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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

The convergence of high-performance computing (HPC) and machine learning is placing unprecedented requirements on storage solutions, as the input/output demands of these two distinct workloads diverge significantly. This shift is occurring at this very moment, with a recent analysis from the independent firm Intersect360 revealing that a striking 63% of current HPC users are actively implementing machine learning applications. Furthermore, Hyperion Research projects that, if trends continue, public sector organizations and enterprises will see HPC storage expenditures increase at a rate 57% faster than HPC compute investments over the next three years. Reflecting on this, Seymour Cray famously stated, "Anyone can build a fast CPU; the trick is to build a fast system." In the realm of HPC and AI, while creating fast file storage may seem straightforward, the true challenge lies in developing a storage system that is not only quick but also economically viable and capable of scaling effectively. We accomplish this by integrating top-tier parallel file systems into HPE's parallel storage solutions, ensuring that cost efficiency is a fundamental aspect of our approach. This strategy not only meets the current demands of users but also positions us well for future growth.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AWS Batch Yes 
AWS EC2 Trn3 Instances Yes 
AWS Elastic Fabric Adapter (EFA) Yes 
AWS HPC Yes 
AWS Lambda Yes 
AWS Parallel Computing Service Yes 
Amazon API Gateway Yes 
Amazon Web Services (AWS) Yes 
Automai Robotic Process Automation No 
Check Point IPS No 
Check Point Infinity No 
GitHub Yes 
Python Yes 
SQLXPress No 
Slurm Yes 
XYGATE Identity Connector No 
XYGATE SecurityOne No 

Integrations

AWS Batch No 
AWS EC2 Trn3 Instances No 
AWS Elastic Fabric Adapter (EFA) No 
AWS HPC No 
AWS Lambda No 
AWS Parallel Computing Service No 
Amazon API Gateway No 
Amazon Web Services (AWS) No 
Automai Robotic Process Automation Yes 
Check Point IPS Yes 
Check Point Infinity Yes 
GitHub No 
Python No 
SQLXPress Yes 
Slurm No 
XYGATE Identity Connector Yes 
XYGATE SecurityOne Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/hpc/parallelcluster/

Vendor Details

Company Name

Hewlett Packard

Founded

2015

Country

United States

Website

www.hpe.com/us/en/solutions/hpc-high-performance-computing/storage.html

Product Features

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