Leaking Space

Mitchell, Neil E.

doi:10.1145/2538031.2538488

Cited by 4 publications

(1 citation statement)

References 6 publications

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“…The term was first coined in Reference 24 in the context of functional programming to refer to applications that do release the allocated memory, but later than the developer expects. Since then, researchers have revisited space leaks for different languages (e.g., Haskell in Reference 25, or Java for embedded applications in Reference 26). Space leaks are a type of memory allocation anomaly, and our method can detect and fix them, together with other anomalies.…”

Section: Background and Related Work On Memory Anomaliesmentioning

confidence: 99%

Memory allocation anomalies in high‐performance computing applications: A study with numerical simulations

Gomes

Molion

Souto

et al. 2020

Concurrency and Computation

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Summary A memory allocation anomaly occurs when the allocation of a set of heap blocks imposes an unnecessary overhead on the execution of an application. This overhead is particularly disturbing for high‐performance computing (HPC) applications running on shared resources—for example, numerical simulations running on clusters or clouds—because it may increase either the execution time of the application (contributing to a reduction on the overall efficiency of the shared resource) or its memory consumption (eventually inhibiting its capacity to handle larger problems). In this article, we propose a method for identifying, locating, characterizing and fixing allocation anomalies, and a tool for developers to apply the method. We experiment our method and tool with a numerical simulator aimed at approximating the solutions to partial differential equations using a finite element method. We show that taming allocation anomalies in this simulator reduces both its execution time and the memory footprint of its processes, irrespective of the specific heap allocator being employed with it. We conclude that the developer of HPC applications can benefit from the method and tool during the software development cycle.

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Section: Background and Related Work On Memory Anomaliesmentioning

confidence: 99%

Memory allocation anomalies in high‐performance computing applications: A study with numerical simulations

Gomes

Molion

Souto

et al. 2020

Concurrency and Computation

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Autobahn: using genetic algorithms to infer strictness annotations

Wang

Nunez

Fisher

2016

Proceedings of the 9th International Symposium on Haskell

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Although laziness enables beautiful code, it comes with non-trivial performance costs. The ghc compiler for Haskell has optimizations to reduce those costs, but the optimizations are not sufficient. As a result, Haskell also provides a variety of strictness annotations so that users can indicate program points where an expression should be evaluated eagerly. Skillful use of those annotations is a black art, known only to expert Haskell programmers. In this paper, we introduce AUTOBAHN, a tool that uses genetic algorithms to automatically infer strictness annotations that improve program performance on representative inputs. Users examine the suggested annotations for soundness and can instruct AUTOBAHN to automatically produce modified sources. Experiments on 60 programs from the NoFib benchmark suite show that AUTOBAHN can infer annotation sets that improve runtime performance by a geometric mean of 8.5%. Case studies show AUTOBAHN can reduce the live size of a GC simulator by 99% and infer application-specific annotations for Aeson library code. A 10-fold cross-validation study shows the AUTOBAHN-optimized GC simulator generally outperforms a version optimized by an expert.

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Versatile event correlation with algebraic effects

Bračevac

Amin

Salvaneschi

et al. 2018

Proc. ACM Program. Lang.

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We present the first language design to uniformly express variants of n-way joins over asynchronous event streams from different domains, e.g., stream-relational algebra, event processing, reactive and concurrent programming. We model asynchronous reactive programs and joins in direct style, on top of algebraic effects and handlers. Effect handlers act as modular interpreters of event notifications, enabling fine-grained control abstractions and customizable event matching. Join variants can be considered as cartesian product computations with łdegeneratež control flow, such that unnecessary tuples are not materialized a priori. Based on this computational interpretation, we decompose joins into a generic, naïve enumeration procedure of the cartesian product, plus variant-specific extensions, represented in terms of user-supplied effect handlers. Our microbenchmarks validate that this extensible design avoids needless materialization. Alongside a formal semantics for joining and prototypes in Koka and multicore OCaml, we contribute a systematic comparison of the covered domains and features.

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Leaking Space

Cited by 4 publications

References 6 publications

Memory allocation anomalies in high‐performance computing applications: A study with numerical simulations

Memory allocation anomalies in high‐performance computing applications: A study with numerical simulations

Autobahn: using genetic algorithms to infer strictness annotations

Versatile event correlation with algebraic effects

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