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acm sigplan Workshop on Memory Systems Performance and Correctness, MSPC 2013, co-located with the 34th annual acm sigplan conference on programming language design and implementation, pldi

作者： Zhang, Dong Ping Jayasena, Nuwan Lyashevsky, Alexander Greathouse, Joseph Meswani, Mitesh Nutter, Mark Ignatowski, Mike Research Group AMD CA United States

ISBN: (纸本)9781450321037

As computation becomes increasingly limited by data movement and energy consumption, exploiting locality throughout the memory hierarchy becomes critical for maintaining the performance scaling that many have come to expect from the computing industry. Moving computation closer to main memory presents an opportunity to reduce the overheads associated with data movement. We explore the potential of using 3D die stacking to move memory-intensive computations closer to memory. This approach to processing-in-memory addresses some drawbacks of prior research on in-memory computing and appears commercially viable in the foreseeable future. We show promising early results from this approach and identify areas that are in need of research to unlock its full potential. © 2013 acm.

关键词： Memory architecture

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Synthesising Graphics Card Programs from DSLs 12

Synthesising Graphics Card Programs from DSLs

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33rd acm sigplan conference on programming language design and implementation

作者： Cartey, Luke Lyngsoe, Rune de Moor, Oege Univ Oxford Oxford OX1 2JD England

ISBN: (纸本)9781450312059

Over the last five years, graphics cards have become a tempting target for scientific computing, thanks to unrivaled peak performance, often producing a runtime speed-up of x10 to x25 over comparable CPU solutions. However, this increase can be difficult to achieve, and doing so often requires a fundamental rethink. This is especially problematic in scientific computing, where experts do not want to learn yet another architecture. In this paper we develop a method for automatically parallelising recursive functions of the sort found in scientific papers. Using a static analysis of the function dependencies we identify sets - partitions - of independent elements, which we use to synthesise an efficient GPU implementation using polyhedral code generation techniques. We then augment our language with DSL extensions to support a wider variety of applications, and demonstrate the effectiveness of this with three case studies, showing significant performance improvement over equivalent CPU methods, and similar efficiency to hand-tuned GPU implementations.

关键词： language Performance gpu scientific applications program synthesis dynamic programming

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implementation of complete, asynchronous, distributed garbage collection

Implementation of complete, asynchronous, distributed garbag...

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Proceedings of the 1998 Annual acm sigplan conference on programming language design and implementation, pldi

作者： Le Fessant, Fabrice Piumarta, Ion Shapiro, Marc INRIA Roquencourt Le Chesnay France

Most existing reference-based distributed object systems include some kind of acyclic garbage collection, but fail to provide acceptable collection of cyclic garbage. Those that do provide such GC currently suffer from one or more problems: synchronous operation, the need for expensive global consensus or termination algorithms, susceptibility to communication problems, or an algorithm that does not scale. We present a simple, complete, fault-tolerant, asynchronous extension to the (acyclic) cleanup protocol of the SSP Chains system. This extension is scalable, consumes few resources, and could easily be adapted to work in other reference-based distributed object systems - rendering them usable for very large-scale applications.

关键词： Computer systems programming

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Associated Effects Flexible Abstractions for Effectful programming

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PROCEEDINGS OF THE acm ON programming languageS-PacmPL 2024年第PLDI期8卷 394-416页

作者： Lutze, Matthew Madsen, Magnus Aarhus Univ Aarhus Denmark

We present associated effects, a programming language feature that enables type classes to abstract over the effects of their function signatures, allowing each type class instance to specify its concrete effects. Associated effects significantly increase the flexibility and expressive power of a programming language that combines a type and effect system with type classes. In particular, associated effects allow us to (i) abstract over total and partial functions, where partial functions may throw exceptions, (ii) abstract over immutable data structures and mutable data structures that have heap effects, and (iii) implement adaptors that combine type classes with algebraic effects. We implement associated effects as an extension of the Flix programming language and refactor the Flix Standard Library to use associated effects, significantly increasing its flexibility and expressive power. Specifically, we add associated effects to 11 type classes, which enables us to add 28 new type class instances.

关键词： effect systems associated effects associated types generic programming type classes type functions ad-hoc polymorphism

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Scalable Verification of Probabilistic Networks 2019

Scalable Verification of Probabilistic Networks

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40th acm sigplan conference on programming language design and implementation (pldi) part of acm's Federated Computing Research conference (FCRC)

作者： Smolka, Steffen Kumar, Praveen Kahn, David M. Foster, Nate Hsu, Justin Kozen, Dexter Silva, Alexandra Cornell Univ Ithaca NY 14850 USA Carnegie Mellon Univ Pittsburgh PA 15213 USA Univ Wisconsin Madison WI USA UCL London England

ISBN: (纸本)9781450367127

This paper presents McNetKAT, a scalable tool for verifying probabilistic network programs. McNetKAT is based on a new semantics for the guarded and history-free fragment of Probabilistic NetKAT in terms of finite-state, absorbing Markov chains. This view allows the semantics of all programs to be computed exactly, enabling construction of an automatic verification tool. Domain-specific optimizations and a parallelizing backend enable McNetKAT to analyze networks with thousands of nodes, automatically reasoning about general properties such as probabilistic program equivalence and refinement, as well as networking properties such as resilience to failures. We evaluate McNetKAT's scalability using real-world topologies, compare its performance against state-of-the-art tools, and develop an extended case study on a recently proposed data center network design.

关键词： Network verification Probabilistic programming

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Thread-modular shape analysis 07

Thread-modular shape analysis

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conference on programming language design and implementation

作者： Gotsman, Alexey Berdine, Josh Cook, Byron Sagiv, Mooly Univ Cambridge Cambridge CB2 1TN England Microsoft Corp Redmond WA 98052 USA

ISBN: (纸本)9781595936332

We present the first shape analysis for multithreaded programs that avoids the explicit enumeration of execution-interleavings. Our approach is to automatically infer a resource invariant associated with each lock that describes the part of the heap protected by the lock. This allows us to use a sequential shape analysis on each thread. We show that resource invariants of a certain class can be characterized as least fixed points and computed via repeated applications of shape analysis only on each individual thread. Based on this approach, we have implemented a thread-modular shape analysis tool and applied it to concurrent heap-manipulating code from Windows device drivers.

关键词： abstract interpretation concurrent programming shape analysis static analysis

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Proceedings of the acm sigplan '92 conference on programming language design and implementation

Proceedings of the ACM SIGPLAN '92 Conference on Programming...

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acm sigplan '92 conference on programming language design and implementation, pldi 1992

This conference contains 30 papers all of which are abstracted and indexed individually. The topics covered are: program debugging techniques;debugging optimized codes;concurrent compilers;abstract machine;false data ... 详细信息

ISBN: (纸本)0897914759

关键词： Computer programming

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Bounded Expectations: Resource Analysis for Probabilistic Programs 2018

Bounded Expectations: Resource Analysis for Probabilistic Pr...

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39th acm sigplan conference on programming language design and implementation (pldi)

作者： Van Chan Ngo Carbonneaux, Quentin Hoffmann, Jan Carnegie Mellon Univ Pittsburgh PA 15213 USA Yale Univ New Haven CT 06520 USA

ISBN: (纸本)9781450356985

This paper presents a new static analysis for deriving upper bounds on the expected resource consumption of probabilistic programs. The analysis is fully automatic and derives symbolic bounds that are multivariate polynomials in the inputs. The new technique combines manual state-of-the-art reasoning techniques for probabilistic programs with an effective method for automatic resource-bound analysis of deterministic programs. It can be seen as both, an extension of automatic amortized resource analysis (AARA) to probabilistic programs and an automation of manual reasoning for probabilistic programs that is based on weakest preconditions. An advantage of the technique is that it combines the clarity and compositionality of a weakest-precondition calculus with the efficient automation of AARA. As a result, bound inference can be reduced to off-the-shelf LP solving in many cases and automatically-derived bounds can be interactively extended with standard program logics if the automation fails. Building on existing work, the soundness of the analysis is proved with respect to an operational semantics that is based on Markov decision processes. The effectiveness of the technique is demonstrated with a prototype implementation that is used to automatically analyze 39 challenging probabilistic programs and randomized algorithms. Experiments indicate that the derived constant factors in the bounds are very precise and even optimal for some programs.

关键词： probabilistic programming resource bound analysis static analysis

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Heartbeat Scheduling: Provable Efficiency for Nested Parallelism 2018

Heartbeat Scheduling: Provable Efficiency for Nested Paralle...

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39th acm sigplan conference on programming language design and implementation (pldi)

作者： Acar, Umut A. Chargueraud, Arthur Guatto, Adrien Rainey, Mike Sieczkowski, Filip Carnegie Mellon Univ Pittsburgh PA 15213 USA INRIA Rocquencourt France Univ Strasbourg ICube Strasbourg France CREST Bloomington IN USA

ISBN: (纸本)9781450356985

A classic problem in parallel computing is to take a high-level parallel program written, for example, in nested-parallel style with fork-join constructs and run it efficiently on a real machine. The problem could be considered solved in theory, but not in practice, because the overheads of creating and managing parallel threads can overwhelm their benefits. Developing efficient parallel codes therefore usually requires extensive tuning and optimizations to reduce parallelism just to a point where the overheads become acceptable. In this paper, we present a scheduling technique that delivers provably efficient results for arbitrary nested-parallel programs, without the tuning needed for controlling parallelism overheads. The basic idea behind our technique is to create threads only at a beat (which we refer to as the "heartbeat") and make sure to do useful work in between. We specify our heartbeat scheduler using an abstract-machine semantics and provide mechanized proofs that the scheduler guarantees low overheads for all nested parallel programs. We present a prototype C++ implementation and an evaluation that shows that Heartbeat competes well with manually optimized Cilk Plus codes, without requiring manual tuning.

关键词： parallel programming languages granularity control

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MAPL 2019 - Proceedings of the 3rd acm sigplan International Workshop on Machine Learning and programming languages, co-located with pldi 2019

MAPL 2019 - Proceedings of the 3rd ACM SIGPLAN International...

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3rd acm sigplan International Workshop on Machine Learning and programming languages, MAPL 2019, co-located with pldi 2019

ISBN: (纸本)9781450367196

The proceedings contain 5 papers. The topics discussed include: machine learning in python with no strings attached;triton: an intermediate language and compiler for tiled neural network computations;HackPPL: a universal probabilistic programming language;neural query expansion for code search;and a case study on machine learning for synthesizing benchmarks.

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