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检索条件"任意字段=16th ACM Symposium on Principles and Practice of Parallel Programming"

共 407 条记录，以下是51-60 订阅

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Intra-Application Shared Cache Partitioning For Multithreaded Applications

Intra-Application Shared Cache Partitioning For Multithreade...

引用

15th acm SIGPLAN symposium on principles and practice of parallel programming

作者： Muralidhara, Sai Prashanth Kandemir, Mahmut Raghavan, Padma Penn State Univ University Pk PA 16802 USA

In this paper, we address the problem of partitioning a shared cache when the executing threads belong to the same application.

ISBN: (纸本)9781605587080

In this paper, we address the problem of partitioning a shared cache when the executing threads belong to the same application.

关键词： Cache Multicore parallel Applications

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Automatic placement of communications in mesh-partitioning parallelization 97

Automatic placement of communications in mesh-partitioning p...

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6th acm SIGPLAN symposium on principles and practice of parallel programming

作者： Hascoet, L INRIA Sophia-Antipolis B.P. 93 06902 Sophia-Antipolis France

ISBN: (纸本)9780897919067

We present a tool for mesh-partitioning parallelization of numerical programs working iteratively on an unstructured mesh. this conventional method splits a mesh into sub-meshes, adding some overlap on the boundaries of the sub-meshes. the program is then run in SPMD mode on a parallel architecture with distributed memory. It is necessary to add calls to communication routines at a few carefully selected locations in the code. the tool presented here uses the data-dependence information to mechanize the placement of these synchronizations. Additionally, we see that there is not a unique solution for placing these synchronizations, and performance depends on this choice.

关键词： parallel processing systems

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Applying the Concurrent Collections programming Model to Asynchronous parallel Dense Linear Algebra

Applying the Concurrent Collections Programming Model to Asy...

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15th acm SIGPLAN symposium on principles and practice of parallel programming

作者： Chandramowlishwaran, Aparna Knobe, Kathleen Vuduc, Richard Georgia Inst Technol Atlanta GA 30332 USA Intel Corp Santa Clara CA 95051 USA

ISBN: (纸本)9781605587080

this poster is a case study on the application of a novel programming model, called Concurrent Collections (CnC), to the implementation of an asynchronous-parallel algorithm for computing the Cholesky factorization of dense matrices. In CnC, the programmer expresses her computation in terms of application-specific operations, partially-ordered by semantic scheduling constraints. We demonstrate the performance potential of CnC in this poster, by showing that our Cholesky implementation nearly matches or exceeds competing vendor-tuned codes and alternative programming models. We conclude that the CnC model is well-suited for expressing asynchronous-parallel algorithms on emerging multicore systems.

关键词： Algorithms Performance

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Achieving a Single Compute Device Image in OpenCL for Multiple GPUs 11

Achieving a Single Compute Device Image in OpenCL for Multip...

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16th acm symposium on principles and practice of parallel programming

作者： Kim, Jungwon Kim, Honggyu Lee, Joo Hwan Lee, Jaejin Seoul Natl Univ Ctr Manycore Programming Sch Comp Sci & Engn Seoul 151744 South Korea

ISBN: (纸本)9781450301190

In this paper, we propose an OpenCL framework that treats multiple GPUs as a single compute device. Providing the single GPU image makes an OpenCL application written for a single GPU portable to the GPGPU systems with multiple GPUs. It also makes the application exploit the full computing power of the multiple GPUs and the entire amount of GPU memories available in the system. Our OpenCL framework automatically distributes at run time an OpenCL kernel written for a single GPU into multiple CUDA kernels that execute on the multiple GPUs. It applies a run-time memory access range analysis to the kernel by performing a sampling run and identifies an optimal workload distribution for the kernel. To achieve a single compute device image, the runtime maintains a virtual device memory that is allocated in the main memory of the GPGPU system. the OpenCL runtime treats the memory as if it were the memory of a single GPO device and keeps it consistent to the memories of the multiple GPUs. Our OpenCL-C-to-C translator generates the sampling code from the OpenCL kernel code and our OpenCL-C-to-CUDA-C translator generates the CUDA kernel code for the distributed OpenCL kernel. We show the effectiveness of our OpenCL framework by implementing the OpenCL runtime and the two source-to-source translators. We evaluate its performance with a GPGU system that contains eight GPUs using eleven OpenCL benchmark applications.

关键词： Algorithm Design Experimentation Languages Measurement Performance OpenCL Compilers Runtime Access range analysis Workload distribution Virtual device memory

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POSTER: ParGeo: A Library for parallel Computational Geometry 27

POSTER: ParGeo: A Library for Parallel Computational Geometr...

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27th acm SIGPLAN symposium on principles and practice of parallel programming (PPoPP)

作者： Wang, Yiqiu Yu, Shangdi Dhulipala, Laxman Gu, Yan Shun, Julian IMIT CSAIL Riverside CA USA

We present PARGEO, a multicore library for computational geometry algorithms. We describe two of the algorithms from PARGEO, convex hull and the smallest enclosing ball, and present a short evaluation of all implement... 详细信息

ISBN: (纸本)9781450392044

关键词： Computational geometry

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COREMU: A Scalable and Portable parallel Full-system Emulator 11

COREMU: A Scalable and Portable Parallel Full-system Emulato...

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16th acm symposium on principles and practice of parallel programming

作者： Wang, Zhaoguo Liu, Ran Chen, Yufei Wu, Xi Chen, Haibo Zhang, Weihua Zang, Binyu Fudan Univ Parallel Proc Inst Shanghai Peoples R China

ISBN: (纸本)9781450301190

this paper presents the open-source COREMU, a scalable and portable parallel emulation framework that decouples the complexity of parallelizing full-system emulators from building a mature sequential one. the key observation is that CPU cores and devices in current (and likely future) multiprocessors are loosely-coupled and communicate through well-defined interfaces. Based on this observation, COREMU emulates multiple cores by creating multiple instances of existing sequential emulators, and uses a thin library layer to handle the inter-core and device communication and synchronization, to maintain a consistent view of system resources. COREMU also incorporates lightweight memory transactions, feedback-directed scheduling, lazy code invalidation and adaptive signal control to provide scalable performance. To make COREMU useful in practice, we also provide some preliminary tools and APIs that can help programmers to diagnose performance problems and (concurrency) bugs. A working prototype, which reuses the widely-used QEMU as the sequential emulator, is with only 2500 lines of code (LOCs) changes to QEMU. It currently supports x64 and ARM platforms, and can emulates up to 255 (1) cores running commodity OSes with practical performance, while QEMU cannot scale above 32 cores. A set of performance evaluation against QEMU indicates that, COREMU has negligible uniprocessor emulation overhead, performs and scales significantly better than QEMU. We also show how COREMU could be used to diagnose performance problems and concurrency bugs of both OS kernel and parallel applications.

关键词： Full-system Emulator parallel Emulator Multicore Design Experimentation Performance

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Lazier Imperative programming 14

Lazier Imperative Programming

引用

16th International symposium on principles and practice of Declarative programming (PPDP)

作者： Douence, Remi Tabareau, Nicolas Mines Nantes Nantes France INRIA Le Chesnay France

ISBN: (纸本)9781450329477

Laziness is a powerful concept in functional programming that enables reusing general functions in a specific context, while keeping performance close to the efficiency of dedicated definitions. Lazy evaluation can be used in imperative programming too. Twenty years ago, John Launchbury was already advocating for lazy imperative programming, but the level of laziness of his framework remained limited: a single effect can trigger numerous delayed computations, even if those are not required for the correctness of the evaluation. Twenty years after, the picture has not changed. In this article, we propose an Haskell framework to specify computational effects of imperative programs as well as their dependencies. Our framework is based on the operational monad transformer which encapsulates an algebraic presentation of effectful operations. A lazy monad transformer is then in charge of delaying non-necessary computations by maintaining a trace of imperative closures. We present a semantics of a call-by-need A-calculus extended with imperative strict and lazy features and prove the correctness of our approach. While originally motivated by a less rigid use of foreign functions, we show that our approach is fruitful for a simple scenario based on sorted mutable arrays. Furthermore, we can take advantage of equations between algebraic operations to dynamically optimize imperative computations composition.

关键词： Calculations

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Ordered vs. Unordered: a Comparison of parallelism and Work-efficiency in Irregular Algorithms 11

Ordered <i>vs</i>. Unordered: a Comparison of Parallelism an...

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16th acm symposium on principles and practice of parallel programming

作者： Hassaan, M. Amber Burtscher, Martin Pingali, Keshav Texas State Univ San Marcos Dept Comp Sci San Marcos TX USA Univ Texas Austin Dept Comp Sci Austin TX 78712 USA

ISBN: (纸本)9781450301190

Outside of computational science, most problems are formulated in terms of irregular data structures such as graphs, trees and sets. Unfortunately, we understand relatively little about the structure of parallelism and locality in irregular algorithms. In this paper, we study several algorithms for four such problems: discrete-event simulation, single-source shortest path, breadth-first search, and minimal spanning trees. We show that these algorithms can be classified into two categories that we call unordered and ordered, and demonstrate experimentally that there is a trade-off between parallelism and work efficiency: unordered algorithms usually have more parallelism than their ordered counterparts for the same problem, but they may also perform more work. Nevertheless, our experimental results show that unordered algorithms typically lead to more scalable implementations, demonstrating that less work-efficient irregular algorithms may be better for parallel execution.

关键词： Irregular Algorithms Amorphous Data-parallelism parallel Breadth-first Search Single-Source Shortest Path Discrete-Event Simulation Minimal Spanning Tree Multicore processors Galois system Algorithms Languages Performance

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POSTER: Automatic Synthesis of parallel Unix Commands and Pipelines with KUMQUAT 27

POSTER: Automatic Synthesis of Parallel Unix Commands and Pi...

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27th acm SIGPLAN symposium on principles and practice of parallel programming (PPoPP)

作者： Shen, Jiasi Rinard, Martin Vasilakis, Nikos MIT Cambridge MA USA

ISBN: (纸本)9781450392044

We present KUMQUAT, a system for automatically generating data-parallel implementations of UNIX shell commands and pipelines. the generated parallel versions split input streams, execute multiple instantiations of the original pipeline commands to process the splits in parallel, then combine the resulting parallel outputs to produce the final output stream. KumQUAT automatically synthesizes the combine operators, with a domain-specific combiner language acting as a strong regularizer that promotes efficient inference of correct combiners. We present experimental results that show that these combiners enable the effective parallelization of our benchmark scripts.

关键词： Automatic parallelization program synthesis

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parallel and Distributed Bounded Model Checking of Multi-threaded Programs 20

Parallel and Distributed Bounded Model Checking of Multi-thr...

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

作者： Inverso, Omar Trubiani, Catia Gran Sasso Sci Inst Laquila Italy

ISBN: (纸本)9781450368186

We introduce a structure-aware parallel technique for context-bounded analysis of concurrent programs. the key intuition consists in decomposing the set of concurrent traces into symbolic subsets that are separately explored by multiple instances of the same decision procedure running in parallel. the decision procedures work on different partitions of the search space without cooperating, whence distribution follows effortlessly. Our experiments on a selection of complex multi-threaded programs show significant analysis speedups and scalability, and greater performance gains than with general-purpose parallel solvers.

关键词： Concurrency Multithreading Sequentialization Software Verification parallel Analysis Bounded Model Checking SAT

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