Generic Programming for Scientific Computing in C++, JavaTM, and C#

Gerlach, Jens; Kneis, Joachim

doi:10.1007/978-3-540-39425-9_37

“…It is explicitly designed to allow generic code to achieve performance comparable to that of hand-specialized code [48], a goal that is often achieved [51,35,36,26]. The programming technique we propose makes compile-time polymorphism applicable to a wider range of problems.…”

Section: Related Workmentioning

confidence: 99%

Minimizing dependencies within generic classes for faster and smaller programs

Tsafrir¹,

Wisniewski²,

Bacon³

et al. 2009

Proceedings of the 24th ACM SIGPLAN Conference on Object Oriented Programming Systems Languages and Applications

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Generic classes can be used to improve performance by allowing compile-time polymorphism. But the applicability of compile-time polymorphism is narrower than that of runtime polymorphism, and it might bloat the object code. We advocate a programming principle whereby a generic class should be implemented in a way that minimizes the dependencies between its members (nested types, methods) and its generic type parameters. Conforming to this principle (1) reduces the bloat and (2) gives rise to a previously unconceived manner of using the language that expands the applicability of compile-time polymorphism to a wider range of problems. Our contribution is thus a programming technique that generates faster and smaller programs. We apply our ideas to GCC's STL containers and iterators, and we demonstrate notable speedups and reduction in object code size (real application runs 1.2x to 2.1x faster and STL code is 1x to 25x smaller). We conclude that standard generic APIs (like STL) should be amended to reflect the proposed principle in the interest of efficiency and compactness. Such modifications will not break old code, simply increase flexibility. Our findings apply to languages like C++, C#, and D, which realize generic programming through multiple instantiations.

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“…In summary, generic parallel programming can be conceived as an expansion to the templates concept which provides a method for the automated development or the platform optimization of parallel libraries. Templates have demonstrated an interesting potential in high‐level parallel programming 177, mostly confined to the development of scientific applications 178–180.…”

Section: Related Approachesmentioning

confidence: 99%

A survey of algorithmic skeleton frameworks: high‐level structured parallel programming enablers

González–Vélez

¹

,

Leyton

²

2010

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Structured parallel programs ought to be conceived as two separate and complementary entities: computation, which expresses the calculations in a procedural manner, and coordination, which abstracts the interaction and communication. By abstracting commonly used patterns of parallel computation, communication, and interaction, algorithmic skeletons enable programmers to code algorithms without specifying platform‐dependent primitives. This article presents a literature review on algorithmic skeleton frameworks (ASKF), parallel software development environments furnishing a collection of parameterizable algorithmic skeletons, where the control flow, nesting, resource monitoring, and portability of the resulting parallel program is dictated by the ASKF as opposed to the programmer. Consequently, the ASKF can be positioned as high‐level structured parallel programming enablers, as their systematic utilization permits the abstract description of programs and fosters portability by focusing on the description of the algorithmic structure rather than on its detailed implementation. Copyright © 2010 John Wiley & Sons, Ltd.

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“…It is explicitly designed to allow generic code to achieve performance comparable to that of hand-specialized code [48], a goal that is often achieved [51,35,36,26]. The programming technique we propose makes compile-time polymorphism applicable to a wider range of problems.…”

Section: Related Workmentioning

confidence: 99%

Minimizing dependencies within generic classes for faster and smaller programs

Tsafrir

¹

,

Wisniewski

²

,

Bacon

³

et al. 2009

SIGPLAN Not.

1

0

View full text Add to dashboard Cite

Generic classes can be used to improve performance by allowing compile-time polymorphism. But the applicability of compile-time polymorphism is narrower than that of runtime polymorphism, and it might bloat the object code. We advocate a programming principle whereby a generic class should be implemented in a way that minimizes the dependencies between its members (nested types, methods) and its generic type parameters. Conforming to this principle (1) reduces the bloat and (2) gives rise to a previously unconceived manner of using the language that expands the applicability of compile-time polymorphism to a wider range of problems. Our contribution is thus a programming technique that generates faster and smaller programs. We apply our ideas to GCC's STL containers and iterators, and we demonstrate notable speedups and reduction in object code size (real application runs 1.2x to 2.1x faster and STL code is 1x to 25x smaller). We conclude that standard generic APIs (like STL) should be amended to reflect the proposed principle in the interest of efficiency and compactness. Such modifications will not break old code, simply increase flexibility. Our findings apply to languages like C++, C#, and D, which realize generic programming through multiple instantiations.

show abstract

Generic Programming for Scientific Computing in C++, JavaTM, and C#

Cited by 9 publications

References 3 publications

Minimizing dependencies within generic classes for faster and smaller programs

Minimizing dependencies within generic classes for faster and smaller programs

A survey of algorithmic skeleton frameworks: high‐level structured parallel programming enablers

Minimizing dependencies within generic classes for faster and smaller programs

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