Difference between revisions of "Nvhpc"
(Created page with "Category:SoftwareCategory:Programming Language[[Category:Development]Category:LibraryCategory:MathCategory:NVIDIA {|<!--CONFIGURATION: REQUIRED--> |{{#vard...") |
|||
(5 intermediate revisions by the same user not shown) | |||
Line 1: | Line 1: | ||
− | [[Category:Software]][[Category: | + | [[Category:Software]][[Category:Language]][[Category:Programming]][[Category:Library]][[Category:Math]][[Category:GPU]] |
{|<!--CONFIGURATION: REQUIRED--> | {|<!--CONFIGURATION: REQUIRED--> | ||
− | |{{#vardefine:app| | + | |{{#vardefine:app|nvhpc}} |
− | |{{#vardefine:url| | + | |{{#vardefine:url|https://developer.nvidia.com/hpc-sdk}} |
<!--CONFIGURATION: OPTIONAL (|1}} means it's ON)--> | <!--CONFIGURATION: OPTIONAL (|1}} means it's ON)--> | ||
|{{#vardefine:conf|}} <!--CONFIGURATION--> | |{{#vardefine:conf|}} <!--CONFIGURATION--> | ||
Line 18: | Line 18: | ||
{{App_Description|app={{#var:app}}|url={{#var:url}}|name={{#var:app}}}}|}} | {{App_Description|app={{#var:app}}|url={{#var:url}}|name={{#var:app}}}}|}} | ||
− | + | The NVIDIA HPC SDK C, C++, and Fortran compilers support GPU acceleration of HPC modeling and simulation applications with standard C++ and Fortran, OpenACC® directives, and CUDA®. GPU-accelerated math libraries maximize performance on common HPC algorithms, and optimized communications libraries enable standards-based multi-GPU and scalable systems programming. Performance profiling and debugging tools simplify porting and optimization of HPC applications, and containerization tools enable easy deployment on-premises or in the cloud. With support for NVIDIA GPUs and Arm, OpenPOWER, or x86-64 CPUs running Linux, the HPC SDK provides the tools you need to build NVIDIA GPU-accelerated HPC applications. | |
<!--Modules--> | <!--Modules--> |
Latest revision as of 17:24, 19 August 2022
Description
The NVIDIA HPC SDK C, C++, and Fortran compilers support GPU acceleration of HPC modeling and simulation applications with standard C++ and Fortran, OpenACC® directives, and CUDA®. GPU-accelerated math libraries maximize performance on common HPC algorithms, and optimized communications libraries enable standards-based multi-GPU and scalable systems programming. Performance profiling and debugging tools simplify porting and optimization of HPC applications, and containerization tools enable easy deployment on-premises or in the cloud. With support for NVIDIA GPUs and Arm, OpenPOWER, or x86-64 CPUs running Linux, the HPC SDK provides the tools you need to build NVIDIA GPU-accelerated HPC applications.
Environment Modules
Run module spider nvhpc
to find out what environment modules are available for this application.
System Variables
- HPC_NVHPC_DIR - installation directory