## VGG16 performance analysis（V2 vs Fluid） ## Config and Env - VGG16: - DataSet:cifar10 - Input: 3 * 32 * 32 - Batch_size = 32, iterations= 280, skip_batch_num=20 - Python code: https://github.com/dzhwinter/benchmark/tree/fluid_v2_speed_comparison - commit: ed5cdb9af1130e7a0691080a62017ffeb9dc8004 - Env: - nvidia-docker, TITAN X (Pascal), single machine. - OMP_NUM_THREADS=1 - MKL_NUM_THREADS=1 ### GPU -|sec/batch | examples/sec -- | -- | -- fluid | 0.02787| 1234.08278 v2 | 0.02190 | 1461.31938 ### CPU -| sec/batch | examples/sec -- | -- | -- fluid | 1.47648 | 21.71837 v2 | 1.47969 | 21.62613
VGG16 performance analysis（V2 vs Fluid）
Config and Env
GPU
CPU