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VGG16 performance analysis #39

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chengduoZH opened this issue Dec 29, 2017 · 0 comments

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chengduoZH commented Dec 29, 2017

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: ed5cdb9
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

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