[N] HGX-2 Deep Learning Benchmarks: The 81,920 CUDA Core “Behemoth” GPU Server
![[N] HGX-2 Deep Learning Benchmarks: The 81,920 CUDA Core “Behemoth” GPU Server](https://b.thumbs.redditmedia.com/ChRg2Tv4q7FezhnyirCPraStgnzY14SM6P2kz7pl7bY.jpg "[N] HGX-2 Deep Learning Benchmarks: The 81,920 CUDA Core “Behemoth” GPU Server") |
Deep learning benchmarks for TensorFlow on Exxact TensorEX HGX-2 Server. Original Post from Exxact Here Notable GPU Server Features
Tests were run on ResNet-50, ResNet-152, Inception V3, VGG-16. Also compared FP16 to FP32 performance, and used batch size of 256 (except for ResNet152 FP32, the batch size was 64). Same tests run using 1,2,4,8 and 16 GPU configurations. All benchmarks were done using ‘vanilla’ TensorFlow settings for FP16 and FP32. For the full write-up + tables and numbers visit: https://blog.exxactcorp.com/hgx2-benchmarks-for-deep-learning-in-tensorflow-16x-v100-exxact-tensorex-server/ submitted by /u/exxact-jm |
