Rye-GPU
From FarmShare
Nvidia GPU
Farmshare has GPU's via two systems, rye01 and rye02. You can use these two systems as you would a corn system:
ssh rye01.stanford.edu
or
ssh rye02.stanford.edu
bishopj@scorn:~$ ssh rye01 rye01.stanford.edu - Ubuntu 13.04, amd64 8-core Xeon E5620 @ 2.40GHz (FT72-B7015, empty); 47.16GB RAM, 10GB swap Puppet environment: rec_master; kernel 3.8.0-30-generic (x86_64) --*-*- Stanford University Research Computing -*-*-- _____ ____ _ | ___|_ _ _ __ _ __ ___ / ___|| |__ __ _ _ __ ___ | |_ / _` | '__| '_ ` _ \\___ \| '_ \ / _` | '__/ _ \ | _| (_| | | | | | | | |___) | | | | (_| | | | __/ |_| \__,_|_| |_| |_| |_|____/|_| |_|\__,_|_| \___| http://farmshare.stanford.edu ### ## # new to Ubuntu 13.04 Farmshare? # follow this link to get started: # https://www.stanford.edu/group/farmshare/cgi-bin/wiki/index.php/Ubuntu13TransitionGuide ## ### Last login: Sun Sep 15 20:52:27 2013 from scorn.stanford.edu your cuda device is: CUDA_VISIBLE_DEVICES=6 device last used: unused bishopj@rye01:~$ w 21:23:57 up 2 days, 3:09, 7 users, load average: 1.02, 1.05, 1.05 USER TTY FROM LOGIN@ IDLE JCPU PCPU WHAT rpropper pts/5 c-24-5-176-236.h Sat15 1:18m 0.11s 0.11s -tcsh rpropper pts/6 c-24-5-176-236.h Sat16 27:49m 0.00s 0.00s sshd: rpropper [priv] rpropper pts/7 216.239.45.130:S Sat21 23:57m 23:54m 23:54m ./liquid_model rpropper pts/8 216.239.45.130:S 15:15 1:58m 2:23 2:23 ./MF -d 7 bishopj pts/9 scorn.stanford.e 20:44 39:26 0.09s 0.09s -bash root pts/11 scorn.stanford.e 20:49 26:38 0.13s 0.13s -bash bishopj pts/13 scorn.stanford.e 21:23 4.00s 0.08s 0.00s w bishopj@rye01:~$ module load cuda (reverse-i-search)`device': less getcud^Cvice.sh bishopj@rye01:~$ /usr/local/cuda/samples/bin/x86_64/linux/release/deviceQuery /usr/local/cuda/samples/bin/x86_64/linux/release/deviceQuery Starting... CUDA Device Query (Runtime API) version (CUDART static linking) Detected 1 CUDA Capable device(s) Device 0: "Tesla C2070" CUDA Driver Version / Runtime Version 5.5 / 5.5 CUDA Capability Major/Minor version number: 2.0 Total amount of global memory: 5375 MBytes (5636554752 bytes) (14) Multiprocessors, ( 32) CUDA Cores/MP: 448 CUDA Cores GPU Clock rate: 1147 MHz (1.15 GHz) Memory Clock rate: 1494 Mhz Memory Bus Width: 384-bit L2 Cache Size: 786432 bytes Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65535), 3D=(2048, 2048, 2048) Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 2048 layers Total amount of constant memory: 65536 bytes Total amount of shared memory per block: 49152 bytes Total number of registers available per block: 32768 Warp size: 32 Maximum number of threads per multiprocessor: 1536 Maximum number of threads per block: 1024 Max dimension size of a thread block (x,y,z): (1024, 1024, 64) Max dimension size of a grid size (x,y,z): (65535, 65535, 65535) Maximum memory pitch: 2147483647 bytes Texture alignment: 512 bytes Concurrent copy and kernel execution: Yes with 2 copy engine(s) Run time limit on kernels: No Integrated GPU sharing Host Memory: No Support host page-locked memory mapping: Yes Alignment requirement for Surfaces: Yes Device has ECC support: Enabled Device supports Unified Addressing (UVA): Yes Device PCI Bus ID / PCI location ID: 132 / 0 Compute Mode: < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) > deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 5.5, CUDA Runtime Version = 5.5, NumDevs = 1, Device0 = Tesla C2070 Result = PASS