More Innovation in Less Time

With the Cerebras software platform, you will spend more time pushing the frontiers of deep learning instead of optimizing distributed implementations. Get up and running quickly utilizing the enormous size and high-bandwidth of CS-2 without changing your workflows. Utilize existing frameworks for your work or dive deep developing custom kernels – the Software Platform is designed for flexibility and optimization.

Software Platform

Software that Integrates Seamlessly with your Workflows

The Cerebras software platform integrates with popular machine learning frameworks like TensorFlow and PyTorch, so researchers can use familiar tools and effortlessly bring their models to the CS-2.

A programmable low-level interface allows researchers to extend the platform and develop custom kernels – empowering them to push the limits of ML innovation.


Cerebras Graph Compiler Drives Full Hardware Utilization

The Cerebras Graph Compiler (CGC) automatically translates your neural network to a CS-2 executable.

Every stage of CGC is designed to maximize WSE-2 utilization. Kernels are intelligently sized so that more cores are allocated to more complex work. The Graph Compiler then generates a placement and routing, unique for each neural network, to minimize communication latency between adjacent layers.

Software Tools

Designed for flexibility and extensibility

The Cerebras software platform includes an extensive library of primitives for standard deep learning computations, as well as a familiar C-like interface for developing custom software kernels.

A complete suite of debug and profiling tools allows researchers to optimize the platform for their work.