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  1. Proceedings of the 1st ACM SIGPLAN workshop on Functional high-performance computing (FHPC '12)
  2. Seeing the futures: profiling shared-memory parallel racket
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Using domain-specific languages and access-execute descriptors to expand the parallel code synthesis design space: keynote talk
Avalanche: a fine-grained flow graph model for irregular applications on distributed-memory systems
Haskell vs. f# vs. scala: a high-level language features and parallelism support comparison
Parallel discrete event simulation with Erlang
Parallel programming in Haskell almost for free: an embedding of intel's array building blocks
Harnessing parallelism in FPGAs using the hume language
Financial software on GPUs: between Haskell and Fortran
An embedded DSL for stochastic processes: research article
Usage of petri nets for high performance computing
Seeing the futures: profiling shared-memory parallel racket

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Seeing the futures: profiling shared-memory parallel racket

Content Provider ACM Digital Library
Author Findler, Robert Bruce Fetscher, Burke Swaine, James St-Amour, Vincent Flatt, Matthew
Abstract This paper presents the latest chapter in our adventures coping with a large, sequentially-tuned, legacy runtime system in today's parallel world. Specifically, this paper introduces our new graphical visualizer that helps programmers understand how to program in parallel with Racket's futures and, to some extent, what performs well in sequential Racket. Overall, our experience with parallelism in Racket is that we can achieve reasonable parallel performance in Racket without sacrificing the most important property of functional programming language implementations, namely safety. That is, Racket programmers are guaranteed that every Racket primitive (and thus all functions built using Racket primitives) will either behave properly, or it will signal an error explaining what went wrong. That said, however, it is challenging to understand how to best use futures to achieve interesting speedups, and the visualizer is our attempt to more widely disseminate key performance details of the runtime system in order to help Racket programmers maximize performance.
Starting Page 73
Ending Page 82
Page Count 10
File Format PDF
ISBN 9781450315777
DOI 10.1145/2364474.2364485
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2012-09-15
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Performance tuning Parallel functional programming Racket
Content Type Text
Resource Type Article
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