PMEvo: Portable Inference of Port Mappings for Out-of-Order Processors by Evolutionary Optimization
Achieving peak performance in a computer system requires optimizations in every layer of the system, be it hardware or software. A detailed understanding of the underlying hardware, and especially the processor, is crucial to optimize software. One key criterion for the performance of a processor is its ability to exploit instruction-level parallelism. This ability is determined by the port mapping of the processor, which describes the execution units of the processor for each instruction.
Processor manufacturers usually do not share the port mappings of their microarchitectures. While approaches to automatically infer port mappings from experiments exist, they are based on processor-specific hardware performance counters that are not available on every platform.
We present PMEvo, a framework to automatically infer port mappings solely based on the measurement of the execution time of short instruction sequences. PMEvo uses an evolutionary algorithm that evaluates the fitness of candidate mappings with an analytical throughput model formulated as a linear program. Our prototype implementation infers a port mapping for Intel's Skylake architecture that predicts measured instruction throughput with an accuracy that is competitive to existing work. Furthermore, it finds port mappings for AMD's Zen+ architecture and the ARM Cortex-A72 architecture, which are out of scope of existing techniques.
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06:20 - 07:40 | PerformancePLDI Research Papers at PLDI Research Papers live stream Chair(s): Fredrik Kjolstad Stanford University | ||
06:20 20mTalk | PMEvo: Portable Inference of Port Mappings for Out-of-Order Processors by Evolutionary Optimization PLDI Research Papers | ||
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07:20 20mTalk | SCAF: A Speculation-Aware Collaborative Dependence Analysis Framework PLDI Research Papers Sotiris Apostolakis Princeton University, USA, Ziyang Xu Princeton University, USA, Zujun Tan Princeton University, USA, Greg Chan Princeton University, USA, Simone Campanoni Northwestern University, USA, David I. August Princeton University, USA DOI Pre-print Media Attached |