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14th symposium on principles and practice of Declarative programming, PPDP 2012

作者： Marple, Kyle Bansal, Ajay Min, Richard Gupta, Gopal University of Texas at Dallas 800 W. Campbell Road Richardson TX United States Arizona State University 7231 E. Sonoran Arroyo Mall Mesa AZ United States

ISBN: (纸本)9781450315227

Answer Set programming (ASP) represents an elegant way of introducing non-monotonic reasoning into logic programming. ASP has gained popularity due to its applications to planning, default reasoning and other areas of AI. However, none of the approaches and current implementations for ASP are goal-directed. In this paper we present a technique based on coinduction that can be employed to design SLD resolution-style, goal-directed methods for executing answer set *** also discuss advantages and applications of such goal-directed execution of answer set programs, and report results from our implementation. Copyright © 2012 acm.

关键词： Logic programming

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AUTOGEN: Automatic Discovery of Cache-Oblivious parallel Recursive Algorithms for Solving Dynamic Programs 16

AUTOGEN: Automatic Discovery of Cache-Oblivious Parallel Rec...

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21st acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Chowdhury, Rezaul Ganapathi, Pramod Tithi, Jesmin Jahan Bachmeier, Charles Kuszmaul, Bradley C. Leiserson, Charles E. Solar-Lezama, Armando Tang, Yuan SUNY Stony Brook Dept Comp Sci Stony Brook NY 11794 USA MIT Comp Sci & Artificial Intelligence Lab Cambridge MA 02139 USA Fudan Univ Shanghai Key Lab Intelligent Informat Proc Sch Software Shanghai Peoples R China

ISBN: (纸本)9781450340922

We present AUTOGEN-an algorithm that for a wide class of dynamic programming (DP) problems automatically discovers highly efficient cache-oblivious parallel recursive divide-and-conquer algorithms from inefficient iterative descriptions of DP recurrences. AUTOGEN analyzes the set of DP table locations accessed by the iterative algorithm when run on a DP table of small size, and automatically identifies a recursive access pattern and a corresponding provably correct recursive algorithm for solving the DP recurrence. We use AUTOGEN to autodiscover efficient algorithms for several well-known problems. Our experimental results show that several autodiscovered algorithms significantly outperform parallel looping and tiled loop-based algorithms. Also these algorithms are less sensitive to fluctuations of memory and bandwidth compared with their looping counterparts, and their running times and energy profiles remain relatively more stable. To the best of our knowledge, AUTOGEN is the first algorithm that can automatically discover new nontrivial divide-and-conquer algorithms.

关键词： AutoGen automatic discovery dynamic programming recursive divide-and-conquer cache-efficient parallel cacheoblivious energy-efficient cache-adaptive

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the lock-free k-LSM relaxed priority queue 2015

The lock-free k-LSM relaxed priority queue

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20th acm sigplan symposium on principles and practice of parallel programming, PPoPP 2015

作者： Wimmer, Martin Gruber, Jakob Träff, Jesper Larsson Tsigas, Philippas Faculty of Informatics Parallel Computing Vienna University of Technology Vienna/Wien1040 Austria Computer Science and Engineering Chalmers University of Technology Göteborg412 96 Sweden

ISBN: (纸本)9781450332057

We present a new, concurrent, lock-free priority queue that relaxes the delete-min operation to allow deletion of any of the ρ+1 smallest keys instead of only a minimal one, where ρ is a parameter that can be configured at runtime. It is built from a logarithmic number of sorted arrays, similar to log-structured merge-trees (LSM). For keys added and removed by the same thread the behavior is identical to a non-relaxed priority queue. We compare to state-of-the-art lock-free priority queues with both relaxed and non-relaxed semantics, showing high performance and good scalability of our approach.

关键词： parallel programming

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Scaling Out Speculative Execution of Finite-State Machines with parallel Merge 20

Scaling Out Speculative Execution of Finite-State Machines w...

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25th acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Xia, Yang Jiang, Peng Agrawal, Gagan Ohio State Univ Columbus OH 43210 USA Univ Iowa Iowa City IA USA

ISBN: (纸本)9781450368186

A finite-state machine (FSM) is a key component for many important applications, such as Huffman decoding, regular expression matching and HTML tokenization. Due to its inherent dependencies and unpredictable memory access pattern, FSM computations are considered to be extremely difficult to parallelize. As such, significant research efforts have been made to accelerate FSM computations. Although they achieve promising performance results on multi-core machines, these methods are not scalable for emerging many-core architectures such as the GPUs. Based on our experiments, we point out that the bottleneck of achieving scalability on GPUs is the sequential merge inherent to these methods. However, unlike the case for simple reduction loops, parallel merge implementations for FSM computations typically require runtime checks and re-executions, which can also impede performance. Based on these observations, we develop parallel merge techniques that select efficient runtime check implementations and avoids unnecessary re-executions. Further, based on GPU architectural features, we develop optimization techniques to improve performance. We evaluate our parallel merge implementations on a set of representative algorithms. Experimental results show that our parallel merge implementations are 2.02-6.74 times more efficient than corresponding sequential merge implementations and achieve better scalability on an Nvidia V100 GPU.

关键词： Finite-State Machines Speculation GPUs

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parallel Schedule Synthesis for Attribute Grammars 13

Parallel Schedule Synthesis for Attribute Grammars

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18th acm sigplan symposium on principles and practice of parallel programming

作者： Meyerovich, Leo A. Torok, Matthew E. Atkinson, Eric Bodik, Rastislav Univ Calif Berkeley Berkeley CA 94720 USA

ISBN: (纸本)9781450319225

We examine how to synthesize a parallel schedule of structured traversals over trees. In our system, programs are declaratively specified as attribute grammars. Our synthesizer automatically, correctly, and quickly schedules the attribute grammar as a composition of parallel tree traversals. Our downstream compiler optimizes for GPUs and multicore CPUs. We provide support for designing efficient schedules. First, we introduce a declarative language of schedules where programmers may constrain any part of the schedule and the synthesizer will complete and autotune the rest. Furthermore, the synthesizer answers debugging queries about how schedules may be completed. We evaluate our approach with two case studies. First, we created the first parallel schedule for a large fragment of CSS and report a 3X multicore speedup. Second, we created an interactive GPU-accelerated animation of over 100,000 nodes.

关键词： CSS layout sketching attribute grammars scheduling

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No Barrier in the Road: A Comprehensive Study and Optimization of ARM Barriers 20

No Barrier in the Road: A Comprehensive Study and Optimizati...

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25th acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Liu, Nian Zang, Binyu Chen, Haibo Shanghai Jiao Tong Univ Inst Parallel & Distributed Syst Shanghai Peoples R China Shanghai Jiao Tong Univ Shanghai Key Lab Scalable Comp & Syst Shanghai Peoples R China

ISBN: (纸本)9781450368186

In this paper, we present the first comprehensive performance characterization and optimization of ARM barriers on both mobile and server platforms. We draw a set of observations through several abstracted models and validate them in scenarios where barriers are intensively used. We find that (1) order-preserving approaches without involving the bus significantly outperform other approaches, and (2) the tremendous overhead mostly comes from barriers strictly following remote memory references. Usually, such barriers are inserted when threads are exchanging data, and they are used to ensure the relative order between storing the data to a shared buffer and setting a flag to inform the receiver. Based on the observations, we propose a new mechanism, Pilot, to remove such barriers by leveraging the single-copy atomicity to piggyback the flag with the data. Applying Pilot only requires minor changes to applications and provides 10%-360% performance improvements in multiple benchmarks, which are close to the ideal performance without barriers.

关键词： barrier synchronization concurrency lock

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Task-oriented programming in a pure functional language 12

Task-oriented programming in a pure functional language

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14th symposium on principles and practice of Declarative programming, PPDP 2012

作者： Plasmeijer, Rinus Lijnse, Bas Michels, Steffen Achten, Peter Koopman, Pieter Institute for Computing and Information Sciences Radboud University P.O. Box 9010 6500 GL Nijmegen Netherlands Faculty of Military Sciences Netherlands Defense Academy P.O. Box 10000 1780 CA Den Helder Netherlands

ISBN: (纸本)9781450315227

Task-Oriented programming (TOP) is a novel programming paradigm for the construction of distributed systems where users work together on the *** multiple users collaborate, they need to interact with each other frequently. TOP supports the definition of tasks that react to the progress made by others. With TOP, complex multi-user interactions can be programmed in a declarative style just by defining the tasks that have to be accomplished, thus eliminating the need to worry about the implementation detail that commonly frustrates the development of applications for this domain. TOP builds on four core concepts: tasks that represent computations or work to do which have an observable value that may change over time, data sharing enabling tasks to observe each other while the work is in progress, generic type driven generation of user interaction, and special combinators for sequential and parallel task composition. the semantics of these core concepts is defined in this paper. As an example we present the iTask3 framework, which embeds TOP in the functional programming language Clean. Copyright © 2012 acm.

关键词： Semantics

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Using Sample-Based Time Series Data for Automated Diagnosis of Scalability Losses in parallel Programs 20

Using Sample-Based Time Series Data for Automated Diagnosis ...

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25th acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Wei, Lai Mellor-Crummey, John Rice Univ Dept Comp Sci Houston TX 77005 USA Rice Univ Houston TX USA Pony Ai Fremont CA USA

ISBN: (纸本)9781450368186

the performance of many parallel applications has failed to scale as fast as successive generations of hardware on which these applications execute. To understand the cause of scalability losses, experts use performance tools to monitor and analyze application behavior. Profiles generated by performance tools can usually indicate the presence of scalability losses while time series data are generally necessary to pinpoint the root causes of such losses. However, manual analysis of time series data can be difficult in executions with a large number of processes, long running times, and deep call chains. this paper describes an automated framework that analyzes sample-based time series data to diagnose scalability losses in parallel executions. the framework's automated diagnosis of scalability losses indicates their symptoms, severity, and causes. Two case studies illustrate the effectiveness of this framework. When compared to a tool that analyzes performance using instrumentation-based traces, our overhead for collecting sample-based time series is 1/28 in time and 1/1600 in space while our automated analysis takes 1/25 of the time.

关键词： Performance automated diagnosis scalability losses sample-based time series data

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Deadlock-free buffer configuration for stream computing

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INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2017年第5期31卷 441-450页

作者： Li, Peng Beard, Jonathan C. Buhler, Jeremy D. Washington Univ Dept Comp Sci & Engn St Louis MO 63130 USA

Stream computing is a popular paradigm for parallel and distributed computing, where compute nodes are connected by first-in first-out data channels. Each channel can be considered as a concatenation of several data buffers, including an output buffer for the sender and an input buffer for the receiver. the configuration of buffer sizes impacts the performance as well as the correctness of the application. In this article, we focus on application deadlocks that are caused by incorrect configuration of buffer sizes. We describe three types of deadlock in streaming applications, categorized by how they can be created. To avoid them, we first prove necessary and sufficient conditions for deadlock-free computations;then based on the theorems, we propose both compile-time and runtime solutions for deadlock avoidance.

关键词： Buffer configuration deadlock avoidance feedback channels parallel and distributed computing streaming computing

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Copperhead: Compiling an Embedded Data parallel Language 11

Copperhead: Compiling an Embedded Data Parallel Language

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16th acm symposium on principles and practice of parallel programming

作者： Catanzaro, Bryan Garland, Michael Keutzer, Kurt Univ Calif Berkeley Berkeley CA 94720 USA

ISBN: (纸本)9781450301190

Modern parallel microprocessors deliver high performance on applications that expose substantial fine-grained data parallelism. Although data parallelism is widely available in many computations, implementing data parallel algorithms in low-level languages is often an unnecessarily difficult task. the characteristics of parallel microprocessors and the limitations of current programming methodologies motivate our design of Copperhead, a high-level data parallel language embedded in Python. the Copperhead programmer describes parallel computations via composition of familiar data parallel primitives supporting both flat and nested data parallel computation on arrays of data. Copperhead programs are expressed in a subset of the widely used Python programming language and interoperate with standard Python modules, including libraries for numeric computation, data visualization, and analysis. In this paper, we discuss the language, compiler, and runtime features that enable Copperhead to efficiently execute data parallel code. We define the restricted subset of Python which Copperhead supports and introduce the program analysis techniques necessary for compiling Copperhead code into efficient low-level implementations. We also outline the runtime support by which Copperhead programs interoperate with standard Python modules. We demonstrate the effectiveness of our techniques with several examples targeting the CUDA platform for parallel programming on GPUs. Copperhead code is concise, on average requiring 3.6 times fewer lines of code than CUDA, and the compiler generates efficient code, yielding 45-100% of the performance of hand-crafted, well optimized CUDA code.

关键词： Python Data parallelism GPU Algorithms Design Performance

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