An Environment for Analyzing Space Optimizations in Call-by-Need Functional Languages

Dallmeyer, Nils; Schmidt-Schauß, Manfred

doi:10.4204/eptcs.235.6

Cited by 2 publications

(4 citation statements)

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“…We analyze the space behavior of fold using exclusive-or as function, False as neutral element and a list lst starting with a single True followed by k − 1 False-elements generated using a takefunction/list generator approach. We already compared the three fold variants concerning runtime and space consumption with each other in this scenario in [5], but now we focus on the impact of inlining, i.e. how does inlining affect the space consumption in the same scenario?…”

Section: Figure 9: Experimental Resultsmentioning

confidence: 99%

“…The current version of LRPi uses Peano-encoding for positive integers, but treats arbitrary Peano numbers as of size 1, which makes it is easier to analyze the results. Hence the current statistics differs from that in [5]. The fold-functions are defined in Fig.…”

Section: Figure 9: Experimental Resultsmentioning

confidence: 99%

“…., which are ignored by our space measure. As shown in [5] an evaluation on an abstract machine will really use constant space, if shortening indirections is performed by the abstract machine. Now let s = letrec x = [1.…”

Section: On the Space-safety Of Transformationsmentioning

confidence: 99%

“…Experimental Analysis of Inlining and fold Using the Tool LRPiWe use our interpreter LRPi that executes LRPgc-programs using an abstract machine approach and measures the runtime and space behavior (for more details see[5]) and apply it to several fold-variants.…”

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confidence: 99%

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Space Improvements and Equivalences in a Functional Core Language

Schmidt-Schauß

Dallmeyer

2018

Electron. Proc. Theor. Comput. Sci.

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We explore space improvements in LRP, a polymorphically typed call-by-need functional core language. A relaxed space measure is chosen for the maximal size usage during an evaluation. It abstracts from the details of the implementation via abstract machines, but it takes garbage collection into account and thus can be seen as a realistic approximation of space usage. The results are: a context lemma for space improving translations and for space equivalences; all but one reduction rule of the calculus are shown to be space improvements, and for the exceptional one we show bounds on the space increase. Several further program transformations are shown to be space improvements or space equivalences, in particular the translation into machine expressions is a space equivalence. We also classify certain space-worsening transformations as space-leaks or as space-safe. These results are a step forward in making predictions about the change in runtime space behavior of optimizing transformations in call-by-need functional languages. * supported by the Deutsche Forschungsgemeinschaft (DFG) under grant SCHM 986/11-1.

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Section: Figure 9: Experimental Resultsmentioning

confidence: 99%

Section: Figure 9: Experimental Resultsmentioning

confidence: 99%

Section: On the Space-safety Of Transformationsmentioning

confidence: 99%

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confidence: 99%

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