ShortCut

Abstract

Applications commonly perform repeated computations that are mostly, but not exactly, similar. If a subsequent computation were identical to the original, the operating system could improve performance via memoization, i.e., capturing the differences in program state caused by the computation and applying the differences in lieu of re-executing the computation. However, opportunities for generic memoization are limited by a myriad of differences that arise during execution, e.g., timestamps differ and communication yields non-deterministic responses. Such difference cause memoization to produce incorrect state. ShortCut generically accelerates mostly-deterministic computation by partial memoization. It creates a program, called a slice, that modifies the state diff to account for variation in a subsequent computation. ShortCut learns which inputs, data flows and control flows are likely, and makes assumptions about possible values for each during slice generation. Assuming only likely values rather than allowing all possible values makes complex slice generation feasible and slice execution much faster. Slices are self-verifying; they include predicates that verify all assumptions made during a subsequent execution. When these verifications succeed, the slice is guaranteed to produce a correct modification. If a verification fails, ShortCut transparently rolls back the slice execution and runs the non-memoized computation. Users see no difference between normal, memoized, and rolled-back execution.