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cuda

About

CUDA is a parallel computing platform and programming model that makes using a GPU for general purpose computing simple and elegant. The developer still programs in the familiar C, C++, Fortran, or an ever expanding list of supported languages, and incorporates extensions of these languages in the form of a few basic keywords.

Versions and Availability

Softenv Keys for cuda on philip
Machine Version Softenv Key
philip 4.0.17 +cuda-4.0.17
philip 4.2.9 +cuda-4.2.9
▶ Softenv FAQ?

The information here is applicable to LSU HPC and LONI systems.

Shells

A user may choose between using /bin/bash and /bin/tcsh. Details about each shell follows.

/bin/bash

System resource file: /etc/profile

When one access the shell, the following user files are read in if they exist (in order):

  1. ~/.bash_profile (anything sent to STDOUT or STDERR will cause things like rsync to break)
  2. ~/.bashrc (interactive login only)
  3. ~/.profile

When a user logs out of an interactive session, the file ~/.bash_logout is executed if it exists.

The default value of the environmental variable, PATH, is set automatically using SoftEnv. See below for more information.

/bin/tcsh

The file ~/.cshrc is used to customize the user's environment if his login shell is /bin/tcsh.

Softenv

SoftEnv is a utility that is supposed to help users manage complex user environments with potentially conflicting application versions and libraries.

System Default Path

When a user logs in, the system /etc/profile or /etc/csh.cshrc (depending on login shell, and mirrored from csm:/cfmroot/etc/profile) calls /usr/local/packages/softenv-1.6.2/bin/use.softenv.sh to set up the default path via the SoftEnv database.

SoftEnv looks for a user's ~/.soft file and updates the variables and paths accordingly.

Viewing Available Packages

The command softenv will provide a list of available packages. The listing will look something like:

$ softenv
These are the macros available:
*   @default
These are the keywords explicitly available:
+amber-8                       Applications: 'Amber', version: 8 Amber is a
+apache-ant-1.6.5              Ant, Java based XML make system version: 1.6.
+charm-5.9                     Applications: 'Charm++', version: 5.9 Charm++
+default                       this is the default environment...nukes /etc/
+essl-4.2                      Libraries: 'ESSL', version: 4.2 ESSL is a sta
+gaussian-03                   Applications: 'Gaussian', version: 03 Gaussia
... some stuff deleted ...
Managing SoftEnv

The file ~/.soft in the user's home directory is where the different packages are managed. Add the +keyword into your .soft file. For instance, ff one wants to add the Amber Molecular Dynamics package into their environment, the end of the .soft file should look like this:

+amber-8

@default

To update the environment after modifying this file, one simply uses the resoft command:

% resoft

The command soft can be used to manipulate the environment from the command line. It takes the form:

$ soft add/delete +keyword

Using this method of adding or removing keywords requires the user to pay attention to possible order dependencies. That is, best results require the user to remove keywords in the reverse order in which they were added. It is handy to test out individual keys, but can lead to trouble if changing multiple keys. Changing the .soft file and issuing the resoft is the recommended way of dealing with multiple changes.

Usage

How you program for GPU process with CUDA depends on the language, choice of compilers, and toolset.

▶ Open Example?

Standard C:

void saxpy( int n, float a,
            float *x, float *y )
{
   for ( int i = 0; i < n; ++i )
      y[i] = a * x[i] + y[i];
}

int N = 1 << 20;

saxpy( N, 2.0, x, y );

C with CUDA Extensions:

__global__
void saxpy( int n, float a,
float *x, float *y )
{
   int i = blockIdx.x*blockDim.x + threadIdx.x;
   if ( i < n ) y[i] = a * x[i] + y[i];
}

int N = 1 << 20;
cudaMemcpy(x, d_x, N, cudaMemcpyHostToDevice);
cudaMemcpy(y, d_y, N, cudaMemcpyHostToDevice);

saxpy<<<4096,256>>>(N, 2.0, x, y);

cudaMemcpy(d_y, y, N, cudaMemcpyDeviceToHost);

Resources

Last modified: November 11 2014 16:38:43.