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检索条件"任意字段=Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming"

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Interval-Based Memory Reclamation 18

Interval-Based Memory Reclamation

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23rd acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Wen, Haosen Izraelevitz, Joseph Cai, Wentao Beadle, H. Alan Scott, Michael L. Univ Rochester Dept Comp Sci Rochester NY 14627 USA

ISBN: (纸本)9781450349826

In this paper we present interval-based reclamation (IBR), a new approach to safe reclamation of disconnected memory blocks in nonblocking concurrent data structures. Safe reclamation is a difficult problem: a thread, before freeing a block, must ensure that no other threads are accessing that block;the required synchronization tends to be expensive. In contrast with epoch-based reclamation, in which threads reserve all blocks created after a certain time, or pointer-based reclamation (e.g., hazard pointers), in which threads reserve individual blocks, IBR allows a thread to reserve all blocks known to have existed in a bounded interval of time. By comparing a thread's reserved interval with the lifetime of a detached but not yet reclaimed block, the system can determine if the block is safe to free. Like hazard pointers, IBR avoids the possibility that a single stalled thread may reserve an unbounded number of blocks;unlike hazard pointers, it avoids a memory fence on most pointer-following operations. It also avoids the need to explicitly "unreserve" a no-longer-needed pointer. We describe three specific IBR schemes (one with several variants) that trade off performance, applicability, and space requirements. IBR requires no special hardware or OS support. In experiments with data structure microbenchmarks, it also compares favorably (in both time and space) to other state-of-the-art approaches, making it an attractive alternative for libraries of concurrent data structures.

关键词： shared memory garbage collection parallel algorithms

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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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TigerQuoll: parallel Event-based JavaScript 13

TigerQuoll: Parallel Event-based JavaScript

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

作者： Bonetta, Daniele Binder, Walter Pautasso, Cesare Univ Lugano USI Fac Informat Lugano Switzerland

ISBN: (纸本)9781450319225

JavaScript, the most popular language on the Web, is rapidly moving to the server-side, becoming even more pervasive. Still, JavaScript lacks support for shared memory parallelism, making it challenging for developers to exploit multicores present in both servers and clients. In this paper we present TigerQuoll, a novel API and runtime for parallel programming in JavaScript. TigerQuoll features an event-based API and a parallel runtime allowing applications to exploit a mutable shared memory space. The programming model of TigerQuoll features automatic consistency and concurrency management, such that developers do not have to deal with shared-data synchronization. TigerQuoll supports an innovative transaction model that allows for eventual consistency to speed up high-contention workloads. Experiments show that TigerQuoll applications scale well, allowing one to implement common parallelism patterns in JavaScript.

关键词： Languages Performance JavaScript Event-based programming parallelism Eventual Transactions

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Expressing Graph Algorithms Using Generalized Active Messages 13

Expressing Graph Algorithms Using Generalized Active Message...

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

作者： Edmonds, Nick Willcock, Jeremiah Lumsdaine, Andrew Indiana Univ Bloomington IN 47405 USA

ISBN: (纸本)9781450319225

Recently, graph computation has emerged as an important class of high-performance computing application whose characteristics differ markedly from those of traditional, compute-bound, kernels. Libraries such as BLAS, LAPACK, and others have been successful in codifying best practices in numerical computing. The data-driven nature of graph applications necessitates a more complex application stack incorporating runtime optimization. In this paper, we present a method of phrasing graph algorithms as collections of asynchronous, concurrently executing, concise code fragments which may be invoked both locally and in remote address spaces. A runtime layer performs a number of dynamic optimizations, including message coalescing, message combining, and software routing. Practical implementations and performance results are provided for a number of representative algorithms.

关键词： parallel Graph Algorithms Active Messages parallel programming Models

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Juggler: A Dependence-Aware Task-Based Execution Framework for GPUs 18

Juggler: A Dependence-Aware Task-Based Execution Framework f...

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23rd acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Belviranli, Mehmet E. Lee, Seyong Vetter, Jeffrey S. Bhuyan, Laxmi N. Oak Ridge Natl Lab Oak Ridge TN 37830 USA Univ Calif Riverside Riverside CA 92521 USA

ISBN: (纸本)9781450349826

Scientific applications with single instruction, multiple data (SIMD) computations show considerable performance improvements when run on today's graphics processing units (GPUs). However, the existence of data dependences across thread blocks may significantly impact the speedup by requiring global synchronization across multiprocessors (SMs) inside the GPU. To efficiently run applications with inter-block data dependences, we need fine-granular task-based execution models that will treat SMs inside a GPU as stand-alone parallel processing units. Such a scheme will enable faster execution by utilizing all internal computation elements inside the GPU and eliminating unnecessary waits during device-wide global barriers. In this paper, we propose Juggler, a task-based execution scheme for GPU workloads with data dependences. The Juggler framework takes applications embedding OpenMP 4.5 tasks as input and executes them on the GPU via an efficient in-device runtime, hence eliminating the need for kernel-wide global synchronization. Juggler requires no or little modification to the source code, and once launched, the runtime entirely runs on the GPU without relying on the host through the entire execution. We have evaluated Juggler on an NVIDIA Tesla P100 GPU and obtained up to 31% performance improvement against global barrier based implementation, with minimal runtime overhead.

关键词： GP-GPU programming task-based execution data dependence OpenMP 4.5

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LazyGraph: Lazy Data Coherency for Replicas in Distributed Graph-parallel Computation 18

LazyGraph: Lazy Data Coherency for Replicas in Distributed G...

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23rd acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Wang, Lei Zhuang, Liangji Chen, Junhang Cui, Huimin Lv, Fang Liu, Ying Fen, Xiaobing Chinese Acad Sci Inst Comp Technol State Key Lab Comp Architecture Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9781450349826

Replicas of a vertex play an important role in existing distributed graph processing systems which make a single vertex to be parallel processed by multiple machines and access remote neighbors locally without any remote access. However, replicas of vertices introduce data coherency problem. Existing distributed graph systems treat replicas of a vertex v as an atomic and indivisible vertex, and use an eager data coherency approach to guarantee replicas atomicity. In eager data coherency approach, any changes to vertex data must be immediately communicated to all replicas of v, thus leading to frequent global synchronizations and communications. In this paper, we propose a lazy data coherency approach, called LazyAsync, which treats replicas of a vertex as independent vertices and maintains the data coherency by computations, rather than communications in existing eager approach. Our approach automatically selects some data coherency points from the graph algorithm, and maintains all replicas to share the same global view only at such points, which means the replicas are enabled to maintain different local views between any two adjacent data coherency points. Based on PowerGraph, we develop a distributed graph processing system LazyGraph to implement the LazyAsync approach and exploit graph-aware optimizations. On a 48-node EC2-like cluster, LazyGraph outperforms PowerGraph on four widely used graph algorithms across a variety of real-world graphs, with a speedup ranging from 1.25x to 10.69x.

关键词： Lazy Data Coherency Distributed Graphparallel Computation Execution Model

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Andorra-I: A parallel prolog system that transparently exploits both and-and or-parallelism 91

Andorra-I: A parallel prolog system that transparently explo...

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3rd acm sigplan symposium on principles and practice of parallel programming, PPOPP 1991

作者： Costa, Vitor Santos Warren, David H. D. Yang, Rong Department of Computer Science University of Bristol BristolBS8 ITR United Kingdom

ISBN: (纸本)0897913906

Andorra-I is an experimental parallel Prolog system that transparently exploits both dependent and-parallelism and or-parallelism. It constitutes the first implementation of the Basic Andorra model, a parallel execution model for logic programs in which determinate goals are executed before other goals. This model, besides combining two of the most important forms of implicit parallelism in logic programs, also provides a form of implicit coroutining. This means that Andorra-I not only supports standard Prolog but also provides the capabilities of flat committed-choice languages such as Parlog and GHC. © 1991 Association for Computing Machinery. All Rights Reserved.

关键词： Computer circuits

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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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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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