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We detail the performance optimizations made in rocHPL, AMD's open-sourceimplementation of the High-Performance Linpack (HPL) benchmark targetingaccelerated node architectures designed for exascale systems such as theFrontier supercomputer. The implementation leverages the high-throughput GPUaccelerators on the node via highly optimized linear algebra libraries, as wellas the entire CPU socket to perform latency-sensitive factorization phases. Wedetail novel performance improvements such as a multi-threaded approach tocomputing the panel factorization phase on the CPU, time-sharing of CPU coresbetween processes on the node, as well as several optimizations which hide MPIcommunication. We present some performance results of this implementation ofthe HPL benchmark on a single node of the Frontier early access cluster at OakRidge National Laboratory, as well as scaling to multiple nodes.

Optimizing High-Performance Linpack for Exascale Accelerated Architectures