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检索条件"任意字段=2003 ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming"

共 560 条记录，以下是121-130 订阅

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Design and Implementation of a High-Performance MPI for C# and the Common Language Infrastructure 08

Design and Implementation of a High-Performance MPI for C# a...

引用

acm sigplan symposium on principles and practice of parallel programming (PPoPP 08)

作者： Gregor, Douglas Lumsdaine, Andrew Indiana Univ Bloomington IN 47405 USA

ISBN: (纸本)9781595939609

As high-performance computing enters the mainstream, parallel programming mechanisms (including the Message Passing Interface, or MPI) must be supported in new environments such as C# and the Common Language Infrastructure (CLI). Making effective use of MPI with the CLI requires an interface that reflects the high-level object-oriented nature of C# and that also supports its programming idioms. However, for performance reasons, this high-level functionality must ultimately be mapped to low-level native MPI libraries. In addition to abstraction penalty concerns, avoiding unwanted overhead in this mapping process is significantly complicated by the safety and portability features of the CLI virtual machine, such as garbage collection and just-in-time compilation. In this paper, we describe our approach to using features of C# and the CLI-such as reflection, unsafe code regions, and run-time code generation-to realize an elegant, yet highly efficient, C# interface to MPI. Experimental results demonstrate that there is no appreciable overhead introduced by our approach when compared to the native MS-MPI library.

关键词： Generic programming message passing interface C#

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The Boat Hull Model: Adapting the Roofline Model to Enable Performance Prediction for parallel Computing 12

The Boat Hull Model: Adapting the Roofline Model to Enable P...

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17th acm sigplan symposium on principles and practice of parallel programming

作者： Nugteren, Cedric Corporaal, Henk Eindhoven Univ Technol NL-5600 MB Eindhoven Netherlands

ISBN: (纸本)9781450311601

Multi-core and many-core were already major trends for the past six years, and are expected to continue for the next decades. With these trends of parallel computing, it becomes increasingly difficult to decide on which architecture to run a given application. In this work, we use an algorithm classification to predict performance prior to algorithm implementation. For this purpose, we modify the roofline model to include class information. In this way, we enable architectural choice through performance prediction prior to the development of architecture specific code. The new model, the boat hull model, is demonstrated using a GPU as a target architecture. We show for 6 example algorithms that performance is predicted accurately without requiring code to be available.

关键词： Performance parallel computing performance prediction many-core accelerators the roofline model

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parallel Integer Sort: Theory and practice 24

Parallel Integer Sort: Theory and Practice

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29th acm sigplan Annual symposium on principles and practice of parallel programming (PPoPP)

作者： Dong, Xiaojun Dhulipala, Laxman Gu, Yan Sun, Yihan UC Riverside Riverside CA 92521 USA Univ Maryland Baltimore MD USA

ISBN: (纸本)9798400704352

Integer sorting is a fundamental problem in computer science. This paper studies parallel integer sort both in theory and in practice. In theory, we show tighter bounds for a class of existing practical integer sort algorithms, which provides a solid theoretical foundation for their widespread usage in practice and strong performance. In practice, we design a new integer sorting algorithm, DovetailSort, that is theoreticallyefficient and has good practical performance. In particular, DovetailSort overcomes a common challenge in existing parallel integer sorting algorithms, which is the difficulty of detecting and taking advantage of duplicate keys. The key insight in DovetailSort is to combine algorithmic ideas from both integer- and comparison-sorting algorithms. In our experiments, DovetailSort achieves competitive or better performance than existing state-of-the-art parallel integer and comparison sorting algorithms on various synthetic and real-world datasets.

关键词： Integer Sort Radix Sort parallel Algorithms

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Load Balancing on Speed

Load Balancing on Speed

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

作者： Hofmeyr, Steven Iancu, Costin Blagojevic, Filip Lawrence Berkeley Natl Lab Berkeley CA USA

ISBN: (纸本)9781605587080

To fully exploit multicore processors, applications are expected to provide a large degree of thread-level parallelism. While adequate for low core counts and their typical workloads, the current load balancing support in operating systems may not be able to achieve efficient hardware utilization for parallel workloads. Balancing run queue length globally ignores the needs of parallel applications where threads are required to make equal progress. In this paper we present a load balancing technique designed specifically for parallel applications running on multicore systems. Instead of balancing run queue length, our algorithm balances the time a thread has executed on "faster" and "slower" cores. We provide a user level implementation of speed balancing on UMA and NUMA multi-socket architectures running Linux and discuss behavior across a variety of workloads, usage scenarios and programming models. Our results indicate that speed balancing when compared to the native Linux load balancing improves performance and provides good performance isolation in all cases considered. Speed balancing is also able to provide comparable or better performance than DWRR, a fair multi-processor scheduling implementation inside the Linux kernel. Furthermore, parallel application performance is often determined by the implementation of synchronization operations and speed balancing alleviates the need for tuning the implementations of such primitives.

关键词： Experimentation Theory Performance Measurement Languages Design parallel programming Operating System Load Balancing Speed Balancing Multicore Multisocket

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Space and time efficient execution of parallel irregular computations

Space and time efficient execution of parallel irregular com...

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

作者： Fu, C Yang, T Univ of California Santa Barbara United States

Solving problems of large sizes is an important goal for parallel machines with multiple CPU and memory resources. In this paper, issues of efficient execution of overhead-sensitive parallel irregular computation under memory constraints are addressed. The irregular parallelism is modeled by task dependence graphs with mixed granularities. The trade-off in achieving both time and space efficiency is investigated. The main difficulty of designing efficient run-time system support is caused by the use of fast communication primitives available on modern parallel architectures. A run-time active memory management scheme and new scheduling techniques are proposed to improve memory utilization while retaining good time efficiency, and a theoretical analysis on correctness and performance is provided. This work is implemented in the context of RAPID system [5] which provides run-time support for parallelizing irregular code on distributed memory machines and the effectiveness of the proposed techniques is verified on sparse Cholesky and LU factorization with partial pivoting. The experimental results on Cray-T3D show that solvable problem sizes can be increased substantially under limited memory capacities and the loss of execution efficiency caused by the extra memory managing overhead is reasonable.

关键词： parallel processing systems

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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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Toward efficient and robust software speculative parallelization on multiprocessors 03

Toward efficient and robust software speculative paralleliza...

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2003 acm sigplan symposium on principles and practice of parallel programming

作者： Cintra, Marcelo Llanos, Diego R. School of Informatics University of Edinburgh Edinburgh United Kingdom Departamento de Informática Universidad de Valladolid Valladolid Spain

ISBN: (纸本)9781581135886

With speculative parallelization, code sections that cannot be fully analyzed by the compiler are aggressively executed in parallel. Hardware schemes are fast but expensive and require modifications to the processors and memory system. Software schemes require no extra hardware but can be inefficient. This paper proposes a new software-only speculative parallelization scheme. The scheme is developed after a systematic evaluation of the design options available and is shown to be efficient and robust and to outperform previously proposed schemes. The novelty and performance advantage of the scheme stem from the use of carefully tuned data structures, synchronization policies, and scheduling mechanisms. Experimental results show that our scheme has small overheads and, for applications with few or no data dependence violations, realizes on average 71% of the speedup of a manually parallelized version of the code, outperforming two recently proposed software-only speculative parallelization schemes. For applications with many data dependence violations, our performance monitors and switches can effectively curb the performance degradation.

关键词： parallel processing systems

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Transforming high-level data-parallel programs into vector operations 93

Transforming high-level data-parallel programs into vector o...

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4th acm sigplan symposium on principles and practice of parallel programming, PPOPP 1993

作者： Prins, Jan F. Palmer, Daniel W. Department of Computer Science University of North Carolina Chapel HillNC27599-3175 United States

ISBN: (纸本)0897915895

Efficient parallel execution of a high-level data-parallel language based on nested sequences, higher order functions and generalized iterators can be realized in the vector model using a suitable representation of nested sequences and a small set of transformational rules to distribute iterators through the constructs of the language. © 1993 acm.

关键词： Metadata

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PLUM: Static parallel Program Locality Analysis under Uniform Multiplexing 20

PLUM: Static Parallel Program Locality Analysis under Unifor...

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

作者： Liu, Fangzhou Chen, Dong Smith, Wesley Ding, Chen Univ Rochester Rochester NY 14627 USA Natl Univ Def Technol Changsha Peoples R China

ISBN: (纸本)9781450368186

Data movement has a significant impact on program performance. For multithread programs, this impact is amplified, since different threads often interfere with each other by competing for shared cache space. However, recent de facto locality metrics consider either sequential execution only, or derive locality for multithread programs in an inefficient way, i.e. exhaustive simulation. This paper presents PLUM, a compiler solution for timescale locality analysis for parallel programs. Experiments demonstrate that the prediction accuracy is 93.97% on average. PLUM is the first tool that analyzes data locality for parallel programs during compile time;in addition, it provides an approach for efficiently studying the representative interleaving pattern for parallel executions.

关键词： Static analysis Locality Multithread

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Exploiting Vector and Multicore parallelism for Recursive, Data- and Task-parallel Programs 17

Exploiting Vector and Multicore Parallelism for Recursive, D...

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22nd acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Ren, Bin Krishnamoorthy, Sriram Agrawal, Kunal Kulkarni, Milind Coll William & Mary Williamsburg VA 23187 USA Pacific Northwest Natl Labs Richland WA USA Washington Univ St Louis St Louis MO USA Purdue Univ W Lafayette IN 47907 USA

ISBN: (纸本)9781450344937

Modern hardware contains parallel execution resources that are well-suited for data-parallelism vector units and task parallelism multicores. However, most work on parallel scheduling focuses on one type of hardware or the other. In this work, we present a scheduling framework that allows for a unified treatment of task- and data-parallelism. Our key insight is an abstraction, task blocks, that uniformly handles data-parallel iterations and task-parallel tasks, allowing them to be scheduled on vector units or executed independently as multicores. Our framework allows us to define schedulers that can dynamically select between executing task blocks on vector units or multicores. We show that these schedulers are asymptotically optimal, and deliver the maximum amount of parallelism available in computation trees. To evaluate our schedulers, we develop program transformations that can convert mixed data- and task-parallel programs into task block based programs. Using a prototype instantiation of our scheduling framework, we show that, on an 8-core system, we can simultaneously exploit vector and multicore parallelism to achieve 14 x-108 x speedup over sequential baselines.

关键词： Task parallelism Data parallelism General Scheduler

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