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ease
features
design
support

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Average Ratings 0 Ratings

Total
ease
features
design
support

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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.

Description

NVIDIA Base Command Manager provides rapid deployment and comprehensive management for diverse AI and high-performance computing clusters, whether at the edge, within data centers, or across multi- and hybrid-cloud settings. This platform automates the setup and management of clusters, accommodating sizes from a few nodes to potentially hundreds of thousands, and is compatible with NVIDIA GPU-accelerated systems as well as other architectures. It facilitates orchestration through Kubernetes, enhancing the efficiency of workload management and resource distribution. With additional tools for monitoring infrastructure and managing workloads, Base Command Manager is tailored for environments that require accelerated computing, making it ideal for a variety of HPC and AI applications. Available alongside NVIDIA DGX systems and within the NVIDIA AI Enterprise software suite, this solution enables the swift construction and administration of high-performance Linux clusters, thereby supporting a range of applications including machine learning and analytics. Through its robust features, Base Command Manager stands out as a key asset for organizations aiming to optimize their computational resources effectively.

API Access

Has API

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Screenshots View All

Integrations

AWS Batch
Amazon Web Services (AWS)
AWS Deep Learning AMIs
AWS Elastic Fabric Adapter (EFA)
AWS Nitro System
AWS Trainium
Amazon API Gateway
Amazon EC2 Capacity Blocks for ML
Amazon EC2 G5 Instances
Amazon EC2 Inf1 Instances
Amazon EC2 Trn1 Instances
Amazon EC2 Trn2 Instances
Amazon EC2 UltraClusters
Kubernetes
MXNet
NVIDIA AI Enterprise
NVIDIA Base Command
NVIDIA Cumulus Linux
NVIDIA DGX Cloud
Slurm

Integrations

AWS Batch
Amazon Web Services (AWS)
AWS Deep Learning AMIs
AWS Elastic Fabric Adapter (EFA)
AWS Nitro System
AWS Trainium
Amazon API Gateway
Amazon EC2 Capacity Blocks for ML
Amazon EC2 G5 Instances
Amazon EC2 Inf1 Instances
Amazon EC2 Trn1 Instances
Amazon EC2 Trn2 Instances
Amazon EC2 UltraClusters
Kubernetes
MXNet
NVIDIA AI Enterprise
NVIDIA Base Command
NVIDIA Cumulus Linux
NVIDIA DGX Cloud
Slurm

Integrations

AWS Batch
Amazon Web Services (AWS)
AWS Deep Learning AMIs
AWS Elastic Fabric Adapter (EFA)
AWS Nitro System
AWS Trainium
Amazon API Gateway
Amazon EC2 Capacity Blocks for ML
Amazon EC2 G5 Instances
Amazon EC2 Inf1 Instances
Amazon EC2 Trn1 Instances
Amazon EC2 Trn2 Instances
Amazon EC2 UltraClusters
Kubernetes
MXNet
NVIDIA AI Enterprise
NVIDIA Base Command
NVIDIA Cumulus Linux
NVIDIA DGX Cloud
Slurm

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

$11.57 per hour
Free Trial
Free Version

Pricing Details

No price information available.
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

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

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

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/

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

www.nvidia.com/en-us/data-center/base-command/manager/

Product Features

Product Features

Deep Learning

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

HPC

Product Features

Alternatives

Alternatives

Alternatives

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