Recent content by dhenzjhen

No.

Hi Luke, Sorry I don't have access to GPU servers anymore.

System: Supermicro SYS-4028GR-TXRT Motherboard: X10DG0-T CPU: E5 2699V4 x 2 MEM: 32GB Micron x 12 BIOS: 5/25/17 GPU: Nvidia Tesla V100 SXM2 x 8 | P100 SXM2 x 8 OS: Ubuntu 16.04 x64 Driver: 384.81 Deep learning framework: NV-Caffe CUDA: version 9 Tensor core FTW!!!

Tested P100 while am at it before switching the V100 tray :D

System: Supermicro SYS-4028GR-TXRT Motherboard: X10DG0-T CPU: E5 2699V4 x 2 MEM: 32GB Micron x 12 BIOS: 5/25/17 GPU: Nvidia Tesla P100 SXM2 x 8 OS: Ubuntu 16.04 x64 Driver: 384.81 CUDA: version 9

Thank u sir!

This is only a speed training testing without any accuracy or tuning involved. I only want to test and compare the V100s and P100s in terms of crunching speed. In this testing, I used 1281167 training images and 50000 validation images (ILSVRC2012) and NV-caffe for deep learning framework. On...

Thank you sir! Sent from my SM-N900T using Tapatalk

System: Supermicro SYS-4028GR-TXRT Motherboard: X10DG0 CPU: E5 2699V4 x 2 MEM: 32GB Micron x 12 BIOS: 5/25/17 GPU: Nvidia Tesla V100 SXM2 x 8 OS: Centos 7.2 x64 Driver: 384.81 CUDA: version 9 HPL: hpl_cuda_9_ompi1102_gcc_485_volta_pascal_kepler_v_8_23_17_preliminary (NDA) -dhenzjhen@OCN

Initiate splinter sequence!!!!

No need for fancy 4k monitor since you can do it remotely. Here's the run did last time just in case you want to see it using caffe and DIGITS.

Because majority of deep/machine learning guides online are all based on Ubuntu. Sent from my SM-N900T using Tapatalk

Thanks u sir for the offer. I got the same system also currently testing for some customer.

I tried training images with digits and it's fun but of course the backend still using caffe :) Index of /~chmod755/sth