Advanced compiler optimizations for supercomputers

Padua, David; Wolfe, Michael

doi:10.1145/7902.7904

Cited by 574 publications

(158 citation statements)

References 18 publications

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“…Introductory material on parallelizing compilers can be found in [8], [9], and [11]. Also, all the parallel programs presented in the examples below use extensions similar to those described in the preliminary draft of the X3H5 ANSI committee developing parallel constructs for high level programming languages.…”

Section: Compiler Techniquesmentioning

confidence: 99%

Experience in the automatic parallelization of four Perfect-Benchmark programs

Eigenmann

Hoeflinger

et al.

Languages and Compilers for Parallel Computing

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Abstract.This paper discusses the techniques used to hand-parallelize, for the Alliant FX/80, four Fortran programs from the Perfect-Benchmark suite. The paper also includes the execution times of the programs before and after the transformations. The four programs considered here were not effectively parallelized by the automatic translators available to the authors. However, most of the techniques used for hand parallelization, and perhaps all of them, have wide applicability and can be incorporated into existing translators.

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Section: Compiler Techniquesmentioning

confidence: 99%

Experience in the automatic parallelization of four Perfect-Benchmark programs

Eigenmann

Hoeflinger

et al.

Languages and Compilers for Parallel Computing

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“…Yang and Lebeck [33] present a memory architecture which pro-actively dereferences pointers lower in the hierarchy to push data higher into the memory hierarchy instead of waiting for the higher memory-level to pull the data. While these approaches do improve performance, the linked list pattern remains in the loops which impedes dependence analysis and hence optimizations like concurrentization and vectorization as described by Padua and Wolfe [26] cannot often not be applied.…”

Section: Related Workmentioning

confidence: 99%

A Compile/Run-time Environment for the Automatic Transformation of Linked List Data Structures

Spek

Groot

Bakker

et al. 2008

Int J Parallel Prog

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Irregular access patterns are a major problem for today's optimizing compilers. In this paper, a novel approach will be presented that enables transformations that were designed for regular loop structures to be applied to linked list data structures. This is achieved by linearizing access to a linked list, after which further data restructuring can be performed. Two subsequent optimization paths will be considered: annihilation and sublimation, which are driven by the occurring regular and irregular access patterns in the applications. These intermediate codes are amenable to traditional compiler optimizations targeting regular loops. In the case of sublimation, a run-time step is involved which takes the access pattern into account and thus generates a data instance specific optimized code. Both approaches are applied to a sparse matrix multiplication algorithm and an iterative solver: preconditioned conjugate gradient. The resulting transformed code is evaluated using the major compilers for the x86 platform, GCC and the Intel C compiler.

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“…The same idea can be applied to the vectorization of Matlab code: if many loop iterations can be done independently, a vector of the operands can be supplied to a vector operation instead. The foundation for a vectorizing compiler [2] and techniques to increase the amount of vectorization [19] now appears in textbooks [1,22]. In particular, the dependencebased vectorizer of Allen & Kennedy served as the basis for our vectorizer.…”

Section: Related Workmentioning

confidence: 99%