
NVIDIA HPC Software Development Kit (SDK) includes the proven compilers, libraries and software tools essential to maximizing developer productivity and the performance and portability of HPC applications.
Vendor
NVIDIA
Company Website


NVIDIA HPC Software Development Kit (SDK) includes the proven compilers, libraries, and software tools essential to maximizing developer productivity and the performance and portability of HPC applications. 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 or x86-64 CPUs running Linux, the HPC SDK provides the tools you need to build NVIDIA GPU-accelerated HPC applications.
Features
- CUDA-Accelerated Compilers: Supports C, C++, and Fortran with GPU acceleration for HPC modeling and simulation.
- GPU Math Libraries: Includes cuBLAS, cuSOLVER, cuFFT, and cuSPARSE for optimized performance on common HPC algorithms.
- Optimized Communications Libraries: Enables multi-GPU and scalable systems programming with standards-based libraries.
- Performance Profiling and Debugging Tools: Simplifies porting and optimization of HPC applications.
- Containerization Tools: Facilitates easy deployment on-premises or in the cloud.
- Support for Multiple Architectures: Compatible with NVIDIA GPUs, Arm, and x86-64 CPUs running Linux.
Benefits
- Performance: Delivers breakthrough performance for widely used HPC applications.
- Portability: Ensures applications are fully portable to other compilers and systems.
- Productivity: Maximizes science and engineering throughput and minimizes coding time.
- Scalability: Supports multi-GPU and scalable systems programming.
- Ease of Deployment: Simplifies deployment with containerization tools.