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Average Ratings 0 Ratings
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
In recent years, high-performance computing has become a more accessible resource for a greater number of researchers within the scientific community than ever before. The combination of quality open-source software and affordable hardware has significantly contributed to the widespread adoption of Beowulf class clusters and clusters of workstations. Among various parallel computational approaches, message-passing has emerged as a particularly effective model. This paradigm is particularly well-suited for distributed memory architectures and is extensively utilized in today's most demanding scientific and engineering applications related to modeling, simulation, design, and signal processing. Nonetheless, the landscape of portable message-passing parallel programming was once fraught with challenges due to the numerous incompatible options developers faced. Thankfully, this situation has dramatically improved since the MPI Forum introduced its standard specification, which has streamlined the process for developers. As a result, researchers can now focus more on their scientific inquiries rather than grappling with programming complexities.
API Access
Has API
No
API Access
Has API
No
Integrations
Python
Yes
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
C
No
Integrations
Python
Yes
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
C
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
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
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
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
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/hpc/parallelcluster/
Vendor Details
Company Name
MPI for Python
Website
mpi4py.readthedocs.io/en/stable/