Average Ratings 0 Ratings
Average Ratings 133 Ratings
Description
Amazon EC2 Capacity Blocks for Machine Learning allow users to secure accelerated computing instances within Amazon EC2 UltraClusters specifically for their machine learning tasks. This service encompasses a variety of instance types, including Amazon EC2 P5en, P5e, P5, and P4d, which utilize NVIDIA H200, H100, and A100 Tensor Core GPUs, along with Trn2 and Trn1 instances that leverage AWS Trainium. Users can reserve these instances for periods of up to six months, with cluster sizes ranging from a single instance to 64 instances, translating to a maximum of 512 GPUs or 1,024 Trainium chips, thus providing ample flexibility to accommodate diverse machine learning workloads. Additionally, reservations can be arranged as much as eight weeks ahead of time. By operating within Amazon EC2 UltraClusters, Capacity Blocks facilitate low-latency and high-throughput network connectivity, which is essential for efficient distributed training processes. This configuration guarantees reliable access to high-performance computing resources, empowering you to confidently plan your machine learning projects, conduct experiments, develop prototypes, and effectively handle anticipated increases in demand for machine learning applications. Furthermore, this strategic approach not only enhances productivity but also optimizes resource utilization for varying project scales.
Description
RunPod provides a cloud infrastructure that enables seamless deployment and scaling of AI workloads with GPU-powered pods. By offering access to a wide array of NVIDIA GPUs, such as the A100 and H100, RunPod supports training and deploying machine learning models with minimal latency and high performance. The platform emphasizes ease of use, allowing users to spin up pods in seconds and scale them dynamically to meet demand. With features like autoscaling, real-time analytics, and serverless scaling, RunPod is an ideal solution for startups, academic institutions, and enterprises seeking a flexible, powerful, and affordable platform for AI development and inference.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
PyTorch
TensorFlow
Amazon EC2 P4 Instances
Amazon EC2 P5 Instances
Amazon EC2 UltraClusters
Amazon EKS
Amazon Elastic Container Service (Amazon ECS)
DeepSeek Coder
DeepSeek R1
Integrations
Amazon Web Services (AWS)
PyTorch
TensorFlow
Amazon EC2 P4 Instances
Amazon EC2 P5 Instances
Amazon EC2 UltraClusters
Amazon EKS
Amazon Elastic Container Service (Amazon ECS)
DeepSeek Coder
DeepSeek R1
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$0.40 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/ec2/capacityblocks/
Vendor Details
Company Name
RunPod
Founded
2022
Country
United States
Website
www.runpod.io
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Product Features
Infrastructure-as-a-Service (IaaS)
Analytics / Reporting
Configuration Management
Data Migration
Data Security
Load Balancing
Log Access
Network Monitoring
Performance Monitoring
SLA Monitoring
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Serverless
API Proxy
Application Integration
Data Stores
Developer Tooling
Orchestration
Reporting / Analytics
Serverless Computing
Storage