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Explore the Documentation

This documentation will help you program for the CS system. It covers both basic and advanced topics. Use these docs to accelerate your machine learning training and inference applications on the CS system. Here you will find getting started guides, quickstarts, tutorials, code examples, release notes, and more.

Learn Cerebras basics

How Cerebras works How Cerebras works

Start by learning the basics about how Cerebras systems are deployed and used.

Cerebras installations

Cerebras offers two forms of deployment for CS systems, Wafer-Scale clusters and Original Cerebras installations. Which one do you have?

Cerebras Software Platform

The Cerebras Graph Compiler (CGC) compiles your ML code into a binary for execution on a CS system.

Pipelined and Weight Streaming execution

Cerebras Software Platform supports two execution modes on CS systems.

Types of CS systems installations in more details Types of installations

Learn about Wafer-Scale cluster and Original Cerebras installation and what execution modes are supported by them.

Execution modes in more details Pipelined and Weight Streaming modes

How Pipelined and Weight Streaming work.

ML workflow on Cerebras Cerebras ML workflow

Whether your framework is TensorFlow or PyTorch, get to know the general ML workflow on Cerebras first.

Quickstarts

Quickstarts for Wafer-Scale Cluster

TensorFlow: Getting Started

Quick-Start Guide with a Simple TensorFlow Model on a Cerebras Wafer-Scale Cluster

PyTorch: Getting Started

Quick-Start Guide with a Simple PyTorch Model on a Cerebras Wafer-Scale Cluster

Quickstarts for Original Cerebras Installation

TensorFlow: Getting Started

Quick-Start Guide with a Simple TensorFlow Model in an Original Cerebras Installation

PyTorch: Getting Started

Quick-Start Guide with a Simple PyTorch Model in an Original Cerebras Installation

Check out the reference models

Reference code Cerebras Model Zoo Reference Models

GitHub repo with a partial list of various neural network models currently supported.

Start developing

Dive into developing with TensorFlow and PyTorch

PyTorch or TensorFlow, we got you covered. Start your framework-to-CS journey here.

Develop with TensorFlow

Start your TensorFlow to CS journey here

Develop with PyTorch

Start your PyTorch to CS journey here

Optimize your ML code Performance optimization practices

Determine optimal Slurm resources, use the compiler report to enhance input function.

Extensions

Extensions Adding custom packages to cbcore

Contact

For questions and feedback on documentation Contact docs@cerebras.net via email.

For support Contact support@cerebras.net via email.

Cerebras company website

Visit cerebras.net.

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Software Release Notes