We describe the design and implementation of Dynamo, a software dynamic optimization system that is capable of transparently improving the performance of a native instruction stream as it executes on the processor. Th...
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We describe the design and implementation of Dynamo, a software dynamic optimization system that is capable of transparently improving the performance of a native instruction stream as it executes on the processor. The input native instruction stream to Dynamo can be dynamically generated (by a JIT for example), or it can come from the execution of a statically compiled native binary. This paper evaluates the Dynamo system in the latter, more challenging situation, in order to emphasize the limits, rather than the potential, of the system. Our experiments demonstrate that even statically optimized native binaries can be accelerated Dynamo, and often by a significant degree. For example, the average performance of -O optimized SpecInt95 benchmark binaries created by the HP product C compiler is improved to a level comparable to their -O4 optimized version running without Dynamo. Dynamo achieves this by focusing its efforts on optimization opportunities that tend to manifest only at runtime, and hence opportunities that might be difficult for a static compiler to exploit. Dynamo's operation is transparent in the sense that it does not depend on any user annotations or binary instrumentation, and does not require multiple runs, or any special compiler, operating system or hardware support. The Dynamo prototype presented here is a realistic implementation running on an HP PA-8000 workstation under the HPUX 10.20 operating system.
Concurrent garbage collection is highly attractive for real-time systems, because offloading the collection effort from the executing threads allows faster response, allowing for extremely short deadlines at the micro...
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ISBN:
(纸本)9781595938602
Concurrent garbage collection is highly attractive for real-time systems, because offloading the collection effort from the executing threads allows faster response, allowing for extremely short deadlines at the microseconds level. Concurrent collectors also offer much better scalability over incremental collectors. The main problem with concurrent real-time collectors is their complexity. The first concurrent real-time garbage collector that can support fine synchronization, STOPLESS, has recently been presented by Pizlo et al. In this paper, we propose two additional ( and different) algorithms for concurrent real-time garbage collection: CLOVER and CHICKEN. Both collectors obtain reduced complexity over the first collector STOPLESS, but need to trade a benefit for it. We study the algorithmic strengths and weaknesses of CLOVER and CHICKEN and compare them to STOPLESS. Finally, we have implemented all three collectors on the Bartok compiler and runtime for C# and we present measurements to compare their efficiency and responsiveness.
Despite decades of research on parsing, the construction of parsers remains a painstaking, manual process prone to subtle bugs and pitfalls. We present a programming-by-example framework called Parsify that is able to...
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ISBN:
(纸本)9781450334686
Despite decades of research on parsing, the construction of parsers remains a painstaking, manual process prone to subtle bugs and pitfalls. We present a programming-by-example framework called Parsify that is able to synthesize a parser from input/output examples. The user does not write a single line of code. To achieve this, Parsify provides: (a) an iterative algorithm for synthesizing and refining a grammar one example at a time, (b) an interface that provides immediate visual feedback in response to changes in the grammar being refined, and (c) a graphical mechanism for specifying example parse trees using only textual selections. We empirically demonstrate the viability of our approach by using Parsify to construct parsers for source code drawn from Verilog, SQL, Apache, and Tiger.
We present a novel technique for static race detection in Java programs, comprised of a series of stages that employ a combination of static analyses to successively reduce the pairs of memory accesses potentially inv...
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We present a method for synthesizing recursive functions that provably satisfy a given specification in the form of a polymorphic refinement type. We observe that such specifications are particularly suitable for prog...
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ISBN:
(纸本)9781450342612
We present a method for synthesizing recursive functions that provably satisfy a given specification in the form of a polymorphic refinement type. We observe that such specifications are particularly suitable for program synthesis for two reasons. First, they offer a unique combination of expressive power and decidability, which enables automatic verification-and hence synthesis-of nontrivial programs. Second, a type-based specification for a program can often be effectively decomposed into independent specifications for its components, causing the synthesizer to consider fewer component combinations and leading to a combinatorial reduction in the size of the search space. At the core of our synthesis procedure is a newalgorithm for refinement type checking, which supports specification decomposition. We have evaluated our prototype implementation on a large set of synthesis problems and found that it exceeds the state of the art in terms of both scalability and usability. The tool was able to synthesize more complex programs than those reported in prior work (several sorting algorithms and operations on balanced search trees), as well as most of the benchmarks tackled by existing synthesizers, often starting from a more concise and intuitive user input.
C-Rules is a business rules management system developed by Constraint Technologies International(1) (CTI), designed for use in transportation problems. Users define rules describing various aspects of a problem, such ...
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ISBN:
(纸本)9781595938152
C-Rules is a business rules management system developed by Constraint Technologies International(1) (CTI), designed for use in transportation problems. Users define rules describing various aspects of a problem, such as solution costs and legality, which are then queried from a host application, typically an optimising solver. At its core, C-Rules provides a functional expression language which affords users both power and flexibility when formulating rules. In this paper we will describe our experiences of using functional programming both at the end-user level, as well as at the implementation level. We highlight some of the benefits we, and the product's users, have enjoyed from the decision to base our rule system on features such as: higher-order functions, referential transparency, and static, polymorphic typing. We also outline some of our experiences in using Haskell to build an efficient compiler for the core language.
We propose SE(2)GIS, a novel inductive recursion synthesis approach with the ability to both synthesize code and declare a problem unsolvable. SE(2)GIS combines a symbolic variant of counterexample-guided inductive sy...
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ISBN:
(纸本)9781450392655
We propose SE(2)GIS, a novel inductive recursion synthesis approach with the ability to both synthesize code and declare a problem unsolvable. SE(2)GIS combines a symbolic variant of counterexample-guided inductive synthesis (CEGIS) with a new dual inductive procedure, which focuses on proving a synthesis problem unsolvable rather than finding a solution for it. A vital component of this procedure is a new algorithm that produces a witness, a set of concrete assignments to relevant variables, as a proof that the synthesis instance is not solvable. Witnesses in the dual inductive procedure play the same role that solutions do in classic CEGIS;that is, they ensure progress. Given a reference function, invariants on the input recursive data types, and a target family of recursive functions, SE(2)GIS synthesizes an implementation in this family that is equivalent to the reference implementation, or declares the problem unsolvable and produces a witness for it. We demonstrate that SE(2)GIS is effective in both cases;that is, for interesting data types with complex invariants, it can synthesize non-trivial recursive functions or output witnesses that contain useful feedback for the user.
While logic programminglanguages offer a great deal of scope for parallelism, there is usually some overhead associated with the execution of goals in parallel because of the work involved in task creation and schedu...
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ISBN:
(纸本)0897913647
While logic programminglanguages offer a great deal of scope for parallelism, there is usually some overhead associated with the execution of goals in parallel because of the work involved in task creation and scheduling. In practice, therefore, the 'granularity' of a goal, i.e. an estimate of the work available under it, should be taken into account when deciding whether or not to execute a goal concurrently as a separate task. This paper describes a method for estimating the granularity of a goal at compile time. The runtime overhead associated with our approach is usually quite small, and the performance improvements resulting from the incorporation of grainsize control can be quite good. This is shown by means of experimental results.
We present the Sum-Product Probabilistic language (SPPL), a new probabilistic programminglanguage that automatically delivers exact solutions to a broad range of probabilistic inference queries. SPPL translates proba...
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ISBN:
(纸本)9781450383912
We present the Sum-Product Probabilistic language (SPPL), a new probabilistic programminglanguage that automatically delivers exact solutions to a broad range of probabilistic inference queries. SPPL translates probabilistic programs into sum-product expressions, a new symbolic representation and associated semantic domain that extends standard sum-product networks to support mixed-type distributions, numeric transformations, logical formulas, and pointwise and set-valued constraints. We formalize SPPL via a novel translation strategy from probabilistic programs to sum-product expressions and give sound exact algorithms for conditioning on and computing probabilities of events. SPPL imposes a collection of restrictions on probabilistic programs to ensure they can be translated into sum-product expressions, which allow the system to leverage new techniques for improving the scalability of translation and inference by automatically exploiting probabilistic structure. We implement a prototype of SPPL with a modular architecture and evaluate it on benchmarks the system targets, showing that it obtains up to 3500x speedups over state-of-the-art symbolic systems on tasks such as verifying the fairness of decision tree classifiers, smoothing hidden Markov models, conditioning transformed random variables, and computing rare event probabilities.
Program slices have potential uses in many software engineering applications. Traditional slicing algorithms, however, do not work correctly on programs that contain explicit jump statements. Two similar algorithms we...
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ISBN:
(纸本)089791662X
Program slices have potential uses in many software engineering applications. Traditional slicing algorithms, however, do not work correctly on programs that contain explicit jump statements. Two similar algorithms were proposed recently to alleviate this problem. Both require the flowgraph and the program dependence graph of the program to be modified. In this paper, we propose an alternative algorithm that leaves these graphs intact and uses a separate graph to store the additional required information. We also show that this algorithm permits an extremely efficient, conservative adaptation for use with programs that contain only `structured' jump statements.
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