Section: New Results

Runtime Multi-Versioning and Specialization

Participant : Philippe Clauss.

We have developped an extension of APOLLO that implements code multi-versioning and specialization to optimize and parallelize loop kernels that are invoked many times with varying parameters. These parameters may influence the code structure, the touched memory locations, the workload, and the runtime performance. They may also impact the validity of the parallelizing and optimizing polyhedral transformations that are applied on-the-fly.

For a target loop kernel and its associated parameters, a different optimizing and parallelizing transformation is evaluated at each invocation, among a finite set of transformations (multi-versioning and specialization). The best performing transformed code version is stored and indexed using its associated parameters. When every optimizing transformation has been evaluated, the best performing code version regarding the current parameters, which has been stored, is relaunched at next invocations (memoization).

This work has been accomplished in collaboration with Raquel Lazcano and Eduardo Juarez of the Universidad Politécnica de Madrid, Spain, and has been published at the ACM SIGPLAN 2020 International Conference on Compiler Construction (CC 2020).