NVIDIA HPC SDK

NVIDIA HPC SDK

The NVIDIA HPC Software Development Kit (SDK) equips developers with essential compilers, libraries, and tools to enhance productivity and portability in high-performance computing. It supports GPU acceleration for C, C++, and Fortran applications using OpenACC and CUDA, optimizing performance with specialized math and communication libraries, alongside profiling and debugging tools for efficient application deployment.

Top NVIDIA HPC SDK Alternatives

Ad
StackScan

StackScan

Use StackScan to discover the technologies powering websites, with insights across 50,000+ technology stacks and 105 million domains.

StackScan Pte Ltd
1

NVIDIA Modulus

NVIDIA Modulus is a powerful neural network framework designed to integrate physics with data to create high-fidelity surrogate models.

By: NVIDIA From United States
2

HPE Performance Cluster Manager

HPE Performance Cluster Manager (HPCM) offers an integrated management solution tailored for Linux-based HPC clusters.

By: Hewlett Packard Enterprise From United States
3

Intel oneAPI HPC Toolkit

The IntelĀ® oneAPI HPC Toolkit empowers developers to create, analyze, and optimize high-performance computing applications essential for AI, machine learning, and deep learning.

By: Intel From United States
4

Ansys HPC

Ansys HPC leverages the power of multicore computing to enable faster, more intricate simulations, enhancing accuracy and complexity.

By: Ansys From United States
5

AWS Parallel Computing Service

AWS Parallel Computing Service (AWS PCS) streamlines the execution and scaling of high-performance computing workloads, empowering users to construct elastic environments with integrated compute, storage, and networking tools.

By: Amazon From United States
6

Lustre

Lustre is an open-source, parallel file system designed for high-performance computing environments, capable of scaling to thousands of clients and petabytes of storage.

By: OpenSFS and EOFS From United States
7

AWS HPC

With Elastic Fabric Adapter for low-latency networking and on-demand resource access, teams can innovate rapidly...

By: Amazon From United States
8

Moab HPC Suite

Utilizing a patented intelligence engine, it employs multi-dimensional policies to optimize workload scheduling and execution...

By: Adaptive Computing From United States
9

Azure HPC

It combines powerful CPU, GPU, and FPGA capabilities, enabling users to tackle complex challenges and...

By: Microsoft From United States
10

Fuzzball

Its user-friendly, web-based interface allows researchers to design and automate complex workflows seamlessly...

By: CIQ From United States
11

UberCloud

The platform integrates seamlessly with leading tools like ANSYS and COMSOL, optimizing high-performance computing environments...

By: Simr (formerly UberCloud) From United States
12

Covalent

With Python-based access to diverse hardware resources, it automates containerization, provisioning, and scheduling, ensuring efficient...

By: Agnostiq From Canada
13

Arm Allinea Studio

It includes specialized compilers, libraries, and advanced debugging and optimization tools, alongside the Arm Performance...

By: Arm From United Kingdom
14

Nimbix Supercomputing Suite

With features like bare metal-as-a-service and the Federated Supercomputing model, it ensures seamless scalability, agility...

By: Atos From France
15

Arm MAP

It operates seamlessly on multiple architectures, delivering critical insights into bottlenecks and memory usage with...

By: Arm From United Kingdom

Top NVIDIA HPC SDK Features

  • GPU-accelerated Fortran support
  • C++17 parallel algorithms
  • OpenACC directive-based programming
  • Tensor Core optimization
  • Multi-GPU communication primitives
  • CUDA-aware MPI library
  • Performance profiling tools
  • Easy deployment via containers
  • Highly portable across architectures
  • Integrated suite for HPC
  • Support for Arm and x86-64
  • Optimized math libraries
  • Simplified debugging processes
  • Industry-standard communication libraries
  • Seamless integration with existing code
  • Proven performance for top applications
  • Support for CUDA Unified Memory
  • Efficient memory allocation routines
  • Access to technical experts
  • Enhanced developer productivity.