Research

Publication (Conferences and Seminars)

Runtime multi-versioning and specialization inside a memoized speculative loop optimizer

Lazcano López, Raquel; Madroñal Quintín, Daniel; Juárez Martínez, Eduardo; Clauss, P.
Abstract:
In this paper, we propose a runtime framework 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).
Research areas:
Year:
2020
Type of Publication:
Conferences and Seminars
Keywords:
runtime speculative optimization and parallelization; multi-versioning; memoization; specialization; polyhedral model
Publisher:
ACM
Address:
San Diego, Estados Unidos de América
Organization:
International Conference on Compiler Construction (CC)
Month:
Febrero
DOI:
10.1145/3377555.3377886