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.
Start with this big picture before you dive into your ML development with Cerebras system.
Programming model and the compilerGet to know how Cerebras separates compile vs execution, and the compiler flow from framework to the executable.
The Cerebras server clusterHow a Cerebras multi-worker configuration differs from a GPU multi-worker configuration.
Weight streaming vs pipelined executionHow to run an extremely large model such as a GPT-3 model (with ~1 billion parameters) or a smaller sized model.
Whether your framework is TensorFlow or PyTorch, get to know the general ML workflow on Cerebras first.
Go over this quick checklist to ensure you have access credentials, hostnames, IP address of the CS system and more.
GitHub repo with a partial list of various neural network models currently supported.
PyTorch or TensorFlow, we got you covered. Start your framework-to-CS journey here.
Determine optimal Slurm resources, use the compiler report to enhance input function.