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检索条件"任意字段=Proceedings of the 14th ACM SIGPLAN symposium on Principles and practice of parallel programming"

共 360 条记录，以下是161-170 订阅

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Automatic Problem Size Sensitive Task Partitioning on Heterogeneous parallel Systems 13

Automatic Problem Size Sensitive Task Partitioning on Hetero...

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

作者： Grasso, Ivan Kofler, Klaus Cosenza, Biagio Fahringer, thomas Univ Innsbruck Inst Informat A-6020 Innsbruck Austria

ISBN: (纸本)9781450319225

In this paper we propose a novel approach which automatizes task partitioning in heterogeneous systems. Our framework is based on the Insieme Compiler and Runtime infrastructure [1]. the compiler translates a single-device OpenCL program into a multi-device OpenCL program. the runtime system then performs dynamic task partitioning based on an offline-generated prediction model. In order to derive the prediction model, we use a machine learning approach that incorporates static program features as well as dynamic, input sensitive features. Our approach has been evaluated over a suite of 23 programs and achieves performance improvements compared to an execution of the benchmarks on a single CPU and a single GPU only.

关键词： Languages Algorithms Performance heterogeneous computing compilers GPU task partitioning code analysis machine learning runtime system

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Work-stealing with Configurable Scheduling Strategies 13

Work-stealing with Configurable Scheduling Strategies

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

作者： Wimmer, Martin Traeff, Jesper Larsson Cederman, Daniel Tsigas, Philippas Vienna Univ Technol Fac Informat Res Grp Parallel Comp A-1040 Vienna Austria Chalmers Univ Technol S-41296 Gothenburg Sweden

ISBN: (纸本)9781450319225

Work-stealing systems are typically oblivious to the nature of the tasks they are scheduling. they do not know or take into account how long a task will take to execute or how many subtasks it will spawn. Moreover, task execution order is typically determined by an underlying task storage data structure, and cannot be changed. there are thus possibilities for optimizing task parallel executions by providing information on specific tasks and their preferred execution order to the scheduling system. We investigate generalizations of work-stealing and introduce a framework enabling applications to dynamically provide hints on the nature of specific tasks using scheduling strategies. Strategies can be used to independently control both local task execution and steal order. Strategies allow optimizations on specific tasks, in contrast to more conventional scheduling policies that are typically global in scope. Strategies are composable and allow different, specific scheduling choices for different parts of an application simultaneously. We have implemented a work-stealing system based on our strategy framework. A series of benchmarks demonstrates beneficial effects that can be achieved with scheduling strategies.

关键词： Algorithms Work-stealing scheduler hints strategies priorities

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Correct and efficient work-stealing for weak memory models 13

Correct and efficient work-stealing for weak memory models

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18th acm sigplan symposium on principles and practice of parallel programming, PPoPP 2013

作者： Lê, Nhat Minh Pop, Antoniu Cohen, Albert Zappa Nardelli, Francesco INRIA ENS Paris Paris France

ISBN: (纸本)9781450319225

Chase and Lev's concurrent deque is a key data structure in shared-memory parallel programming and plays an essential role in work-stealing schedulers. We provide the first correctness proof of an optimized implementation of Chase and Lev's deque on top of the POWER and ARM architectures: these provide very relaxed memory models, which we exploit to improve performance but considerably complicate the reasoning. We also study an optimized x86 and a portable C11 implementation, conducting systematic experiments to evaluate the impact of memory barrier optimizations. Our results demonstrate the benefits of hand tuning the deque code when running on top of relaxed memory models. © 2013 acm.

关键词： parallel programming

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parallel programming with big operators 13

Parallel programming with big operators

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18th acm sigplan symposium on principles and practice of parallel programming, PPoPP 2013

作者： Park, Changhee Steele Jr., Guy L. Tristan, Jean-Baptiste KAIST Seoul Korea Republic of Oracle Labs. Burlington MA United States

ISBN: (纸本)9781450319225

In the sciences, it is common to use the so-called "big operator" notation to express the iteration of a binary operator (the reducer) over a collection of values. Such a notation typically assumes that the reducer is associative and abstracts the iteration process. Consequently, from a programming point-of-view, we can organize the reducer operations to minimize the depth of the overall reduction, allowing a potentially parallel evaluation of a big operator expression. We believe that the big operator notation is indeed an effective construct to express parallel computations in the Generate/Map/Reduce programming model, and our goal is to introduce it in programming languages to support parallel programming. the effective definition of such a big operator expression requires a simple way to generate elements, and a simple way to declare algebraic properties of the reducer (such as its identity, or its commutativity). In this poster, we want to present an extension of Scala with support for big operator expressions. We show how big operator expressions are defined and how the API is organized to support the simple definition of reducers with their algebraic properties. © 2013 Authors.

关键词： parallel programming

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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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ZOOMM: A parallel web browser engine for multicore mobile devices 13

ZOOMM: A parallel web browser engine for multicore mobile de...

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18th acm sigplan symposium on principles and practice of parallel programming, PPoPP 2013

作者： Caşcaval, CǍlin Fowler, Seth Montesinos-Ortego, Pablo Piekarski, Wayne Reshadi, Mehrdad Robatmili, Behnam Weber, Michael Bhavsar, Vrajesh Qualcomm Research Silicon Valley Santa Clara CA United States

ISBN: (纸本)9781450319225

We explore the challenges in expressing and managing concurrency in browsers on mobile devices. Browsers are complex applications that implement multiple standards, need to support legacy behavior, and are highly dynamic and interactive. We present ZOOMM, a highly concurrent web browser engine prototype and show how concurrency is effectively exploited at different levels: speed up computation performance, preload network resources, and preprocess resources outside the critical path of page loading. On a dual-core Android mobile device we demonstrate that ZOOMM is two times faster than the native WebKit based browser when loading the set of pages defined in the Vellamo benchmark. © 2013 acm.

关键词： Web browsers

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Multi-Level parallel Computing of Reverse Time Migration for Seismic Imaging on Blue Gene/Q 13

Multi-Level Parallel Computing of Reverse Time Migration for...

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

作者： Lu, Ligang Magerlein, Karen IBM Watson Res Ctr Yorktown Hts NY USA

ISBN: (纸本)9781450319225

Blue Gene/Q (BG/Q) is an early representative of increasing scale and thread count that will characterize future HPC systems: large counts of nodes, cores, and threads; and a rich programming environment with many degrees of freedom in parallel computing optimization. So it is both a challenge and an opportunity to it to accelerate the seismic imaging applications to the unprecedented levels that will significantly advance the technologies for the oil and gas industry. In this work we aim to address two important questions: how HPC systems with high levels of scale and thread count will perform in real applications; and how systems with many degrees of freedom in parallel programming can be calibrated to achieve optimal performance. Based on BG/Q's architecture features and RTM workload characteristics, we developed massive domain partition, MPI , and SIMD Our detailed deep analyses in various aspects of optimization also provide valuable experience and insights into how can be utilized to facilitate the advance of seismic imaging technologies. Our BG/Q RTM solution achieved a 14.93x speedup over the BG/P implementation. Our multi-level parallelism strategies for Reverse Time Migration (RTM) seismic imaging computing on BG/Q provides an example of how HPC systems like BG/Q can accelerate applications to a new level.

关键词： Multi-level parallelism parallel Computing High Performance Computing Performance Optimization Reverse Time Migration Seismic Imaging

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the Tasks with Effects Model for Safe Concurrency 13

The Tasks with Effects Model for Safe Concurrency

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

作者： Heumann, Stephen T. Adve, Vikram S. Wang, Shengjie Univ Illinois Urbana IL 61801 USA

ISBN: (纸本)9781450319225

Today's widely-used concurrent programming models either provide weak safety guarantees, making it easy to write code with subtle errors, or are limited in the class of programs that they can express. We propose a new concurrent programming model based on tasks with effects that offers strong safety guarantees while still providing the flexibility needed to support the many ways that con-currency is used in complex applications. the core unit of work in our model is a dynamically-created task. the model's key feature is that each task has programmer-specified effects, and a run-time scheduler is used to ensure that two tasks are run concurrently only if they have non-interfering effects. through the combination of statically verifying the declared effects of tasks and using an effect-aware run-time scheduler, our model is able to guarantee strong safety properties, including data race freedom and atomicity. It is also possible to use our model to write programs and computations that can be statically proven to behave deterministically. We describe the tasks with effects programming model and provide a formal dynamic semantics for it. We also describe our implementation of this model in an extended version of Java and evaluate its use in several programs exhibiting various patterns of concurrency.

关键词： Languages Verification Design Performance Tasks effects task scheduling concurrent and parallel programming task isolation data race freedom atomicity determinism

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Ligra: A Lightweight Graph Processing Framework for Shared Memory 13

Ligra: A Lightweight Graph Processing Framework for Shared M...

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

作者： Shun, Julian Blelloch, Guy E. Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9781450319225

there has been significant recent interest in parallel frameworks for processing graphs due to their applicability in studying social networks, the Web graph, networks in biology, and unstructured meshes in scientific simulation. Due to the desire to process large graphs, these systems have emphasized the ability to run on distributed memory machines. Today, however, a single multicore server can support more than a terabyte of memory, which can fit graphs with tens or even hundreds of billions of edges. Furthermore, for graph algorithms, shared-memory multicores are generally significantly more efficient on a per core, per dollar, and per joule basis than distributed memory systems, and shared-memory algorithms tend to be simpler than their distributed counterparts. In this paper, we present a lightweight graph processing framework that is specific for shared-memory parallel/multicore machines, which makes graph traversal algorithms easy to write. the framework has two very simple routines, one for mapping over edges and one for mapping over vertices. Our routines can be applied to any subset of the vertices, which makes the framework useful for many graph traversal algorithms that operate on subsets of the vertices. Based on recent ideas used in a very fast algorithm for breadth-first search (BFS), our routines automatically adapt to the density of vertex sets. We implement several algorithms in this framework, including BFS, graph radii estimation, graph connectivity, betweenness centrality, PageRank and single-source shortest paths. Our algorithms expressed using this framework are very simple and concise, and perform almost as well as highly optimized code. Furthermore, they get good speedups on a 40-core machine and are significantly more efficient than previously reported results using graph frameworks on machines with many more cores.

关键词： Algorithms Performance Shared Memory Graph Algorithms parallel programming

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Ownership Passing: Efficient Distributed Memory programming on Multi-core Systems 13

Ownership Passing: Efficient Distributed Memory Programming ...

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

作者： Friedley, Andrew Hoefler, Torsten Bronevetsky, Greg Lumsdaine, Andrew Ma, Ching-Chen Indiana Univ Bloomington IN 47405 USA ETH Zurich Switzerland Lawrence Livermore Natl Lab Livermore CA USA Rose Hulman Inst Technol Terre Haute IN 47803 USA

ISBN: (纸本)9781450319225

the number of cores in multi- and many-core high-performance processors is steadily increasing. MPI, the de-facto standard for programming high-performance computing systems offers a distributed memory programming model. MPI's semantics force a copy from one process' send buffer to another process' receive buffer. this makes it difficult to achieve the same performance on modern hardware than shared memory programs which are arguably harder to maintain and debug. We propose generalizing MPI's communication model to include ownership passing, which make it possible to fully leverage the shared memory hardware of multi-and many-core CPUs to stream communicated data concurrently with the receiver's computations on it. the benefits and simplicity of message passing are retained by extending MPI with calls to send (pass) ownership of memory regions, instead of their contents, between processes. Ownership passing is achieved with a hybrid MPI implementation that runs MPI processes as threads and is mostly transparent to the user. We propose an API and a static analysis technique to transform legacy MPI codes automatically and transparently to the programmer, demonstrating that this scheme is easy to use in practice. Using the ownership passing technique, we see up to 51% communication speedups over a standard message passing implementation on state-of-the art multicore systems. Our analysis and interface will lay the groundwork for future development of MPI-aware optimizing compilers and multi-core specific optimizations, which will be key for success in current and next-generation computing platforms.

关键词： Ownership Passing Distributed Memory Shared Memory Message Passing Multi-core

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