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Mon 19 Jun 2017 10:50 - 11:15 at Aula Master - Compiler Optimizations Chair(s): Uday Bondhugula

We present an approach to optimize the cache locality for recursive programs by dynamically splicing—recursively interleaving—the execution of distinct function invocations. By utilizing data effect annotations, we identify concurrency and data reuse opportunities across function invocations and interleave them to reduce reuse distance. We present algorithms that efficiently track effects in recursive programs, detect interference and dependencies, and interleave execution of function invocations using user-level (non-kernel) lightweight threads. To enable multi-core execution, a program is parallelized using a nested fork/join programming model. Our cache optimization strategy is designed to work in the context of a random work stealing scheduler. We present an implementation using the MIT Cilk framework that demonstrates significant improvements in sequential and parallel performance, competitive with a state-of-the-art compile-time optimizer for loop programs and a domain-specific optimizer for stencil programs.

Conference Day
Mon 19 Jun

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

10:50 - 12:30
Compiler OptimizationsPLDI Research Papers at Aula Master
Chair(s): Uday BondhugulaIndian Institute of Science
10:50
25m
Talk
Cache Locality Optimization for Recursive Programs
PLDI Research Papers
Jonathan Lifflander, Sriram KrishnamoorthyPacific Northwest National Laboratories
11:15
25m
Talk
Fusing Effectful Comprehensions
PLDI Research Papers
Olli Saarikivi, Margus VeanesMicrosoft Research, Todd Mytkowicz, Madan MusuvathiMicrosoft Research
11:40
25m
Talk
Generalizations of the Theory and Deployment of Triangular Inequality for Compiler-Based Strength Reduction
PLDI Research Papers
Yufei DingNorth Carolina State University, Lin NingNorth Carolina State University, Hui GuanNorth Carolina State University, Xipeng ShenNorth Carolina State University
Media Attached
12:05
25m
Talk
ALIVE-INFER: Data-Driven Precondition Inference for Peephole Optimizations in LLVM
PLDI Research Papers
David MenendezRutgers University, Santosh NagarakatteRutgers University, USA
Media Attached