Difference between revisions of "Nvidia CUDA Toolkit"

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(Created page with "Category:Software {|<!--CONFIGURATION: REQUIRED--> |{{#vardefine:app|cuda}} |{{#vardefine:url|http://www.nvidia.com/object/cuda_home_new.html}} <!--CONFIGURATION: OPTIONAL...")
 
 
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[[Category:Software]]
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[[Category:Software]][[Category:Programming]][[Category:Library]][[Category:Graphics]]
 
{|<!--CONFIGURATION: REQUIRED-->
 
{|<!--CONFIGURATION: REQUIRED-->
 
|{{#vardefine:app|cuda}}
 
|{{#vardefine:app|cuda}}
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<!--CONFIGURATION: OPTIONAL (|1}} means it's ON)-->
 
<!--CONFIGURATION: OPTIONAL (|1}} means it's ON)-->
 
|{{#vardefine:conf|}}          <!--CONFIGURATION-->
 
|{{#vardefine:conf|}}          <!--CONFIGURATION-->
|{{#vardefine:exe|}}            <!--ADDITIONAL INFO-->
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|{{#vardefine:exe|1}}            <!--ADDITIONAL INFO-->
|{{#vardefine:pbs|}}            <!--PBS SCRIPTS-->
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|{{#vardefine:pbs|1}}            <!--JOB SCRIPTS-->
|{{#vardefine:policy|}}        <!--POLICY-->
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|{{#vardefine:policy|1}}        <!--POLICY-->
|{{#vardefine:testing|}}       <!--PROFILING-->
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|{{#vardefine:testing|}}       <!--PROFILING-->
 
|{{#vardefine:faq|}}            <!--FAQ-->
 
|{{#vardefine:faq|}}            <!--FAQ-->
 
|{{#vardefine:citation|}}      <!--CITATION-->
 
|{{#vardefine:citation|}}      <!--CITATION-->
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CUDA™ is a parallel computing platform and programming model invented by NVIDIA. It enables dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU). With millions of CUDA-enabled GPUs sold to date, software developers, scientists and researchers are finding broad-ranging uses for GPU computing with CUDA.
 
CUDA™ is a parallel computing platform and programming model invented by NVIDIA. It enables dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU). With millions of CUDA-enabled GPUs sold to date, software developers, scientists and researchers are finding broad-ranging uses for GPU computing with CUDA.
 
<!--Modules-->
 
<!--Modules-->
==Required Modules==
+
==Environment Modules==
cuda
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Use the 'module avail' command after loading a cuda environment module to see the available module trees or see which compiler and openmpi modules require the cuda module to be loaded.
 +
 
 
==System Variables==
 
==System Variables==
* HPC_{{#uppercase:{{#var:app}}}}_DIR
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* HPC_{{uc:{{#var:app}}}}_DIR
* HPC_{{#uppercase:{{#var:app}}}}_BIN
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* HPC_{{uc:{{#var:app}}}}_BIN
* HPC_{{#uppercase:{{#var:app}}}}_INC
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* HPC_{{uc:{{#var:app}}}}_INC
* HPC_{{#uppercase:{{#var:app}}}}_LIB
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* HPC_{{uc:{{#var:app}}}}_LIB
 
<!--Configuration-->
 
<!--Configuration-->
 
{{#if: {{#var: conf}}|==Configuration==
 
{{#if: {{#var: conf}}|==Configuration==
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|}}
 
|}}
 
<!--Run-->
 
<!--Run-->
{{#if: {{#var: exe}}|==Additional Information==
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==Program Development==
WRITE_ADDITIONAL_INSTRUCTIONS_ON_RUNNING_THE_SOFTWARE_IF_NECESSARY
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|}}
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===Environment===
<!--PBS scripts-->
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For CUDA development please load the "cuda" module.  Doing so will ensure that your environment is set up correctly for the use of the CUDA compiler, header files, and libraries. Currently cuda/9.2.88 and cuda/10.0.130 are the only versions supported on hipergator.
{{#if: {{#var: pbs}}|==PBS Script Examples==
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See the [[{{PAGENAME}}_PBS]] page for {{#var: app}} PBS script examples.
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<pre>
|}}
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$ module spider cuda
<!--Policy-->
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-------------------------------------------------------------
{{#if: {{#var: policy}}|==Usage Policy==
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cuda:
WRITE USAGE POLICY HERE (Licensing, usage, access).
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-------------------------------------------------------------
|}}
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    Description:
<!--Performance-->
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      NVIDIA CUDA Toolkit
{{#if: {{#var: testing}}|==Performance==
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WRITE_PERFORMANCE_TESTING_RESULTS_HERE
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    Versions:
|}}
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        cuda/9.2.88
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        cuda/10.0.130
 +
       
 +
 
 +
--------------------------------------------------------------------------------------------------------------------
 +
  For detailed information about a specific "cuda" module (including how to load the modules) use the module full name.
 +
  For example:
 +
 
 +
    $ module spider cuda/10.0.130
 +
--------------------------------------------------------------------------------------------------------------------
 +
 
 +
$ module load cuda/10.0.130
 +
 
 +
$ which nvcc
 +
/apps/compilers/cuda/10.0.130/bin/nvcc
 +
 
 +
$ printenv | grep CUDA
 +
HPC_CUDA_LIB=/apps/compilers/cuda/10.0.130/lib64
 +
HPC_CUDA_DIR=/apps/compilers/cuda/10.0.130
 +
HPC_CUDA_BIN=/apps/compilers/cuda/10.0.130/bin
 +
HPC_CUDA_INC=/apps/compilers/cuda/10.0.130/include
 +
UFRC_FAMILY_CUDA_VERSION=10.0.130
 +
</pre>
 +
 
 +
 
 +
===Selecting CUDA Arch Flags===
 +
When compiling with NVCC, you need to specify the Nvidia architecture that the CUDA files will be compiled for. Please refer to [https://docs.nvidia.com/cuda/cuda-compiler-driver-nvcc/index.html#gpu-feature-list GPU Feature List] for CUDA naming scheme sm_xy where x denotes the GPU generation and y denotes the version. The table below lists the SM flags for the three types of GPUs on HiPerGator.  
 +
 
 +
{| class="wikitable"
 +
|-
 +
! SM !! Nvidia Cards
 +
|-
 +
| SM_37 || Tesla K80 (No longer available)
 +
|-
 +
| SM_61 || GeForce GTX 1080Ti
 +
|-
 +
| SM_75|| GeForce RTX 2080Ti
 +
|-
 +
| SM_80 || DGX A100
 +
|}
 +
 
 +
==Sample GPU Batch Job Scripts==
 +
 
 +
===SLURM Job Scripts===
 +
 
 +
See the [[Example_SLURM-GPU-Job-Scripts]] page for an example.
 +
 
 +
<!--|}}-->
 +
 
 
<!--Faq-->
 
<!--Faq-->
 
{{#if: {{#var: faq}}|==FAQ==
 
{{#if: {{#var: faq}}|==FAQ==
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{{#if: {{#var: installation}}|==Installation==
 
{{#if: {{#var: installation}}|==Installation==
 
See the [[{{PAGENAME}}_Install]] page for {{#var: app}} installation notes.|}}
 
See the [[{{PAGENAME}}_Install]] page for {{#var: app}} installation notes.|}}
<!--Turn the Table of Contents and Edit paragraph links ON/OFF-->
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<!--Turn the Table of Contents and Edit paragraph links ON/OFF
 
__NOTOC____NOEDITSECTION__
 
__NOTOC____NOEDITSECTION__
 +
-->

Latest revision as of 14:17, 15 August 2022

Description

cuda website  
CUDA™ is a parallel computing platform and programming model invented by NVIDIA. It enables dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU). With millions of CUDA-enabled GPUs sold to date, software developers, scientists and researchers are finding broad-ranging uses for GPU computing with CUDA.

Environment Modules

Use the 'module avail' command after loading a cuda environment module to see the available module trees or see which compiler and openmpi modules require the cuda module to be loaded.

System Variables

  • HPC_CUDA_DIR
  • HPC_CUDA_BIN
  • HPC_CUDA_INC
  • HPC_CUDA_LIB

Program Development

Environment

For CUDA development please load the "cuda" module. Doing so will ensure that your environment is set up correctly for the use of the CUDA compiler, header files, and libraries. Currently cuda/9.2.88 and cuda/10.0.130 are the only versions supported on hipergator.

$ module spider cuda
-------------------------------------------------------------
cuda:
-------------------------------------------------------------
    Description:
      NVIDIA CUDA Toolkit

     Versions:
        cuda/9.2.88
        cuda/10.0.130
        

--------------------------------------------------------------------------------------------------------------------
  For detailed information about a specific "cuda" module (including how to load the modules) use the module full name.
  For example:

     $ module spider cuda/10.0.130
--------------------------------------------------------------------------------------------------------------------

$ module load cuda/10.0.130

$ which nvcc
/apps/compilers/cuda/10.0.130/bin/nvcc

$ printenv | grep CUDA
HPC_CUDA_LIB=/apps/compilers/cuda/10.0.130/lib64
HPC_CUDA_DIR=/apps/compilers/cuda/10.0.130
HPC_CUDA_BIN=/apps/compilers/cuda/10.0.130/bin
HPC_CUDA_INC=/apps/compilers/cuda/10.0.130/include
UFRC_FAMILY_CUDA_VERSION=10.0.130


Selecting CUDA Arch Flags

When compiling with NVCC, you need to specify the Nvidia architecture that the CUDA files will be compiled for. Please refer to GPU Feature List for CUDA naming scheme sm_xy where x denotes the GPU generation and y denotes the version. The table below lists the SM flags for the three types of GPUs on HiPerGator.

SM Nvidia Cards
SM_37 Tesla K80 (No longer available)
SM_61 GeForce GTX 1080Ti
SM_75 GeForce RTX 2080Ti
SM_80 DGX A100

Sample GPU Batch Job Scripts

SLURM Job Scripts

See the Example_SLURM-GPU-Job-Scripts page for an example.