With performance comparable to the Nvidia V100 GPU, a common accelerator in HPC but better energy consumption numbers and memory bandwidth potential, Graphcore can turn heads in supercomputing. That is, if the software stack can be built to meet some tough portability, programmability requirements.
While the Graphcore IPU will not be a fit for all HPC workloads by any stretch, work out of the University of Bristol on stencil computations for structured grid operations proves the IPUs mettle, even if such testing takes some extra software footwork. These problems in HPC are high-value in that they are the core solvers for differential equations used in areas including computational fluid dynamics—a compute-heavy workload frequently run at scale on supercomputing resources.
The University of Bristol has had Graphcore hardware for several months and have been exploring its relevance in a broader array of scientific computing domains, including particle physics (for CERN in addition to Bristol).