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Description
AWS ParallelCluster is a free, open-source tool designed for efficient management and deployment of High-Performance Computing (HPC) clusters within the AWS environment. It streamlines the configuration of essential components such as compute nodes, shared filesystems, and job schedulers, while accommodating various instance types and job submission queues. Users have the flexibility to engage with ParallelCluster using a graphical user interface, command-line interface, or API, which allows for customizable cluster setups and oversight. The tool also works seamlessly with job schedulers like AWS Batch and Slurm, making it easier to transition existing HPC workloads to the cloud with minimal adjustments. Users incur no additional costs for the tool itself, only paying for the AWS resources their applications utilize. With AWS ParallelCluster, users can effectively manage their computing needs through a straightforward text file that allows for the modeling, provisioning, and dynamic scaling of necessary resources in a secure and automated fashion. This ease of use significantly enhances productivity and optimizes resource allocation for various computational tasks.
Description
Amazon EC2 P4d instances are designed for optimal performance in machine learning training and high-performance computing (HPC) applications within the cloud environment. Equipped with NVIDIA A100 Tensor Core GPUs, these instances provide exceptional throughput and low-latency networking capabilities, boasting 400 Gbps instance networking. P4d instances are remarkably cost-effective, offering up to a 60% reduction in expenses for training machine learning models, while also delivering an impressive 2.5 times better performance for deep learning tasks compared to the older P3 and P3dn models. They are deployed within expansive clusters known as Amazon EC2 UltraClusters, which allow for the seamless integration of high-performance computing, networking, and storage resources. This flexibility enables users to scale their operations from a handful to thousands of NVIDIA A100 GPUs depending on their specific project requirements. Researchers, data scientists, and developers can leverage P4d instances to train machine learning models for diverse applications, including natural language processing, object detection and classification, and recommendation systems, in addition to executing HPC tasks such as pharmaceutical discovery and other complex computations. These capabilities collectively empower teams to innovate and accelerate their projects with greater efficiency and effectiveness.
API Access
Has API
API Access
Has API
Integrations
AWS Batch
Amazon Web Services (AWS)
AWS Deep Learning AMIs
AWS Elastic Fabric Adapter (EFA)
AWS Lambda
AWS Neuron
AWS Nitro System
AWS Trainium
Amazon EC2
Amazon EC2 Capacity Blocks for ML
Integrations
AWS Batch
Amazon Web Services (AWS)
AWS Deep Learning AMIs
AWS Elastic Fabric Adapter (EFA)
AWS Lambda
AWS Neuron
AWS Nitro System
AWS Trainium
Amazon EC2
Amazon EC2 Capacity Blocks for ML
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$11.57 per hour
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/hpc/parallelcluster/
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/ec2/instance-types/p4/
Product Features
Product Features
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
