Trevor E. Carlson

BranchSherpa: A Fast and Accurate Analytical Modeling Framework for Branch Predictors

DGNA: Dissecting GPU NUMA Architecture through Microbenchmarking and Data Analysis

This paper introduces DGNA, a methodology designed to unveil the NUMA architecture of the GPU memory hierarchy through microbenchmarking and data analysis, and is the first paper to detail the NUMA architecture within the GPU memory subsystem.

A Cache Modeling Framework for Accelerator Systems

PlastiCache represents an accelerator memory stream as address–time pairs and extends reuse-distance analysis with predicted service intervals for outstanding misses, and targets early-stage cache design-space exploration by preserving the relative ordering of candidate configurations.