Space-efficient multi-versioning for input-adaptive feedback-driven program optimizations

Abstract

Function versioning is an approach to addressing inputsensitivity of program optimizations. A major side effect of it is notable code size increase, which has been hindering its broad applications to large code bases and space-stringent environments. In this paper, we initiate a systematic exploration into the problem, providing answers to some fundamental questions: Given a space constraint, to which function we should apply versioning? How many versions of a function should we include in the final executable? Is the optimal selection feasible to do in polynomial time? This study proves selecting the best set of versions under a space constraint is NP-complete and proposes a heuristic algorithm named CHoGS which yields near optimal results in quadratic time. We implement the algorithm and conduct experiments through the IBM XL compilers. We observe significant performance enhancement with only slight code size increase; the results from CHoGS show factors of higher space efficiency than those from traditional hotness-based methods.

Characterizing Performance and Cache Impacts of Code Multi-versioning on Multicore Architectures

“…Zhou et al [7] present a space-efficient multi-versioning algorithm targeting large code bases and space limited environments, focusing on good performance improvements with only small size increase. They do not investigate the impact of code size increases on performance and cache behavior in detail, and target primarily space-restricted embedded systems rather than multi-core parallel environments.…”

Multiversioned decoupled access-execute: the key to energy-efficient compilation of general-purpose programs

“…Software multi-versioning was proposed to reduce the overhead of code instrumentation [4,8,10,14,16,30], for checking program correctness [14], for loop parallelization, for automatic, speculative optimizations [7,19,29], or to optimize the execution for different inputs [41,46]. The technique periodically switches between highoverhead instrumenting versions and more efficient original or optimized versions [4,8,10,16].…”