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Massachusetts Institute of Technology

MSL : a synthesis enabled language for distributed high performance computing implementations

Abstract

dc:description.abstract

SPMD-style (single program multiple data) parallel programming, usually done with MPI, are dominant in high-performance computing on distributed memory machines. This thesis outlines a new methodology to aid in the development of SPMD-style high-performance programs. The new methodology is supported by a new language called MSL that combines ideas from generative programming and software synthesis to simplify the development process as well as to allow programmers to package complex implementation strategies behind clean high-level reusable abstractions. We propose in this thesis the key new language features in MSL and new analyses in order to support synthesis and equivalence checking for programs written in SPMD-style, as well as empirical evaluations of our new methodology.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2016

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Xu, Zhilei
Advisor dc:contributor.advisor
  • Armando Solar-Lezama.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/107359
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/107359

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Xu, Zhilei. MSL : a synthesis enabled language for distributed high performance computing implementations. Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/107359