Techniques for the translation of MATLAB programs into Fortran 90

Rose, Luiz De; Padua, David

doi:10.1145/316686.316693

Cited by 75 publications

(61 citation statements)

References 13 publications

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“…Our framework requires that all the processors participating in the system have a copy of MATLAB TM and the HTA toolbox. Since MATLAB TM is interpreted, our library-based implementation suffers from the overheads that a compiler could easily remove [3,19]. Our approach presents programmers a global view of the code.…”

Section: Methodsmentioning

confidence: 99%

Hierarchically tiled arrays for parallelism and locality

Guo¹,

Bikshandi²,

Hoeflinger³

et al. 2006

Proceedings 20th IEEE International Parallel &Amp; Distributed Processing Symposium

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Parallel programming is facilitated by constructs which, unlike the widely used SPMD paradigm, provide programmers with a global view of the code and data structures. These constructs could be compiler directives containing information about data and task distribution, language extensions specifically designed for parallel computation, or classes that encapsulate parallelism. In this paper, we describe a class developed at Illinois and its MATLAB implementation. This class can be used to conveniently express both parallelism and locality. A C++ implementation is now underway. Its characteristics will be reported in a future paper. We have implemented most of the NAS benchmarks using our HTA MATLAB extensions and found during that HTAs enable the fast prototyping of parallel algorithms and produce programs that are easy to understand and maintain.

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Section: Methodsmentioning

confidence: 99%

Hierarchically tiled arrays for parallelism and locality

Guo¹,

Bikshandi²,

Hoeflinger³

et al. 2006

Proceedings 20th IEEE International Parallel &Amp; Distributed Processing Symposium

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show abstract

“…For example, FALCON [14] is a Matlab to Fortran90 translator with sophisticated type inference algorithms. The McLab group has previously implemented a prototype Fortran 95 generator [10], and is developing the next generation Fortran generator in parallel with the MiX10 project.…”

Section: Related Workmentioning

confidence: 99%

First steps to compiling Matlab to X10

Kumar

Hendren

2013

Proceedings of the Third ACM SIGPLAN X10 Workshop

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Matlab is a popular dynamic array-based language commonly used by students, scientists and engineers, who appreciate the interactive development style, the rich set of array operators, the extensive builtin library, and the fact that they do not have to declare static types. Even though these users like to program in Matlab, their computations are often very computeintensive and are potentially very good applications for high-performance languages such as X10.To provide a bridge between Matlab and X10, we are developing MiX10, a source-tosource compiler that translates Matlab to X10. This paper provides an overview of the initial design of the MiX10 compiler, presents a template-based specialization approach to compiling the builtin Matlab operators, and provides translation rules for the key sequential Matlab constructs with a focus on those which are challenging to convert to semantically-equivalent X10. An initial core compiler has been implemented, and preliminary results are provided.

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“…Such generators follow an iterative optimization scheme. Most optimizations performed by these generators are classical loop transformations; some of them involve domain knowledge, from the specialization and interprocedural optimization of library functions [3,8], to application-specific optimizations such as algorithm selection [17]. Recently, the SPIRAL project [21] pioneered the extension of this application-specific approach to a whole domain of programs: digital signal processing.…”

Section: Related Workmentioning

confidence: 99%

A Language for the Compact Representation of Multiple Program Versions

Donadio

Brodman

Roeder

et al. 2006

Languages and Compilers for Parallel Computing

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Abstract. As processor complexity increases compilers tend to deliver suboptimal performance. Library generators such as ATLAS, FFTW and SPIRAL overcome this issue by empirically searching in the space of possible program versions for the one that performs the best. Empirical search can also be applied by programmers, but because they lack a tool to automate the process, programmers need to manually re-write the application in terms of several parameters whose best value will be determined by the empirical search in the target machine. In this paper, we present the design of an annotation language, meant to be used either as an intermediate representation within library generators or directly by the programmer. This language that we call X represents parameterized programs in a compact and natural way. It provides an powerful optimization framework for high performance computing.

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Techniques for the translation of MATLAB programs into Fortran 90

Cited by 75 publications

References 13 publications

Hierarchically tiled arrays for parallelism and locality

Hierarchically tiled arrays for parallelism and locality

First steps to compiling Matlab to X10

A Language for the Compact Representation of Multiple Program Versions

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