyCall with the parameters specified in EnumOption<Start, End, Step>, so each EnumOption describes all the possible values for a certain property and all different configurations will be instantiated (e.g. BlocksPerMP with EnumOption<3, 4, 1, will instantiate the template call with BlocksPerMP=3 and BlocksPerMP=4)

FAQ

For any questions please directly contact Martin Winter martin.winter@icg.tugraz.at

GPUPeople / ACSpGEMM