Statistics on graph reduction of SASL programs

Hartel, Pieter H.; Veen, Arthur H.

doi:10.1002/spe.4380180305

Cited by 20 publications

(5 citation statements)

References 13 publications

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“…A more recent study with similar aims, but for the Standard ML of New Jersey system, is described in Stefanovic and Moss (1994). Hartel and Veen (1988) used an instrumented SASL interpreter to study the characteristics of intermediate combinator graphs during reduction. Their method too was to 'analyse the graph at regular intervals'.…”

Section: Gains From Improved Compilation Rulesmentioning

confidence: 99%

New dimensions in heap profiling

Runciman

Röjemo

1996

J. Funct. Prog.

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First-generation heap profilers for lazy functional languages have proved to be effective tools for locating some kinds of space faults, but in other cases they cannot provide sufficient information to solve the problem. This paper describes the design, implementation and use of a new profiler that goes beyond the two-dimensional ‘who produces what’ view of heap cells to provide information about their more dynamic and structural attributes. Specifically, the new profiler can distinguish between cells according to their eventual lifetime, or on the basis of the closure retainers by virtue of which they remain part of the live heap. A bootstrapping Haskell compiler (nhc) hosts the implementation: among examples of the profiler's use we include self-application to nhc. Another example is the original heap-profiling case study clausify, which now consumes even less memory and is much faster.

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Section: Gains From Improved Compilation Rulesmentioning

confidence: 99%

New dimensions in heap profiling

Runciman

Röjemo

1996

J. Funct. Prog.

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“…Some experiments have been performed with the compiler to assess the performance of the method. The benchmark programs are the result of collecting performance data on implementations of functional programming languages 35,36]. The programs used are:…”

Section: Runtime Performancementioning

confidence: 99%

“…A more detailed description of the run-time organisation than we have described here may be found in our paper 31], where we also argue that the statistic that provides the best indication for the quality of our method is the number of cell claims made. Table 2 shows the cell claims (as reported in our other papers 35,36]) witnessed by Turner's standard combinator reduction machine 18], an early version of Johnsson's G-machine 34] and the C code produced by the ow graph compiler. The numbers apply to evaluation only; the cell claims required to build the initial expressions are not included.…”

Section: Runtime Performancementioning

confidence: 99%

Compilation of functional languages using flow graph analysis

1994

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A system based on the notion of a ow graph is used to formally specify and to implement a compiler for a lazy functional language. The compiler takes a simple functional language as input and generates C. The generated C program can then be compiled, and loaded with an extensive run-time system to provide the facility to experiment with di erent analysis techniques. The compiler provides a single, uni ed, e cient, formal framework for all the analysis and synthesis phases, including the generation of C. Many of the standard techniques, such as strictness and boxing analyses, have been included.

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“…We have already noted that other heap attributes, apart from statically determined properties of individual cells, may be of interest to functional programmers. Hartel and Veen (1988), for example, studied the life-times of cells and the lengths of application chains. Indeed, one could profile all kinds of structural properties of the heap, but it is not obvious which properties to choose or what structural information would best serve the aim of reducing computational costs.…”

Section: Related Workmentioning

confidence: 99%

Heap profiling of lazy functional programs

Runciman¹,

Wakeling²

1993

J. Funct. Prog.

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We describe the design, implementation and use of a new kind of profiling tool that yields valuable information about the memory use of lazy functional programs. The tool has two parts: a modified functional language implementation which generates profiling information during the execution of programs, and a separate program which converts this information to graphical form. With the aid of profile graphs, one can make alterations to a functional program which dramatically reduce its space consumption. We demonstrate this in the case of a genuine example -the first to which the tool was applied -for which the results are strikingly successful. Capsule reviewProfiling technology for lazy functional programs is long overdue. Runciman and Wakeling have produced a practical and useful tool, notably because it works in the context of a fullyfledged compiler. Their work highlights the lack of information we have about the dynamic behaviour of lazy functional programs and the potential performance improvements which may be possible given profiling tools to provide us with it. This paper opens up new areas of practical research designing and building such tools.Runciman and Wakeling have started this work with the design and implementation of a heap profiling tool. They place considerable emphasis on the design of an appropriate graphical presentation of the large quantity of profiling data produced. It is interesting that they profile space and not time; ideally one would like both. An upper bound on execution time improvements from improving space behaviour is the garbage collection and paging time. However, they found that the task of fixing space bugs does sometimes lead to beneficial algorithmic changes too.We await with interest the continued development of practical profiling tools for lazy functional programs.

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Statistics on graph reduction of SASL programs

Cited by 20 publications

References 13 publications

New dimensions in heap profiling

New dimensions in heap profiling

Compilation of functional languages using flow graph analysis

Heap profiling of lazy functional programs

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