PageRank (PR) algorithm for sparse graphs using CUDA Toolkit.
NOTE: Execution time doesnt include memory allocation. It is done ahead of time.
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order: 29008 size: 38416 {}
order: 29008 size: 38416 {}
[00885.7 ms] pageRankPush
[00009.5 ms] pageRank
[00020.1 ms] pageRankCuda
==1163== NVPROF is profiling process 1163, command: ./a.out data/aug2d.mtx
==1163== Profiling application: ./a.out data/aug2d.mtx
==1163== Profiling result:
Type Time(%) Time Calls Avg Min Max Name
GPU activities: 94.24% 16.860ms 25 674.42us 670.04us 683.00us void pageRankKernelStep<float>(float*, float*, int*, int*, float, int)
1.83% 327.80us 25 13.112us 12.991us 14.016us void sumIfNotKernel<float, int>(float*, float*, int*, int)
1.76% 314.01us 25 12.560us 12.448us 12.960us void errorAbsKernel<float>(float*, float*, float*, int)
0.89% 158.37us 56 2.8270us 2.3670us 16.896us [CUDA memcpy DtoH]
0.67% 119.29us 25 4.7710us 4.7030us 5.3120us void multiplyKernel<float>(float*, float*, float*, int)
0.43% 76.127us 10 7.6120us 1.5360us 24.096us [CUDA memcpy HtoD]
0.04% 7.4880us 1 7.4880us 7.4880us 7.4880us void pageRankFactorKernel<float, int>(float*, int*, float, int)
0.04% 6.3360us 1 6.3360us 6.3360us 6.3360us void dotProductKernel<int>(int*, int*, int*, int)
0.03% 6.1760us 1 6.1760us 6.1760us 6.1760us void errorAbsKernel<int>(int*, int*, int*, int)
0.03% 5.6320us 1 5.6320us 5.6320us 5.6320us void sumKernel<int>(int*, int*, int)
0.02% 4.4480us 1 4.4480us 4.4480us 4.4480us void fillKernel<float>(float*, int, float)
0.02% 3.0080us 1 3.0080us 3.0080us 3.0080us void addKernel<int>(int*, int, int)
0.01% 2.3360us 1 2.3360us 2.3360us 2.3360us void fillKernel<int>(int*, int, int)
API calls: 87.44% 153.74ms 19 8.0918ms 3.2640us 152.75ms cudaMalloc
10.88% 19.137ms 66 289.95us 12.216us 723.58us cudaMemcpy
0.83% 1.4652ms 107 13.693us 7.5780us 159.44us cudaLaunchKernel
0.39% 690.48us 18 38.360us 3.8500us 152.74us cudaFree
0.32% 562.27us 1 562.27us 562.27us 562.27us cuDeviceTotalMem
0.11% 197.24us 97 2.0330us 156ns 74.846us cuDeviceGetAttribute
0.01% 24.393us 1 24.393us 24.393us 24.393us cuDeviceGetName
0.00% 8.0020us 1 8.0020us 8.0020us 8.0020us cuDeviceGetPCIBusId
0.00% 1.9220us 3 640ns 154ns 1.0450us cuDeviceGetCount
0.00% 1.7090us 2 854ns 286ns 1.4230us cuDeviceGet
0.00% 271ns 1 271ns 271ns 271ns cuDeviceGetUuid# Download program
rm -rf pagerank-sparse
git clone https://github.com/cudaf/pagerank-sparse# Run
cd pagerank-sparse && nvcc -Xcompiler -fopenmp -O3 main.cu && nvprof ./a.out data/aug2d.mtx- PageRank Algorithm, Mining massive Datasets (CS246), Stanford University
- CUDA by Example :: Jason Sanders, Edward Kandrot
- RAPIDS CUDA DataFrame Internals for C++ Developers - S91043