Speaker
Dr
Justin Foley
(Microway and Nvidia)
Description
We describe recent additions to the QUDA software library that are
aimed at extending strong scaling in multi-GPU lattice calculations.
These include the addition of CPU-thread support in order to increase
concurrency and improve the overlap of computation and communication
in Krylov solver routines, as well as the modifications needed to enable the GPUDirect RDMA feature recently introduced by NVIDIA and Mellanox. However, we focus in particular on the implementation and performance of so-called S-step variants of common Krylov solvers on current NVIDIA hardware. The S-step formulations are designed to reduce the number of global synchronizations associated
with the calculation of vector inner products. These formulations may, when combined with communication-reducing methods such as additive Schwarz preconditioning, form the basis for a set of optimal Krylov solvers for many-GPU calculations.
Primary author
Dr
Justin Foley
(Microway and Nvidia)
Co-author
Dr
Mike Clark
(Nvidia)
