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What is DeepSpeed?

DeepSpeed is an innovative open-source library designed to optimize deep learning workflows specifically for PyTorch. Its main objective is to boost efficiency by reducing the demand for computational resources and memory, while also enabling the effective training of large-scale distributed models through enhanced parallel processing on the hardware available. Utilizing state-of-the-art techniques, DeepSpeed delivers both low latency and high throughput during the training phase of models. This powerful tool is adept at managing deep learning architectures that contain over one hundred billion parameters on modern GPU clusters and can train models with up to 13 billion parameters using a single graphics processing unit. Created by Microsoft, DeepSpeed is intentionally engineered to facilitate distributed training for large models and is built on the robust PyTorch framework, which is well-suited for data parallelism. Furthermore, the library is constantly updated to integrate the latest advancements in deep learning, ensuring that it maintains its position as a leader in AI technology. Future updates are expected to enhance its capabilities even further, making it an essential resource for researchers and developers in the field.

What is Amazon EC2 Trn1 Instances?

Amazon's Elastic Compute Cloud (EC2) Trn1 instances, powered by AWS Trainium processors, are meticulously engineered to optimize deep learning training, especially for generative AI models such as large language models and latent diffusion models. These instances significantly reduce costs, offering training expenses that can be as much as 50% lower than comparable EC2 alternatives. Capable of accommodating deep learning models with over 100 billion parameters, Trn1 instances are versatile and well-suited for a variety of applications, including text summarization, code generation, question answering, image and video creation, recommendation systems, and fraud detection. The AWS Neuron SDK further streamlines this process, assisting developers in training their models on AWS Trainium and deploying them efficiently on AWS Inferentia chips. This comprehensive toolkit integrates effortlessly with widely used frameworks like PyTorch and TensorFlow, enabling users to maximize their existing code and workflows while harnessing the capabilities of Trn1 instances for model training. Consequently, this approach not only facilitates a smooth transition to high-performance computing but also enhances the overall efficiency of AI development processes. Moreover, the combination of advanced hardware and software support allows organizations to remain at the forefront of innovation in artificial intelligence.

Media

Media

Integrations Supported

PyTorch
AWS Deep Learning AMIs
AWS Deep Learning Containers
AWS Inferentia
AWS Neuron
AWS Nitro System
AWS Trainium
Amazon EC2
Amazon EC2 Capacity Blocks for ML
Amazon EC2 Inf1 Instances
Amazon EC2 P4 Instances
Amazon EC2 Trn2 Instances
Amazon EC2 UltraClusters
Amazon SageMaker
Amazon Web Services (AWS)
Axolotl
Comet LLM
Nurix
Python
TensorFlow

Integrations Supported

PyTorch
AWS Deep Learning AMIs
AWS Deep Learning Containers
AWS Inferentia
AWS Neuron
AWS Nitro System
AWS Trainium
Amazon EC2
Amazon EC2 Capacity Blocks for ML
Amazon EC2 Inf1 Instances
Amazon EC2 P4 Instances
Amazon EC2 Trn2 Instances
Amazon EC2 UltraClusters
Amazon SageMaker
Amazon Web Services (AWS)
Axolotl
Comet LLM
Nurix
Python
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

$1.34 per hour
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

www.deepspeed.ai/

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/ec2/instance-types/trn1/

Categories and Features

Deep Learning

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

Categories and Features

Deep Learning

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

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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