Simulation / Modeling / Design

NVIDIA Announces CUDA-X HPC

AI-Generated Summary

  • CUDA-X HPC provides a collection of libraries, tools, compilers and APIs built on CUDA to accelerate high-performance computing applications.
  • The platform includes GPU-accelerated libraries for linear algebra, parallel algorithms, signal and image processing, and multi-GPU scaling such as cuTENSOR, cuFFT, NPP, Thrust and NCCL.
  • NVIDIA Nsight developer tools offer system-wide performance analysis and interactive kernel profiling for CUDA applications.
  • Compilers with support for C/C++, Python and FORTRAN enable developers to build new applications or accelerate existing ones.
  • Over 600 HPC applications across multiple domains use CUDA and CUDA-X HPC, deployable from IoT devices to supercomputers.

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Giving developers the libraries and tools for their next scientific breakthrough

From fluid dynamics and weather simulation, to computational chemistry and bioinformatics, HPC applications span across many domains. Developing these applications requires a robust programming environment with highly optimized domain specific libraries.

Announced today, CUDA-X HPC is a collection of libraries, tools, compilers and APIs that helps developers solve the world’s most challenging problems. Similar to CUDA-X AI announced at GTC Silicon Valley 2019, CUDA-X HPC is built on top of CUDA, NVIDIA’s parallel computing platform and programming model. CUDA-X HPC includes highly tuned kernels essential for high-performance computing (HPC). GPU-accelerated libraries for linear algebra, parallel algorithms, signal and image processing lay the foundation for compute-intensive applications in areas such as computational physics, chemistry, molecular dynamics, and seismic exploration.

The ever expanding list of CUDA-X HPC libraries are regularly extended and fine tuned to take advantage of new algorithmic innovations like mixed precision operations. Linear algebra libraries in the list include industry-best BLAS, Math, and SOLVER libraries that offer extensive functionality and flexibility for programmers. Libraries for optimized tensor primitives (cuTENSOR), fast fourier transforms (cuFFT), performance primitives for image and signal processing (NPP), parallel algorithms and data structures (Thrust), and multi-GPU scaling (NCCL) are some of the other components included in CUDA-X HPC.

Also part of CUDA-X HPC are NVIDIA Nsight developer tools that provide class-leading GPU debugging and profiling. Nsight systems, a system-wide low-overhead performance analysis tool, helps developers identify system wide bottlenecks and Nsight Compute is an interactive kernel profiler for CUDA applications.

Compilers with support for popular languages such as C/C++, Python and FORTRAN make CUDA-X HPC the go to solution for HPC developers building a new application or accelerating existing ones.

Adoption and Availability

CUDA and CUDA-X HPC are used to accelerate over 600 HPC applications across a multitude of domains, on a variety of hardware solutions. Applications built on CUDA-X HPC can be deployed everywhere, including small IoT devices, desktops, data centers, cloud, and supercomputers. It is immediately available to over 1.3 million registered developers on developer.nvidia.com. Developers can also access CUDA-X HPC as containerized software stacks from the NVIDIA NGC software hub.

Learn more about the libraries included in CUDA-X HPC here.

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