eigen/bench/tensors
2016-05-13 14:32:17 -07:00
..
benchmark_main.cc
benchmark.h
contraction_benchmarks_cpu.cc Added benchmarks for contraction on CPU. 2016-05-13 14:32:17 -07:00
README Added benchmarks for contraction on CPU. 2016-05-13 14:32:17 -07:00
tensor_benchmarks_cpu.cc
tensor_benchmarks_fp16_gpu.cu Added a benchmark to measure the performance of full reductions of 16 bit floats 2016-05-05 14:15:11 -07:00
tensor_benchmarks_gpu.cu Added benchmarks for full reduction 2016-02-29 14:57:52 -08:00
tensor_benchmarks.h Added a benchmark to measure the performance of full reductions of 16 bit floats 2016-05-05 14:15:11 -07:00

The tensor benchmark suite is made of several parts.

The first part is a generic suite, in which each benchmark comes in 2 flavors: one that runs on CPU, and one that runs on GPU.

To compile the floating point CPU benchmarks, simply call:
g++ tensor_benchmarks_cpu.cc benchmark_main.cc -I ../../ -std=c++11 -O3 -DNDEBUG -pthread -mavx -o benchmarks_cpu

To compile the floating point GPU benchmarks, simply call:
nvcc tensor_benchmarks_gpu.cu benchmark_main.cc -I ../../ -std=c++11 -O2 -DNDEBUG -arch compute_35 -o benchmarks_gpu

We also provide a version of the generic GPU tensor benchmarks that uses half floats (aka fp16) instead of regular floats. To compile these benchmarks, simply call the command line below. You'll need a recent GPU that supports compute capability 5.3 or higher to run them and nvcc 7.5 or higher to compile the code.
nvcc tensor_benchmarks_fp16_gpu.cu benchmark_main.cc -I ../../ -std=c++11 -O2 -DNDEBUG -arch compute_53 -o benchmarks_fp16_gpu

last but not least, we also provide a suite of benchmarks to measure the scalability of the contraction code on CPU. To compile these benchmarks, call 
g++ contraction_benchmarks_cpu.cc benchmark_main.cc -I ../../ -std=c++11 -O3 -DNDEBUG -pthread -mavx -o benchmarks_cpu