Bristol-based unicorn, Graphcore, has announced its participation in SparCity – a new European project whose goal is to create a supercomputing framework that can specifically harness the power and energy efficiency of sparse computation for emerging AI applications.

As one of the region’s most successful deep tech businesses, Graphcore will be playing a central role in the project, reflecting their commitment to developing next-generation approaches to artificial intelligence

SparCity has three years of duration and a total budget of 2.6M€; the collaborative project between 6 partners in 4 countries aims to build a sustainable exascale ecosystem and increase Europe’s competitiveness.

Creating a supercomputing framework

The main goal of SparCity is to create a supercomputing framework that will provide efficient algorithms and coherent tools specifically designed for maximising the performance and energy efficiency of sparse computations on emerging High Performance Computing systems, while also opening up new usage areas for sparse computations in data analytics and deep learning.

“When talking about sparse computations, people think of scientific applications, finite element methods, mesh computation, etc. However, this project will also open up new usage areas for sparse computation, including data analytics and deep learning. That is why it is a very impactful project.” says Dr Didem Unat, the coordinator of SparCity at Koç University.

To demonstrate the effectiveness, societal impact, and usability of the framework, the SparCity project will enhance the computing scale and energy efficiency of four challenging real-life applications that come from drastically different domains, namely, computational cardiology, social networks, bioinformatics and autonomous driving. By targeting this collection of challenging applications, SparCity will develop world-class, extreme-scale and energy-efficient HPC technologies.

SparCity involves partnerships with Sabanci Universitesi (Turkey), Simula Research Laboratory (Norway), INESC-ID (Portugal), Ludwig-Maximilians-Universitaet Muenchen (Germany) and Graphcore (Norway), with the coordination of Koç University (Turkey).

“It is thus a great opportunity for researchers at Simula to collaborate with internationally leading experts, through these EuroHPC projects, to bring innovative use of HPC to real-world applications.” says Professor Xing Cai, head of the High Performance Computing department at Simula.

Dr. Kamer Kaya, from Sabancı University, says, “This is an excellent chance for my team at Sabancı University to share our expertise on HPC and work with great researchers on a challenging project which will hopefully change the way we handle extreme-scale problems using sparse data.”

Ola Tørudbakken, GM & SVP Systems at Graphcore adds, “Graphcore is committed to enabling next-generation techniques in AI compute, including innovative approaches to sparsity. Putting new hardware and software tools into the hands of researchers through the SparCity initiative will drive a virtuous cycle of discovery and deployment throughout Europe.”

“For INESC-ID, SparCity will leverage the efforts on the European low power processing technologies (in particular the European Processor Initiative) and contribute to the realisation of future exascale system architectures based on such technologies” says Prof. Leonel Sousa, Full Professor of the Electrical and Computer Engineering Department of Instituto Superior Técnico, University of Lisbon, and Senior Researcher of the High-Performance Computer Architectures and Systems Research Group.

Main Image Credit: Photo by Vitaly Vlasov from Pexels

Shona Wright

Shona covers all things editorial at TechSPARK. She publishes news articles, interviews and features about our fantastic tech and digital ecosystem, working with startups and scaleups to spread the word about the cool things they're up to. She also oversees TechSPARK's social media, sharing the latest updates on everything from investment news to green tech meetups and inspirational stories.