Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • RunPod Reviews & Ratings
    180 Ratings
    Company Website
  • LeanData Reviews & Ratings
    1,094 Ratings
    Company Website
  • DXcharts Reviews & Ratings
    28 Ratings
    Company Website
  • Reflectiz Reviews & Ratings
    15 Ratings
    Company Website
  • Interfacing Enterprise Process Center (EPC) Reviews & Ratings
    63 Ratings
    Company Website
  • JetBrains Junie Reviews & Ratings
    2 Ratings
    Company Website
  • LM-Kit.NET Reviews & Ratings
    22 Ratings
    Company Website
  • Thinfinity Workspace Reviews & Ratings
    14 Ratings
    Company Website
  • Google Cloud Run Reviews & Ratings
    286 Ratings
    Company Website
  • QuickApps Reviews & Ratings
    Company Website

What is NVIDIA HPC SDK?

The NVIDIA HPC Software Development Kit (SDK) provides a thorough collection of dependable compilers, libraries, and software tools that are essential for improving both developer productivity and the performance and flexibility of HPC applications. Within this SDK are compilers for C, C++, and Fortran that enable GPU acceleration for modeling and simulation tasks in HPC by utilizing standard C++ and Fortran, alongside OpenACC® directives and CUDA®. Moreover, GPU-accelerated mathematical libraries enhance the effectiveness of commonly used HPC algorithms, while optimized communication libraries facilitate standards-based multi-GPU setups and scalable systems programming. Performance profiling and debugging tools are integrated to simplify the transition and optimization of HPC applications, and containerization tools make deployment seamless, whether in on-premises settings or cloud environments. Additionally, the HPC SDK is compatible with NVIDIA GPUs and diverse CPU architectures such as Arm, OpenPOWER, or x86-64 operating on Linux, thus equipping developers with comprehensive resources to efficiently develop high-performance GPU-accelerated HPC applications. In conclusion, this powerful toolkit is vital for anyone striving to advance the capabilities of high-performance computing, offering both versatility and depth for a wide range of applications.

What is Amazon EC2 P4 Instances?

Amazon's EC2 P4d instances are designed to deliver outstanding performance for machine learning training and high-performance computing applications within the cloud. Featuring NVIDIA A100 Tensor Core GPUs, these instances are capable of achieving impressive throughput while offering low-latency networking that supports a remarkable 400 Gbps instance networking speed. P4d instances serve as a budget-friendly option, allowing businesses to realize savings of up to 60% during the training of machine learning models and providing an average performance boost of 2.5 times for deep learning tasks when compared to previous P3 and P3dn versions. They are often utilized in large configurations known as Amazon EC2 UltraClusters, which effectively combine high-performance computing, networking, and storage capabilities. This architecture enables users to scale their operations from just a few to thousands of NVIDIA A100 GPUs, tailored to their particular project needs. A diverse group of users, such as researchers, data scientists, and software developers, can take advantage of P4d instances for a variety of machine learning tasks including natural language processing, object detection and classification, as well as recommendation systems. Additionally, these instances are well-suited for high-performance computing endeavors like drug discovery and intricate data analyses. The blend of remarkable performance and the ability to scale effectively makes P4d instances an exceptional option for addressing a wide range of computational challenges, ensuring that users can meet their evolving needs efficiently.

Media

Media

Integrations Supported

AWS Batch
AWS Deep Learning AMIs
AWS Deep Learning Containers
AWS Marketplace
AWS Neuron
Amazon EC2
Amazon EC2 Capacity Blocks for ML
Amazon EC2 G5 Instances
Amazon EC2 P5 Instances
Amazon EC2 Trn1 Instances
Amazon EC2 UltraClusters
Amazon EKS
Amazon Elastic Container Service (Amazon ECS)
Amazon SageMaker
Amazon Web Services (AWS)
Azure Marketplace
Domino Enterprise MLOps Platform
MXNet
PyTorch
TensorFlow

Integrations Supported

AWS Batch
AWS Deep Learning AMIs
AWS Deep Learning Containers
AWS Marketplace
AWS Neuron
Amazon EC2
Amazon EC2 Capacity Blocks for ML
Amazon EC2 G5 Instances
Amazon EC2 P5 Instances
Amazon EC2 Trn1 Instances
Amazon EC2 UltraClusters
Amazon EKS
Amazon Elastic Container Service (Amazon ECS)
Amazon SageMaker
Amazon Web Services (AWS)
Azure Marketplace
Domino Enterprise MLOps Platform
MXNet
PyTorch
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$11.57 per hour
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

developer.nvidia.com/hpc-sdk

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/ec2/instance-types/p4/

Categories and Features

HPC

Categories and Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

HPC

Popular Alternatives

Popular Alternatives