Difference between revisions of "Nvidia CUDA Toolkit"

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.

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.

@@ Line 1: / Line 1: @@
-[[Category:Software]]
+[[Category:Software]][[Category:Programming]][[Category:Library]][[Category:Graphics]][[Category:GPU]]
+{|align=right
+  |__TOC__
+  |}
 {|<!--CONFIGURATION: REQUIRED-->
 |{{#vardefine:app|cuda}}
@@ Line 18: / Line 21: @@
 {{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.
+See also: [https://help.rc.ufl.edu/doc/GPU_Access GPU Access]
 <!--Modules-->
-==Required Modules==
+==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.
-=== For single task, non MPI programs===
- module load cuda/10.0.130 intel/2018.1.163
-or
- module load cuda/10.0.130  gcc/7.3.0
-===For MPI programs ===
- module load cuda/10.0.130 intel/2018.1.163 openmpi/4.0.0
 ==System Variables==
@@ Line 47: / Line 40: @@
 ===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.
+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.
+<div class="mw-collapsible mw-collapsed" style="width:70%; padding: 5px; border: 1px solid gray;">
-<source lang=bash>
+''Expand to view example of loading/using cuda.''
+<div class="mw-collapsible-content" style="padding: 5px;">
+<pre>
 $ module spider cuda
 -------------------------------------------------------------
@@ Line 58: / Line 53: @@
       Versions:
-        cuda/9.2.88
          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
 --------------------------------------------------------------------------------------------------------------------
@@ Line 80: / Line 80: @@
 HPC_CUDA_INC=/apps/compilers/cuda/10.0.130/include
 UFRC_FAMILY_CUDA_VERSION=10.0.130
-</source>
+</pre>
+</div>
+</div>
 ===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.
@@ Line 90: / Line 90: @@
 ! SM !! Nvidia Cards
 |-
-| SM_37 || Tesla K80
+| 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.