SLATE: Software for Linear Algebra Targeting Exascale

When: Friday, January, 2019
Where: PGH 232
Time: 11:00 AM

Speaker: Dr. Jakub Kurzak, University of Tennessee, Knoxville

Host: Dr. Panruo Wu

Software for Linear Algebra Targeting Exascale (SLATE) is being developed as part of the Exascale Computing Project (ECP), which is a collaborative effort between two US Department of Energy (DOE) organizations, the Office of Science and the National Nuclear Security Administration (NNSA). The objective of SLATE is to provide fundamental dense linear algebra capabilities to the US Department of Energy and to the high-performance computing (HPC) community at large.

The ultimate objective of SLATE is to replace the ScaLAPACK library, which has become the industry standard for dense linear algebra operations in distributed memory environments. However, after two decades of operation, ScaLAPACK is past the end of its life cycle and overdue for a replacement, as it can hardly be retrofitted to support hardware accelerators, which are an integral part of today’s HPC hardware infrastructure.

Primarily, SLATE aims to extract the full performance potential and maximum scalability from modern, many-node HPC machines with large numbers of cores and multiple hardware accelerators per node. For typical dense linear algebra workloads, this means getting close to the theoretical peak performance and scaling to the full size of the machine (i.e., thousands to tens of thousands of nodes). This is to be accomplished in a portable manner by relying on standards like MPI and OpenMP.

Bio:

Jakub Kurzak is a Research Assistant Professor at the Innovative Computing Laboratory in the University of Tennessee, Knoxville's Department of Electrical Engineering and Computer Science. Jakub earned his MSc in Electrical and Computer Engineering from Wroclaw University of Technology in Wroclaw, Poland, and he earned his PhD in Computer Science from the University of Houston in Houston, Texas. Jakub's research interests include dense linear algebra libraries for high-performance computing and automatic performance tuning for hardware accelerators.