Tips on building GPULib

Several users have pointed out recently that the documentation included with GPULib is sparser than they would like. The docs do require updating, and you should see better installation and use instructions with the next release of the libraries. Until then, here are some tips on how to deal with common issues.

If you're having trouble getting GPULib to build, make sure that the most recent CUDA libraries are installed for your platform. Also, make sure that you have any other software you need; you can't build the IDL bindings without IDL installed on the machine, for example.

If you see errors such as the following during the build:

cc -I/usr/local/rsi/idl/external/include -I/usr/local/cuda/include -O3 -fPIC -I../vectorOp -I../physicsOp -c gpulib.c
gpulib.c:38:24: error: idl_export.h: No such file or directory
gpulib.c:48: error: expected '=', ',', ';', 'asm' or '__attribute__' before 'get_IDL_long'
In file included from gpulib.c:163:
../vectorOp/gpuVectorOpFuncList.h:38: error: expected '=', ',', ';', 'asm' or '__attribute__' before 'IDL_gpuSqrtF'
../vectorOp/gpuVectorOpFuncList.h:39: error: expected '=', ',', ';', 'asm' or '__attribute__' before 'IDL_gpuExpF'

you probably need to change your configure line to help GPULib figure out where IDL is. A configure line such as

./configure --disable-MATLAB --with-idl-dir=/path/to/idl

should fix this issue and allow the build to continue.

If you encounter any other issues, feel free to describe them in the comments or send email to support@txcorp.com.

Example MATLAB code in GPULib

I recently had a question from a user looking for information on how to use GPULib with MATLAB; you can find examples of how to use GPULib in the

gpulib-0.3p7/MATLAB/ode_cell/

directory of the current distribution.

We're working on refining the MATLAB interface to the library, and hopefully we'll be able to share that work with you soon. In the meantime, if you have suggestions or comments about using GPULib with MATLAB, please let us know!

GPULib 0.3p7 released

Development continues on GPULib -- the team has made a new release; 0.3p7 can be downloaded at

http://www.txcorp.com/technologies/GPULib/

New version 0.3p6 available

Tech-X has just released a new version of GPULib. It is available from

http://www.txcorp.com/technologies/GPULib/download.php

Questions, comments, bug reports, and feature requests are welcome.

Nvidia's David Kirk on CUDA, CPUs and GPUs

bit-tech has a quite interesting interview up with Nvidia's Chief Scientist David Kirk, where he discusses the future of GPU computing.

http://www.bit-tech.net/hardware/2008/04/30/david-kirk-interview/1

Intel to build sGPU supercomputer: Nvidia Tesla cards to debut in Bull system

http://www.tgdaily.com/content/view/37070/135/

The original Bull NovaScale supercomputer setup was based on 1068 nodes, which will result in a total of 8544 processing cores for a peak floating point performance of 192 TFlops. Apparently the design was recently upgraded with 48 nodes of Nvidia Tesla S900 GPGPU cards with 96 (GT200) GPUs. The expected performance is now about 300 TFlops. In comparison, BlueGene/L, currently the world's most powerful supercomputer, peaks at 596 TFlops an uses 212,992 processing cores.

New version 0.3p1 available

A new version of GPULib (0.3p1) is available at

http://www.txcorp.com/technologies/GPULib/download.php


This new version contains a variety of bug fixes and minor updates. Please contact us if you run into any issues or have feature requests.