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2014 ACM International conference on object-oriented-programming-systems-languages-and-applications (oopsla 14)

作者： Bosboom, Jeffrey Rajadurai, Sumanaruban Wong, Weng-Fai Amarasinghe, Saman MIT CSAIL Cambridge MA 02139 USA Natl Univ Singapore Singapore 117548 Singapore

ISBN: (纸本)9781450325851

There are many domain libraries, but despite the performance benefits of compilation, domain-specific languages are comparatively rare due to the high cost of implementing an optimizing compiler. We propose commensal compilation, a new strategy for compiling embedded domain-specific languages by reusing the massive investment in modern language virtual machine platforms. Commensal compilers use the host language's front-end, use host platform APIs that enable back-end optimizations by the host platform JIT, and use an autotuner for optimization selection. The cost of implementing a commensal compiler is only the cost of implementing the domain-specific optimizations. We demonstrate the concept by implementing a commensal compiler for the stream programming language StreamJIT atop the Java platform. Our compiler achieves performance 2.8 times better than the StreamIt native code (via GCC) compiler with considerably less implementation effort.

关键词： Domain-specific languages embedded domain-specific languages

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Performance Problems You Can Fix: A Dynamic Analysis of Memoization Opportunities

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ACM SIGPLAN NOTICES 2015年第10期50卷 607-622页

作者： Della Toffola, Luca Pradel, Michael Gross, Thomas R. Swiss Fed Inst Technol Dept Comp Sci Zurich Switzerland Tech Univ Darmstadt Dept Comp Sci Darmstadt Germany

Performance bugs are a prevalent problem and recent research proposes various techniques to identify such bugs. This paper addresses a kind of performance problem that often is easy to address but difficult to identify: redundant computations that may be avoided by reusing already computed results for particular inputs, a technique called memoization. To help developers find and use memoization opportunities, we present MemoizeIt, a dynamic analysis that identifies methods that repeatedly perform the same computation. The key idea is to compare inputs and outputs of method calls in a scalable yet precise way. To avoid the overhead of comparing objects at all method invocations in detail, MemoizeIt first compares objects without following any references and iteratively increases the depth of exploration while shrinking the set of considered methods. After each iteration, the approach ignores methods that cannot benefit from memoization, allowing it to analyze calls to the remaining methods in more detail. For every memoization opportunity that MemoizeIt detects, it provides hints on how to implement memoization, making it easy for the developer to fix the performance issue. Applying MemoizeIt to eleven real-world Java programs reveals nine profitable memoization opportunities, most of which are missed by traditional CPU time profilers, conservative compiler optimizations, and other existing approaches for finding performance bugs. Adding memoization as proposed by MemoizeIt leads to statistically significant speedups by factors between 1.04x and 12.93x.

关键词： Algorithms Experimentation languages Performance Measurement Memoization caching profiling performance bugs

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Accelerating Iterators in Optimizing AST Interpreters 14

Accelerating Iterators in Optimizing AST Interpreters

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2014 ACM International conference on object-oriented-programming-systems-languages-and-applications (oopsla 14)

作者： Zhang, Wei Larsen, Per Brunthaler, Stefan Franz, Michael Univ Calif Irvine Irvine CA 92697 USA

ISBN: (纸本)9781450325851

Generators offer an elegant way to express iterators. However, performance has always been their Achilles heel and has prevented widespread adoption. We present techniques to efficiently implement and optimize generators. We have implemented our optimizations in ZipPy, a modern, light-weight AST interpreter based Python 3 implementation targeting the Java virtual machine. Our implementation builds on a framework that optimizes AST interpreters using just-in-time compilation. In such a system, it is crucial that AST optimizations do not prevent subsequent optimizations. Our system was carefully designed to avoid this problem. We report an average speedup of 3.58 x for generator-bound programs. As a result, using generators no longer has downsides and programmers are free to enjoy their upsides.

关键词： languages Performance generator iterator dynamic languages optimization Python

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Staged Parser Combinators for Efficient Data Processing

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ACM SIGPLAN NOTICES 2014年第10期49卷 637-653页

作者： Jonnalagedda, Manohar Coppey, Thierry Stucki, Sandro Rompf, Tiark Odersky, Martin EPFL LAMP Zurich Switzerland EPFL DATA Zurich Switzerland

Parsers are ubiquitous in computing, and many applications depend on their performance for decoding data efficiently. Parser combinators are an intuitive tool for writing parsers: tight integration with the host language enables grammar specifications to be interleaved with processing of parse results. Unfortunately, parser combinators are typically slow due to the high overhead of the host language abstraction mechanisms that enable composition. We present a technique for eliminating such overhead. We use staging, a form of runtime code generation, to dissociate input parsing from parser composition, and eliminate intermediate data structures and computations associated with parser composition at staging time. A key challenge is to maintain support for input dependent grammars, which have no clear stage distinction. Our approach applies to top-down recursive-descent parsers as well as bottom-up nondeterministic parsers with key applications in dynamic programming on sequences, where we auto-generate code for parallel hardware. We achieve performance comparable to specialized, hand-written parsers.

关键词： Parser combinators multi-stage programming algebraic dynamic programming

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Alembic: Automatic Locality Extraction via Migration 14

Alembic: Automatic Locality Extraction via Migration

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2014 ACM International conference on object-oriented-programming-systems-languages-and-applications (oopsla 14)

作者： Holt, Brandon Briggs, Preston Ceze, Luis Oskin, Mark Univ Washington Seattle WA 98195 USA

ISBN: (纸本)9781450325851

Partitioned Global Address Space (PGAS) environments simplify writing parallel code for clusters because they make data movement implicit - dereferencing global pointers automatically moves data around. However, it does not free the programmer from needing to reason about locality - poor placement of data can lead to excessive and even unnecessary communication. For this reason, modern PGAS languages such as X10, Chapel, and UPC allow programmers to express data-layout constraints and explicitly move computation. This places an extra burden on the programmer, and is less effective for applications with limited or data-dependent locality (e.g., graph analytics). This paper proposes Alembic, a new static analysis that frees programmers from having to manually move computation to exploit locality in PGAS programs. It works by determining regions of code that access the same cluster node, then transforming the code to migrate parts of the execution to increase the proportion of accesses to local data. We implement the analysis and transformation for C++ in LLVM and show that in irregular application kernels, Alembic can achieve 82% of the performance of hand-tuned communication (for comparison, naive compiler-generated communication achieves only 13%).

关键词： Compilers Distributed systems languages PGAS LLVM Locality Thread migration Continuation-passing style

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ShamDroid: Gracefully Degrading Functionality in the Presence of Limited Resource Access

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ACM SIGPLAN NOTICES 2015年第10期50卷 316-331页

作者： Brutschy, Lucas Ferrara, Pietro Tripp, Omer Pistoia, Marco Swiss Fed Inst Technol Dept Comp Sci Zurich Switzerland IBM Thomas J Watson Res Ctr Yorktown Hts NY USA

Given a program whose functionality depends on access to certain external resources, we investigate the question of how to gracefully degrade functionality when a subset of those resources is unavailable. The concrete setting motivating this problem statement is mobile applications, which rely on contextual data (e.g., device identifiers, user location and contacts, etc.) to fulfill their functionality. In particular, we focus on the Android platform, which mediates access to resources via an installation-time permission model. On the one hand, granting an app the permission to access a resource (e.g., the device ID) entails privacy threats (e.g., releasing the device ID to advertising servers). On the other hand, denying access to a resource could render the app useless (e.g., if inability to read the device ID is treated as an error state). Our goal is to specialize an existing Android app in such a way that it is disabled from accessing certain sensitive resources (or contextual data) as specified by the user, while still being able to execute functionality that does not depend on those resources. We present SHAMDROID, a program transformation algorithm, based on specialized forms of program slicing, backwards static analysis and constraint solving, that enables the use of Android apps with partial permissions. We rigorously state the guarantees provided by SHAMDROID w.r.t. functionality maximization. We provide an evaluation over the top 500 Google Play apps and report on an extensive comparative evaluation of SHAMDROID against three other state-of-theart solutions (APM, XPrivacy, and Google App Ops) that mediate resource access at the system (rather than app) level. SHAMDROID performs better than all of these tools by a significant margin, leading to abnormal behavior in only 1 out of 27 apps we manually investigated, compared to the other solutions, which cause crashes and abnormalities in 9 or more of the apps. This demonstrates the importance of performing a

关键词： Security Verification Static Program Analysis Android applications Privacy

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The HipHop Virtual Machine 14

The HipHop Virtual Machine

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2014 ACM International conference on object-oriented-programming-systems-languages-and-applications (oopsla 14)

作者： Adams, Keith Evans, Jason Maher, Bertrand Ottoni, Guilherme Paroski, Andrew Simmers, Brett Smith, Edwin Yamauchi, Owen Facebook Cambridge MA USA

ISBN: (纸本)9781450325851

The HipHop Virtual Machine (HHVM) is a JIT compiler and runtime for PHP. While PHP values are dynamically typed, real programs often have latent types that are useful for optimization once discovered. Some types can be proven through static analysis, but limitations in the ahead-of-time approach leave some types to be discovered at run time. And even though many values have latent types, PHP programs can also contain polymorphic variables and expressions, which must be handled without catastrophic slow-down. HHVM discovers latent types by structuring its JIT around the concept of a tracelet. A tracelet is approximately a basic block specialized for a particular set of run-time types for its input values. Tracelets allow HHVM to exactly and efficiently learn the types observed by the program, while using a simple compiler. This paper shows that this approach enables HHVM to achieve high levels of performance, without sacrificing compatibility or interactivity.

关键词： Design languages Performance PHP dynamic languages JIT compiler tracelet

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Determinacy in Static Analysis for jQuery 14

Determinacy in Static Analysis for jQuery

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2014 ACM International conference on object-oriented-programming-systems-languages-and-applications (oopsla 14)

作者： Andreasen, Esben Moller, Anders Aarhus Univ DK-8000 Aarhus C Denmark

ISBN: (纸本)9781450325851

Static analysis for JavaScript can potentially help programmers find errors early during development. Although much progress has been made on analysis techniques, a major obstacle is the prevalence of libraries, in particular jQuery, which apply programming patterns that have detrimental consequences on the analysis precision and performance. Previous work on dynamic determinacy analysis has demonstrated how information about program expressions that always resolve to a fixed value in some call context may lead to significant scalability improvements of static analysis for such code. We present a static dataflow analysis for JavaScript that infers and exploits determinacy information on-the-fly, to enable analysis of some of the most complex parts of jQuery. The analysis combines selective context and path sensitivity, constant propagation, and branch pruning, based on a systematic investigation of the main causes of analysis imprecision when using a more basic analysis. The techniques are implemented in the TAJS analysis tool and evaluated on a collection of small programs that use jQuery. Our results show that the proposed analysis techniques boost both precision and performance, specifically for inferring type information and call graphs.

关键词： languages Algorithms Verification JavaScript program analysis

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The HipHop Virtual Machine

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ACM SIGPLAN NOTICES 2014年第10期49卷 777-790页

作者： Adams, Keith Evans, Jason Maher, Bertrand Ottoni, Guilherme Paroski, Andrew Simmers, Brett Smith, Edwin Yamauchi, Owen Facebook Cambridge MA USA

关键词： Design languages Performance PHP dynamic languages JIT compiler tracelet

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Accelerating Iterators in Optimizing AST Interpreters

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ACM SIGPLAN NOTICES 2014年第10期49卷 727-743页

作者： Zhang, Wei Larsen, Per Brunthaler, Stefan Franz, Michael Univ Calif Irvine Irvine CA 92697 USA

关键词： languages Performance generator iterator dynamic languages optimization Python

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