Paper Info
Title
Modeling The Conflicting Demands Of Parallelism And Temporal/Spatial Locality In Affine Scheduling
Abstract
The construction of effective loop nest optimizers and parallelizers remains challenging despite decades of work in the area. Due to the increasing diversity of loop-intensive applications and to the complex memory/computation hierarchies in modern processors, optimization heuristics are pulled towards conflicting goals, highlighting the lack of a systematic approach to optimizing locality and parallelism. Acknowledging these conflicting demands on loop nest optimization, we propose an algorithmic template capable of modeling the multi-level parallelism and the temporal/spatial locality of multiprocessors and accelerators. This algorithmic template orchestrates a collection of parameterizable, linear optimization problems over a polyhedral space of semantics-preserving transformations. While the overall problem is not convex, effective algorithms can be derived from this template delivering unprecedented performance portability over GPU and multicore CPU. We discuss the rationale for this algorithmic template and validate it on representative computational kernels/benchmarks.
Year
DOI
Venue
2018
10.1145/3178372.3179507
CC'18: PROCEEDINGS OF THE 27TH INTERNATIONAL CONFERENCE ON COMPILER CONSTRUCTION
Keywords
Field
DocType
Polyhedral Model, Compiler Optimizations
Loop nest optimization,Locality,Programming language,Computer science,Scheduling (computing),Parallel computing,Optimizing compiler,Heuristics,Software portability,Linear programming,Polytope model
Conference
Citations 
PageRank 
References 
4
0.40
21
Authors
7
Name
Order
Citations
PageRank
Oleksandr Zinenko1162.61
Sven Verdoolaege270646.15
Chandan Reddy340.40
Jun Shirako443334.56
Tobias Grosser527116.04
Vivek Sarkar64318409.41
Albert Cohen728212.38