CAREER: Slice-Processing: Highly-Accurate Prediction for Future High-Performance Processors

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DATE: April 19, 2000PROPOSAL NUMBER: C-CR 9984371INSTITUTION: Northwestern UniversityPI: Andreas MoshovosTITLE: CAREER: Slice-Processing: Highly-Accurate Prediction for Future High-Performance ProcessorsABSTRACTPrediction-driven speculative techniques are used in virtually all modern, high-performance processors. Such techniques offer a promising direction for furtherboosting performance. However, the benefits so obtained are only as good as theunderlying prediction-based methods are at guessing what the program needs.This project investigates slice-prediction, a paradigm that aims at providinghighly accurate prediction beyond what is possible with the existing methods.Existing methods are primarily outcome-based since they rely on repeatingpatterns in a program's outcome stream (e.g., addresses or branch directions).However, such patterns do not always exist. More importantly, as currentoutcome-based methods are perfected, irregular patterns increasingly dominateperformance. Slice-prediction attacks such cases by predicting the computation-slice that produces such irregular yet performance-critical outcomes. Predictedslices are then treated as miniature, autonomous programs, which can precomputeperformance critical outcomes. The intuition is that while the outcome of aprogram can be irregular the method used is typically relatively simple andfairly stable.This project focuses on architecturally invisible, hardware implementations ofslice-prediction, and targets the following applications: (1) Branch Predictionand (2) Data Prefetching. Performance achieved by slice-prediction is evaluatedthrough a detailed software simulator over a set of widely used benchmarks.