Skip to main content
eScholarship
Open Access Publications from the University of California

UC Riverside

UC Riverside Previously Published Works bannerUC Riverside

HALWPE: Hardware-Assisted Light Weight Performance Estimation for GPUs

  • Author(s): O'Neal, K;
  • Brisk, P;
  • Shriver, E;
  • Kishinevsky, M
  • et al.
Abstract

This paper presents a predictive modeling framework for GPU performance. The key innovation underlying this approach is that performance statistics collected from representative workloads running on current generation GPUs can effectively predict the performance of next-generation GPUs. This is useful when simulators are available for the next-generation device, but simulation times are exorbitant, rendering early design space exploration of microarchitectural parameters and other features infeasible. When predicting performance across three Intel GPU generations (Haswell, Broadwell, Skylake), our models achieved low out-of-sample-errors ranging from 7.45% to 8.91%, while running 30,000-45,000 times faster than cycle-Accurate simulation.

Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View