Paper Info
Title
SMARTS: exploiting temporal locality and parallelism through vertical execution
Abstract
In the solution of large-scale numerical problems, pamllel computing is becoming simultaneously more important and more difictilt. The complex organization of today's multi- processors with several memory hierarchies has forced the sci- entiific progmmmer to make a choice between simple but unscal- able code and scalable but extremely complex code that does not port to other architectures. This paper describes how the SMARTS runtime system and the POOMA C++ class library for high-performance scientijk computing work together to exploit data parallelism in scientific applications while hiding the details of managing parallelism and data locality from the user. We present innovative algo- n'thms, based on the macro-dataflow model, for detecting data pamllelism and eficiently executing data-parallel statements on shared-memory multiprocessors. We also describe how these al-
Year
DOI
Venue
1999
10.1145/305138.305207
International Conference on Supercomputing 2006
Keywords
Field
DocType
temporal locality,vertical execution,programming models,barrier synchronization,data locality,cache reuse,data-parallel languages,dependence-driven execution,run-time systems,macro-dataflow,object-oriented,data-parallelism,object-parallelism,scientific computation,loop scheduling,data parallelism,parallel programming model,object oriented,scientific computing
Instruction-level parallelism,Locality of reference,Programming paradigm,Computer science,Task parallelism,Parallel computing,Data parallelism,Loop scheduling,Runtime system,Scalability
Conference
ISBN
Citations 
PageRank 
1-58113-164-X
15
2.37
References 
Authors
21
8
Name
Order
Citations
PageRank
Suvas Vajracharya13410.76
Steve Karmesin211117.80
Peter Beckman321835.20
James Crotinger4528.38
Allen Malony5948.29
Sameer Shende61351116.40
Rod Oldehoeft7153.05
Stephen Smith8152.37