Participants in the Graphcore Academic Programme will receive free access to our IPU compute platform in the cloud. Each system comprises 16x Mk1 GC2 IPUs on 8x C2 PCIe cards, inside a Dell DSS8440 server.
Other benefits of the programme include support and regular check-ins from Graphcore’s in-house researchers and engineers. Graphcore may also offer support with grant applications and funding proposals.
More details on the Graphcore Academic Programme and information on how to apply can be found at graphcore.ai/academic.
We will be prioritising access to projects and proposals that fall into the following areas. However, we will also consider other proposals that include innovative applications of the IPU:
- Sparse training
- Conditional sparse computation
- Optimisation of stochastic learning
- New efficient models for deep learning and graph networks
- Small graph networks
- New directions for parallel training
- Local parallelism
- Multi-model training
The Graphcore Academic Programme builds on the body of academic research that has already been produced using the IPU. Some of the world’s foremost academics and institutions have published papers detailing advances made possible by our compute platform – among them researchers from Imperial College London, UC Berkeley, UMass Amherst, and the University of Bristol.
Their work variously details both quantitative performance gains, and novel applications for the IPU based on specific capabilities not found in other processor types. In each case, the results point to future research directions – enabling a virtuous cycle of exploration and discovery.
