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A Provably TimeEfficient Parallel Implementation of Full Speculation
 In Proceedings of the 23rd ACM Symposium on Principles of Programming Languages
, 1996
"... Speculative evaluation, including leniency and futures, is often used to produce high degrees of parallelism. Existing speculative implementations, however, may serialize computation because of their implementation of queues of suspended threads. We give a provably efficient parallel implementation ..."
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Cited by 17 (5 self)
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Speculative evaluation, including leniency and futures, is often used to produce high degrees of parallelism. Existing speculative implementations, however, may serialize computation because of their implementation of queues of suspended threads. We give a provably efficient parallel implementation of a speculative functional language on various machine models. The implementation includes proper parallelization of the necessary queuing operations on suspended threads. Our target machine models are a butterfly network, hypercube, and PRAM. To prove the efficiency of our implementation, we provide a cost model using a profiling semantics and relate the cost model to implementations on the parallel machine models. 1 Introduction Futures, lenient languages, and several implementations of graph reduction for lazy languages all use speculative evaluation (callbyspeculation [15]) to expose parallelism. The basic idea of speculative evaluation, in this context, is that the evaluation of a...
A Parallel Complexity Model for Functional Languages
 IN: PROC. ACM CONF. ON FUNCTIONAL PROGRAMMING LANGUAGES AND COMPUTER ARCHITECTURE
, 1994
"... A complexity model based on the calculus with an appropriate operational semantics in presented and related to various parallel machine models, including the PRAM and hypercube models. The model is used to study parallel algorithms in the context of "sequential" functional languages, and to relate ..."
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Cited by 5 (2 self)
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A complexity model based on the calculus with an appropriate operational semantics in presented and related to various parallel machine models, including the PRAM and hypercube models. The model is used to study parallel algorithms in the context of "sequential" functional languages, and to relate these results to algorithms designed directly for parallel machine models. For example, the paper shows that equally good upper bounds can be achieved for merging two sorted sequences in the pure calculus with some arithmetic constants as in the EREW PRAM, when they are both mapped onto a more realistic machine such as a hypercube or butterfly network. In particular for n keys and p processors, they both result in an O(n=p + log 2 p) time algorithm. These results argue that it is possible to get good parallelism in functional languages without adding explicitly parallel constructs. In fact, the lack of random access seems to be a bigger problem than the lack of parallelism. This research...
Programming Language Expressiveness and Circuit Complexity
 in: Internat. Conf. on the Mathematical Foundations of Programming Semantics
, 1996
"... This paper is a continuation of the work begun in [5] on establishing relative intensional expressiveness results for programming languages. Language L 1 is intensionally more expressive than L 2 , if L 1 can compute all the functions L 2 can, with at least the same asymptotic complexity. The questi ..."
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Cited by 4 (2 self)
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This paper is a continuation of the work begun in [5] on establishing relative intensional expressiveness results for programming languages. Language L 1 is intensionally more expressive than L 2 , if L 1 can compute all the functions L 2 can, with at least the same asymptotic complexity. The question we address is: Does nondeterministic parallelism add intensional expressiveness? We compare deterministic and nondeterministic extensions of PCF, a simple functional programming language. We develop further the circuit semantics from our earlier work, and establish a connection between parallel PCF programs and boolean circuits. Using results from circuit complexity, and assuming hardware which can detect undefined inputs, we show that nondeterministic parallelism is indeed intensionally more expressive. More precisely, we show that nondeterministic parallelism can lead to exponentially faster programs, and also programs that do exponentially less work. 1 Introduction We conduct an inves...