NDLI: Next Generation Asynchronous Adaptive Specialization for Data-Parallel Functional Array Processing in SAC: Accelerating the Availability of Specialized High Performance Code

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Next Generation Asynchronous Adaptive Specialization for Data-Parallel Functional Array Processing in SAC: Accelerating the Availability of Specialized High Performance Code

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Next Generation Asynchronous Adaptive Specialization for Data-Parallel Functional Array Processing in SAC: Accelerating the Availability of Specialized High Performance Code

Content Provider	ACM Digital Library
Author	Wiesinger, Heinrich Grelck, Clemens
Abstract	Data-parallel processing of multi-dimensional functional/immutable arrays is characterized by a fundamental trade-off between software engineering principles on the one hand and runtime performance concerns on the other hand. Whereas the former demand code to be written in a generic style abstracting from structural properties of arrays as much as possible, the latter require an optimizing compiler to have as much information on the very same structural properties available at compile time. Asynchronous adaptive specialization of generic code to specific data to be processed at application runtime has proven to be an effective way to reconcile these contrarian demands. In this paper we revisit asynchronous adaptive specialization in the context of the functional data-parallel array language SaC. We provide a comprehensive analysis of its strengths and weaknesses and propose improvements for its design and implementation. These improvements are primarily concerned with making specializations available to running applications as quickly as possible. We propose four complementary measures to this effect. Bulk adaptive specialization speculatively waits for future specialization requests to materialize instead of addressing each request individually. Prioritized adaptive specialization aims at selecting the most profitable specializations first. Parallel adaptive specialization reserves multiple cores for specialization and, thus, computes multiple specializations simultaneously. Last but not least, persistent adaptive specialization preserves specializations across independent program runs and even across unrelated applications.
Starting Page	117
Ending Page	128
Page Count	12
File Format	PDF
ISBN	9781450329880
DOI	10.1145/2620678.2620690
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-08-28
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Single assignment c Dynamic compilation Runtime optimization Array processing Rank and shape specialization
Content Type	Text
Resource Type	Article

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