Golden Energy Computing Organization
Tesla Node

The Golden Energy Computing Organization (GECO) invites CSM students to apply for an account on the Mines Nvidia Tesla S1070 system CUDA1.MINES.EDU

Nvidia Tesla S1070 system CUDA1.MINES.EDU

Special purpose computing accelerators, such as graphic processing units, (GPU) have become an important platform for parallel high performance scientific computing. GECO recently took delivery of and installed a Nvidia Tesla S1070 system. This 1U rack mountable system contains 4 of the Nvidia Quadro FX 5600 GPU cards and has a peak computing performance of 4 trillion floating point operations per second, or 4 Teraflops. This new Tesla system is front-ended by one of the RA nodes. Each of the 4 graphics processing units (GPU) on the Tesla has 240 processing cores and 4 Gbytes of memory for a total of 960 cores and 16 Gbytes. The individual GPUs are connected to the front-end node via a PCI connector.

Doctor Dobbs Tutorial
size: 4.3 MB
Cuda Programming Guide
size: 1.2 MB
Tech Fee Proposal
size: 700 KB
Cuda Documentation that "ships" with the compiler
size: 7 MB
Portland Group compiler information
External Link
Examples from software development kit
size: 56 MB
Examples from Aug 24 workshop
size: 4 KB
Thomas's first set of slides from Aug 24 workshop
size: 188 KB
Thomas's second set of slides from Aug 24 workshop
size: 188 KB
Tim's slides from Aug 24 workshop
size: 188 KB
Celebration of Mines poster
size: 2.5 MB
Oredigger Article about cuda1
External Link
Request an account on The GECO tesla node cuda1.mines.edu

Basic Usage Instructions

The GECO Tesla node is connected to one of the RA nodes via two PCI interface cables. In particular, it is connected node cuda1. To access the Tesla you must first ssh to ra.mines.edu then ssh to cuda1. For example:

[victoire:~] floydl% ssh ra.mines.edu
Last login: Tue Jul 14 10:07:12 2009 from victoire.mines.edu
Rocks Frontend Node - ra Cluster
...
...
...
[floydl@ra ~]$ ssh cuda1
Last login: Tue Jul 14 10:06:34 2009 from ra.mines.edu
[floydl@cuda1 ~]$ 

You will want to add the following lines to you .bash_profile file on cuda1 to enable you to access the cuda compilers.

export LD_LIBRARY_PATH=/usr/local/cuda/lib:/usr/local/cuda/cudaprof/bin:$LD_LIBRARY_PATH
export PATH=$PATH:/usr/local/cuda/bin
export PATH=$PATH:$HOME/cuda/bin/linux/release
export MANPATH=$MANPATH:/usr/local/cuda/man

Next copy the example programs to your home directory.

[floydl@cuda1 ~]$ cp -r /usr/local/cuda_sdk cuda

Finally, log out and log back in to set your path correctly. After you log back in go to your cuda directory and type make. This will build the cuda example programs. The examples will be in the $HOME/cuda/bin/linux/release directory.

[floydl@cuda1 ~]$ cd cuda
[floydl@cuda1 cuda]$ ls
bin  common  doc  lib  Makefile  projects  releaseNotesData  ReleaseNotes.html  tools
[floydl@cuda1 cuda]$ make
make[1]: Entering directory `/home/floydl/cuda/common'
a - obj/release/bank_checker.cpp.o
a - obj/release/cmd_arg_reader.cpp.o
a - obj/release/cutil.cpp.o
a - obj/release/stopwatch.cpp.o
a - obj/release/stopwatch_linux.cpp.o
...
...
[floydl@cuda1 ~]$ cd $HOME/cuda/bin/linux/release
[floydl@cuda1 release]$ ls
alignedTypes          dwtHaar1D           nbody                   simpleStreams
asyncAPI              dxtc                oceanFFT                simpleTemplates
bandwidthTest         eigenvalues         particles               simpleTexture
...
...
deviceQueryDrv        MonteCarloMultiGPU  simpleMultiGPU          volumeRender
[floydl@cuda1 release]$ 

The Tesla board is designed primarily for computation and does not support video out. It you try to run any of the examples that produce video out you will get an error.

For questions please contact Dr. Timothy Kaiser at tkaiser@mines.edu