The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Author: Steven Harris (Washington University in St. Louis)
Advisor: Roger Chamberlain (Washington University in St. Louis), Christopher Gill (Washington University in St. Louis)
Abstract: Heterogeneous platforms introduce new complexities into performance modeling and prediction. The intrinsic performance asymmetries found in these platforms require radically different approaches to manage the compute diversity of this polymorphic architectural design space. Core heterogeneity augments our traditional notion of compute semantics, making simply defining the number of compute units of a given speed no longer sufficient. Workload adaptation and complexity mitigation is no longer simply a question of volume (number of cores) but also constitution (types of cores). To ensure performance portability of workloads on these platforms requires an understanding of and investigation into the interactions of workloads, compute units, and parameters that create a spectrum of performance opportunities extending across classes of platforms.
Using the Orange Pi 5, a heterogeneous asymmetric multiprocessing platform (AMP), to examine this prolific domain, we embark on a principled analysis journey into the performance implications of classical workloads (i.e., matrix-matrix multiply) on these platforms. We demonstrate techniques enabling complexity mitigation and performance portability across compute unit groups. Finally, by applying structural equation modeling (SEM) to this reference platform, we discover the most critical components impacting performance for these classical workloads, revealing component interactions affecting platform performance, and articulating the impact of parameter effects on platform performance using a novel and unprecedented approach in computer engineering.
Thesis Canvas: pdf