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Parallel Programming using Functional Languages
, 1991
"... I am greatly indebted to Simon Peyton Jones, my supervisor, for his encouragement and technical assistance. His overwhelming enthusiasm was of great support to me. I particularly want to thank Simon and Geoff Burn for commenting on earlier drafts of this thesis. Through his excellent lecturing Cohn ..."
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Cited by 49 (3 self)
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I am greatly indebted to Simon Peyton Jones, my supervisor, for his encouragement and technical assistance. His overwhelming enthusiasm was of great support to me. I particularly want to thank Simon and Geoff Burn for commenting on earlier drafts of this thesis. Through his excellent lecturing Cohn Runciman initiated my interest in functional programming. I am grateful to Phil Trinder for his simulator, on which mine is based, and Will Partain for his help with LaTex and graphs. I would like to thank the Science and Engineering Research Council of Great Britain for their financial support. Finally, I would like to thank Michelle, whose culinary skills supported me whilst I was writingup.The Imagination the only nation worth defending a nation without alienation a nation whose flag is invisible and whose borders are forever beyond the horizon a nation whose motto is why have one or the other when you can have one the other and both
Complexity Analysis for a Lazy HigherOrder Language
 In Proceedings of the 3rd European Symposium on Programming
, 1990
"... This paper is concerned with the timeanalysis of functional programs. Techniques which enable us to reason formally about a program's execution costs have had relatively little attention in the study of functional programming. We concentrate here on the construction of equations which compu ..."
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Cited by 47 (2 self)
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This paper is concerned with the timeanalysis of functional programs. Techniques which enable us to reason formally about a program's execution costs have had relatively little attention in the study of functional programming. We concentrate here on the construction of equations which compute the timecomplexity of expressions in a lazy higherorder language. The problem with higherorder functions is that complexity is dependent on the cost of applying functional parameters. Structures called costclosures are introduced to allow us to model both functional parameters and the cost of their application. The problem with laziness is that complexity is dependent on context. Projections are used to characterise the context in which an expression is evaluated, and costequations are parameterised by this contextdescription to give a compositional timeanalysis. Using this form of context information we introduce two types of timeequation: sufficienttime equations and nece...
Static dependent costs for estimating execution time
 In Proc. of the 1994 ACM Conference on LISP and functional programming
, 1994
"... We present the first system for estimating and using datadependent expression execution times in a language with firstclass procedures and imperative constructs. Thepresence of firstclass procedures and imperative constructs makes cost estimation a global problem that can benefit from type informa ..."
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Cited by 46 (0 self)
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We present the first system for estimating and using datadependent expression execution times in a language with firstclass procedures and imperative constructs. Thepresence of firstclass procedures and imperative constructs makes cost estimation a global problem that can benefit from type information. We estimate expression costs with the aid of an algebraic type reconstruction system that assigns every procedure atype that includes a static dependent cost. A static dependent cost describes the execution time of a procedure in terms of its inputs. In particular, a procedure’s static dependent cost can depend on the size of input data structures and the cost of input firstclass procedures. Our cost system produces symbolic cost expressions that contain free variables describing the size and cost of the procedure’s inputs. At runtime, a cost estimate is dynamically computed from the statically determined cost expression and runtime cost and size information. We present experimental results that validate our cost system onthreecompilers and architectures. We experimentally demonstrate the utility of cost estimates in making dynamic parallelization decisions. In our experience, dynamic parallelization meets or exceeds the parallel performance of any fixed number of processors. 1
A Naïve Time Analysis and its Theory of Cost Equivalence
 Journal of Logic and Computation
, 1995
"... Techniques for reasoning about extensional properties of functional programs are well understood, but methods for analysing the underlying intensional or operational properties have been much neglected. This paper begins with the development of a simple but useful calculus for time analysis of nons ..."
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Cited by 39 (7 self)
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Techniques for reasoning about extensional properties of functional programs are well understood, but methods for analysing the underlying intensional or operational properties have been much neglected. This paper begins with the development of a simple but useful calculus for time analysis of nonstrict functional programs with lazy lists. One limitation of this basic calculus is that the ordinary equational reasoning on functional programs is not valid. In order to buy back some of these equational properties we develop a nonstandard operational equivalence relation called cost equivalence, by considering the number of computation steps as an `observable' component of the evaluation process. We define this relation by analogy with Park's definition of bisimulation in CCS. This formulation allows us to show that cost equivalence is a contextual congruence (and thus is substitutive with respect to the basic calculus) and provides useful proof techniques for establishing costequivalen...
Introducing Parallelism in a Lazy Functional Language
, 1997
"... Interpretation  Combinator Systems . . . . . . . . 13 2.2.6 Backward Analysis . . . . . . . . . . . . . . . . . . . . . . . . 14 2.2.7 Evaluation transformers . . . . . . . . . . . . . . . . . . . . . 18 2.3 Granularity of Parallelism . . . . . . . . . . . . . . . . . . . . . . . . 20 2.3.1 Serial ..."
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Interpretation  Combinator Systems . . . . . . . . 13 2.2.6 Backward Analysis . . . . . . . . . . . . . . . . . . . . . . . . 14 2.2.7 Evaluation transformers . . . . . . . . . . . . . . . . . . . . . 18 2.3 Granularity of Parallelism . . . . . . . . . . . . . . . . . . . . . . . . 20 2.3.1 Serial Combinators . . . . . . . . . . . . . . . . . . . . . . . . 20 2.3.2 Complexity Analysis . . . . . . . . . . . . . . . . . . . . . . . 21 2.3.3 Strictness Analysis Applied to Time Analysis . . . . . . . . . 21 2.3.4 Using Type Information to Derive Time Information . . . . . 25 2.4 Parallel Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.4.1 HBCPP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.4.2 GranSim . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 2.5 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . 30 2.5.1 Strictness Analysis . . . . . . . . . . . . . . . . . . . . . . . . 30 2.5.2 Granularity Analysis . . ...