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Doctoral Thesis
DOI
https://doi.org/10.11606/T.76.2001.tde-24062008-172320
Document
Author
Full name
Raul Junji Nakashima
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2001
Supervisor
Committee
Travieso, Gonzalo (President)
Bergamini, Eduardo Whitaker
Guardia, Hélio Crestana
Panetta, Jairo
Slaets, Jan Frans Willem
Title in Portuguese
Análises estatísticas para a paralelização de linguagens de atribuição única para sistemas de memória distribuída
Keywords in Portuguese
Compiladores
Linguagens funcionais
Memória distribuida
Paralelismo
Abstract in Portuguese
Este trabalho descreve técnicas de análise estática de compilação baseadas na álgebra e programação linear que buscam otimizar a distribuição de loops forall e array em programas escritos na linguagem S/SAL visando à execução em máquinas paralelas de memória distribuídas. Na fase de alinhamento, nós trabalhamos com o alinhamento de hiperplanos onde objetivo é tentar encontrar as porções dos diferentes arrays que necessitam ser distribuídas juntas. Na fase de divisão, que tenta quebrar em partes independente dados e computações, nós usamos duas funções afins, a função de decomposição de dados e a função de decomposição de computação. A última fase, o mapeamento, distribui os elementos de computação nos elementos de processamento usando um conjunto de inequações. As técnicas foram implementadas num compilador SISAL, mas pode ser usada sem mudanças em outras linguagens de associação simples e com a adição de análise de dependências pode ser usada em linguagens imperativas.
Title in English
Static analysis for the parallelization of single assigment languages for distributed memory systems
Keywords in English
Compilers
Distributed memory
Functional languages
Parallelism
Abstract in English
This work describes static compiler analysis techniques based on linear algebra and linear programming for optimizing the distribution of forall loops and of array elements in programs written in the SISAL programming language for distributed memory parallel machines. In the alignment phase, attempt is made in the identification of portions of different arrays that need to be distributed jointly by means of alignment of hyperplanes. In the partitioning phase, effort is made in breaking as even possible the computation and pertinent data in independent parts, by means of using related functions: the data decomposition function and the computation decomposition function. The last phase is dedicated to the mapping, which comprises the distribution of the elements of computation into the existing processing elements by means of a set of inequations. These techniques are being implemented in a SISAL compiler, but can be also used without changes by means of other single assignment languages or, with the addition of dependency analysis when using other set of languages, as well.
 
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RaulNakashima_D.pdf (3.88 Mbytes)
Publishing Date
2008-07-04
 
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