Data parallel implementation of extensible sparse functional arrays

O'Donnell, John T.

doi:10.1007/3-540-56891-3_6

Cited by 5 publications

(2 citation statements)

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“…Parts of the ESFA algorithm were presented in 1993 [10]. This paper briefly reviews the earlier work, and goes on to make several new contributions: operations and algorithms for memory management, correctness proofs of key parts of the system, specification of the hardware as well as software, an analysis of the complexity, specification of the operations to support sparse and extensible ar-rays, a discussion of applications, and executable implementations of the algorithm and a simulator for the hardware.…”

Section: Introductionmentioning

confidence: 99%

Extensible sparse functional arrays with circuit parallelism

O'Donnell

2015

Science of Computer Programming

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A longstanding open question in algorithms and data structures is the time and space complexity of pure functional arrays. Imperative arrays provide update and lookup operations that require constant time in the RAM theoretical model, but it is conjectured that there does not exist a RAM algorithm that achieves the same complexity for functional arrays, unless restrictions are placed on the operations. The main result of this paper is an algorithm that does achieve optimal unit time and space complexity for update and lookup on functional arrays. This algorithm does not run on a RAM, but instead it exploits the massive parallelism inherent in digital circuits. The algorithm also provides unit time operations that support storage management, as well as sparse and extensible arrays. The main idea behind the algorithm is to replace a RAM memory by a tree circuit that is more powerful than the RAM yet has the same asymptotic complexity in time (gate delays) and size (number of components). The algorithm uses an array representation that allows elements to be shared between many arrays with only a small constant factor penalty in space and time. This system exemplifies circuit parallelism, which exploits very large numbers of transistors per chip in order to speed up key algorithms. Extensible Sparse Functional Arrays (ESFA) can be used with both functional and imperative programming languages. The system comprises a set of algorithms and a circuit specification, and it has been implemented on a GPGPU with good performance.

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Section: Introductionmentioning

confidence: 99%

Extensible sparse functional arrays with circuit parallelism

O'Donnell

2015

Science of Computer Programming

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“…Toward this direction, there are several relevant recent approaches for functional data-parallel programming. O'Donnell (1993) has shown that a flexible array structure, extensible sparse functional arrays, can be efficiently implemented on massively parallel computers. Misra (1994) has shown that many data-parallel algorithms can be expressed as a recursion of data-parallel operations on a specific data structure called powerlist, which is a list constructed by concatenating two lists of the same length.…”

Section: Introductionmentioning

confidence: 99%

Parallel functional programming on recursively defined data via data-parallel recursion

Nishimura

Ohori

1999

J. Funct. Prog.

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This article proposes a new language mechanism for data-parallel processing of dynamically allocated recursively defined data. Different from the conventional array-based data- parallelism, it allows parallel processing of general recursively defined data such as lists or trees in a functional way. This is achieved by representing a recursively defined datum as a system of equations, and defining new language constructs for parallel transformation of a system of equations. By integrating them with a higher-order functional language, we obtain a functional programming language suitable for describing data-parallel algorithms on recursively defined data in a declarative way. The language has an ML style polymorphic type system and a type sound operational semantics that uniformly integrates the parallel evaluation mechanism with the semantics of a typed functional language. We also show the intended parallel execution model behind the formal semantics, assuming an idealized distributed memory multicomputer.

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The aim is laziness in a data-parallel language

Hill

1994

Workshops in Computing

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Data parallel implementation of extensible sparse functional arrays

Cited by 5 publications

References 3 publications

Extensible sparse functional arrays with circuit parallelism

Extensible sparse functional arrays with circuit parallelism

Parallel functional programming on recursively defined data via data-parallel recursion

The aim is laziness in a data-parallel language

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