Difference between revisions of "Nvidia CUDA Toolkit"

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(updated the currently available cuda versions on hipergator. removed deprecated version not available anymore.)
 
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[[Category:Software]]
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[[Category:Software]][[Category:Programming]][[Category:Library]][[Category:Graphics]][[Category:GPU]]
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{|align=right
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  |__TOC__
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  |}
 
{|<!--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|1}}            <!--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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{{App_Description|app={{#var:app}}|url={{#var:url}}|name={{#var:app}}}}|}}
 
{{App_Description|app={{#var:app}}|url={{#var:url}}|name={{#var:app}}}}|}}
 
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.
 +
 +
See also: [https://help.rc.ufl.edu/doc/GPU_Access GPU Access]
 
<!--Modules-->
 
<!--Modules-->
==Required Modules==
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==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. The cuda versions below are currently supported on hipergator.
{{#if: {{#var: pbs}}|==PBS Script Examples==
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<div class="mw-collapsible mw-collapsed" style="width:70%; padding: 5px; border: 1px solid gray;">
See the [[{{PAGENAME}}_PBS]] page for {{#var: app}} PBS script examples.
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''Expand to view example of loading/using cuda.''
|}}
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<div class="mw-collapsible-content" style="padding: 5px;">
<!--Policy-->
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<pre>
{{#if: {{#var: policy}}|==Usage Policy==
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$ module spider cuda
WRITE USAGE POLICY HERE (Licensing, usage, access).
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-------------------------------------------------------------
|}}
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cuda:
<!--Performance-->
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-------------------------------------------------------------
{{#if: {{#var: testing}}|==Performance==
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    Description:
WRITE_PERFORMANCE_TESTING_RESULTS_HERE
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      NVIDIA CUDA Toolkit
|}}
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 +
    Versions:
 +
        cuda/10.0.130
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        cuda/11.0.207
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        cuda/11.1.0
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        cuda/11.4.3
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        cuda/11.6
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        cuda/12.2.0
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        cuda/12.2.2
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        cuda/12.4.1
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 +
--------------------------------------------------------------------------------------------------------------------
 +
  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
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 +
$ which nvcc
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/apps/compilers/cuda/10.0.130/bin/nvcc
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 +
$ printenv | grep CUDA
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HPC_CUDA_LIB=/apps/compilers/cuda/10.0.130/lib64
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HPC_CUDA_DIR=/apps/compilers/cuda/10.0.130
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HPC_CUDA_BIN=/apps/compilers/cuda/10.0.130/bin
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HPC_CUDA_INC=/apps/compilers/cuda/10.0.130/include
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UFRC_FAMILY_CUDA_VERSION=10.0.130
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</pre>
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</div>
 +
</div>
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===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.  
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 +
{| class="wikitable"
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|-
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! SM !! Nvidia Cards
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|-
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| SM_37 || Tesla K80 (No longer available)
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|-
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| SM_61 || GeForce GTX 1080Ti
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|-
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| SM_75|| GeForce RTX 2080Ti
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|-
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| SM_80 || DGX A100
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|}
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 +
==Sample GPU Batch Job Scripts==
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 +
 
 +
See the [[Example_SLURM-GPU-Job-Scripts]] page for an example.
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 +
<!--|}}-->
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<!--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__
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-->

Latest revision as of 13:22, 31 May 2024

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.

See also: GPU Access

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. The cuda versions below are currently supported on hipergator.

Expand to view example of loading/using cuda.

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

     Versions:
        cuda/10.0.130
        cuda/11.0.207
        cuda/11.1.0
        cuda/11.4.3
        cuda/11.6
        cuda/12.2.0
        cuda/12.2.2
        cuda/12.4.1

--------------------------------------------------------------------------------------------------------------------
  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

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