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Object-oriented stream programming using aspects

Object-oriented stream programming using aspects

引用

24th IEEE International parallel and Distributed Processing symposium, IPDPS 2010

作者： Wang, Mingliang Parashar, Manish Rutgers University 94 Brett Road Piscataway NJ 08854 United States

ISBN: (纸本)9781424464432

High-performance parallel programs that efficiently utilize heterogeneous CPU+GPU accelerator systems require tuned coordination among multiple program units. However, using current programming frameworks such as CUDA leads to tangled source code that combines code for the core computation with that for device and computational kernel management, data transfers between memory spaces, and various optimizations. In this paper, we propose a programming system based on the principles of Aspect-Oriented programming, to un-clutter the code and to improve programmability of these heterogeneous parallel systems. Specifically, we use standard C++ to describe the core computations and aspects to encapsulate all other support parts. An aspect-weaving compiler is then used to combine these two pieces of code to generate a final program. the system modularizes concerns that are hard to manage using conventional programming frameworks such as CUDA, has a small impact on existing program structure as well as performance, and as a result, simplifies the programming of accelerator-based heterogeneous parallel systems. We also present an options pricing and an n-body simulation example program to demonstrate that programs written using this system can be successfully translated to CUDA programs for NVIDIA GPU hardware and to OpenCL programs for multicore CPUs with comparable performance. For both examples, the performance of the translated code achieved ~80% of the hand-coded CUDA programs. © 2010 IEEE.

关键词： Data transfer

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Load Balancing on Speed

Load Balancing on Speed

引用

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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OPTIMAL MAPPING OF SEQUENCES OF DATA-parallel TASKS 95

OPTIMAL MAPPING OF SEQUENCES OF DATA-PARALLEL TASKS

引用

5th ACM SIGPLAN symposium on principles and practice of parallel programming

作者： SUBHLOK, J VONDRAN, G HEWLETT PACKARD CORP ADV LASER JET OPERAT BOISE ID 83714 USA

ISBN: (纸本)9780897917001

Many applications in a variety of domains including digital signal processing, image processing, and computer vision are composed of a sequence of tasks that act on a stream of input data sets in a pipelined manner. Recent research has established that these applications are best mapped to a massively parallel machine by dividing the tasks into modules and assigning a subset of the available processors to each module. this paper addresses the problem of optimally mapping such applications onto a massively parallel machine. We formulate the problem of optimizing throughput in task pipelines and present two new solution algorithms. the formulation uses a general and realistic model for inter-task communication, takes memory constraints into account, and addresses the entire problem of mapping which includes clustering tasks into modules, assignment of processors to modules, and possible replication of modules. the first algorithm is based on dynamic programming and finds the optimal mapping of k tasks onto P processors in O(P(4)k(2)) time. We also present a heuristic algorithm that is linear in the number of processors and establish with theoretical and practical results that the solutions obtained are optimal in practical situations. the entire framework is implemented as an automatic mapping tool for the Fx parallelizing compiler for High Performance Fortran. We present experimental results that demonstrate the importance of choosing a good mapping and show that the methods presented yield efficient mappings and predict optimal performance accurately.

关键词： parallel processing systems

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parallel execution of multi-set constraint rewrite rules 08

Parallel execution of multi-set constraint rewrite rules

引用

PPDP 2008: 10th International ACM SIGPLAN symposium on principles and practice of Declarative programming

作者： Sulzmann, Martin Lam, Edmund S. L. Programming Logics and Semantics Group IT University of Copenhagen Rued Langgaards Vej 7 2300 Copenhagen S Denmark School of Computing National University of Singapore S16 Level 5 3 Science Drive 2 Singapore 117543 Singapore

ISBN: (纸本)9781605581170

Multi-set constraint rewriting allows for a highly parallel computational model and has been used in a multitude of application domains such as constraint solving, agent specification etc. Rewriting steps can be applied simultaneously as long as they do not interfere with each other. We wish that the underlying constraint rewrite implementation executes rewrite steps in parallel on increasingly popular becoming multi-core architectures. We design and implement efficient algorithms which allow for the parallel execution of multi-set constraint rewrite rules. Our experiments show that we obtain some significant speed-ups on multi-core architectures. Copyright © 2008 ACM.

关键词： Computer architecture

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parallel Block-Delayed Sequences 22

Parallel Block-Delayed Sequences

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

作者： Westrick, Sam Rainey, Mike Anderson, Daniel Blelloch, Guy E. Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9781450392044

programming languages using functions on collections of values, such as map, reduce, scan and filter, have been used for over fifty years. Such collections have proven to be particularly useful in the context of parallelism because such functions are naturally parallel. However, if implemented naively they lead to the generation of temporary intermediate collections that can significantly increase memory usage and runtime. To avoid this pitfall, many approaches use "fusion" to combine operations and avoid temporary results. However, most of these approaches involve significant changes to a compiler and are limited to a small set of functions, such as maps and reduces. In this paper we present a library-based approach that fuses widely used operations such as scans, filters, and flattens. In conjunction with existing techniques, this covers most of the common operations on collections. Our approach is based on a novel technique which parallelizes over blocks, with streams within each block. We demonstrate the approach by implementing libraries targeting multicore parallelism in two languages: parallel ML and C++, which have very different semantics and compilers. To help users understand when to use the approach, we define a cost semantics that indicates when fusion occurs and how it reduces memory allocations. We present experimental results for a dozen benchmarks that demonstrate significant reductions in both time and space. In most cases the approach generates code that is near optimal for the machines it is running on.

关键词： parallel programming fusion collections functional programming

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Space and time efficient execution of parallel irregular computations

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

引用

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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Interaction of parallel programming constructs and coherence protocols

Interaction of parallel programming constructs and coherence...

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proceedings of the 1997 6th ACM SIGPLAN symposium on principles and practice of parallel programming

作者： Bianchini, Ricardo Carrera, Enrique V. Kontothanassis, Leonidas Federal Univ of Rio de Janeiro Rio de Janeiro Brazil

Some of the most common parallel programming idioms include locks, barriers, and reduction operations. the interaction of these programming idioms with the multiprocessor's coherence protocol has a significant impact on performance. In addition, the advent of machines that support multiple coherence protocols prompts the question of how to best implement such parallel constructs, i.e. what combination of implementation and coherence protocol yields the best performance. In this paper we study the running time and communication behavior of (1) centralized (ticket) and MCS spin locks, (2) centralized, dissemination, and tree-based barriers, and (3) parallel and sequential reductions, under pure and competitive update coherence protocols;results for write-invalidate protocol are presented mostly for comparison purposes. Our experiments indicate that parallel programming techniques that are well-established for write invalidate protocols, such as MCS locks and parallel reductions, are often inappropriate for update-based protocols. In contrast, techniques such as dissemination and tree barriers achieve superior performance under update-based protocols. Our results also show that the implementation of parallel programming idioms must take the coherence protocol into account, since update-based protocols often lead to different design decisions than write invalidate protocols. Our main conclusion is that protocol-conscious implementation of parallel programming structures can significantly improve application performance;for multiprocessors that can support more than one coherence protocol both the protocol and implementation should be taken into account when exploiting parallel constructs.

关键词： parallel processing systems

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Statistical scalability analysis of communication operations in distributed applications 01

Statistical scalability analysis of communication operations...

引用

8th ACM SIGPLAN symposium on the principles and practice of parallel Computing

作者： Vetter, JS McCracken, MO Lawrence Livermore Natl Lab Ctr Appl Sci Comp Livermore CA 94551 USA

ISBN: (纸本)9781581133462

Current trends in high performance computing suggest that users will soon have widespread access to clusters of multiprocessors with hundreds, if not thousands, of processors. this unprecedented degree of parallelism will undoubtedly expose scalability limitations in existing applications, where scalability is the ability of a parallel algorithm on a parallel architecture to effectively utilize an increasing number of processors. Users will need precise and automated techniques for detecting the cause of limited scalability. this paper addresses this dilemma. First, we argue that users face numerous challenges in understanding application scalability: managing substantial amounts of experiment data, extracting useful trends from this data, and reconciling performance information with their application's design. Second, we propose a solution to automate this data analysis problem by applying fundamental statistical techniques to scalability experiment data. Finally, we evaluate our operational prototype on several applications, and show that statistical techniques offer an effective strategy for assessing application scalability. In particular, we find that non-parametric correlation of the number of tasks to the ratio of the time for communication operations to overall communication time provides a reliable measure for identifying communication operations that scale poorly.

关键词： Scalability Experimental data statistical techniques Consumers Communication Research Automated recording parallel architectures Surgery Multiprocessor High Performance Computing parallel algorithms

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principles and practice of Constraint programming 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： John Hooker

ISBN: (数字)9783319983349

ISBN: (纸本)9783319983332

this book constitutes the proceedings of the 24th International Conference on principles and practice of Constraint programming, CP 2018, held in Lille, France, in August *** 41 full and 9 short papers presented in this volume were carefully reviewed and selected from 114 submissions. they deal with all aspects of computing with constraints including theory, algorithms, environments, languages, models, systems, and applications such as decision making, resource allocation, scheduling, configuration, and planning. the papers were organized according to the following topics/tracks: main technical track; applications track; CP and data science; CP and music; CP and operations research; CP, optimization and power system management; multiagent and parallel CP; and testing and verification.

关键词： Mathematical Logic and Formal Languages Mathematics of Computing Artificial Intelligence Software Engineering/programming and Operating Systems Data Structures and Information theory Computer Systems Organization and Communication Networks

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A parallel SAT-Based Framework for Closed Frequent Itemsets Mining 1

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24th International Conference on the principles and practice of Constraint programming (CP)

作者： Dlala, Imen Ouled Jabbour, Said Raddaoui, Badran Sais, Lakhdar Univ Artois CNRS CRIL F-62307 Lens France Univ Paris Saclay CNRS SAMOVAR Telecom SudParis Evry France Univ Tunis LARODEC Tunis Tunisia

ISBN: (数字)9783319983349

ISBN: (纸本)9783319983349;9783319983332

Constraint programming (CP) and propositional satisfiability (SAT) based framework for modeling and solving pattern mining tasks has gained a considerable audience in recent years. However, this nice declarative and generic framework encounters a scaling problem. the huge size of constraints networks/propositional formulas encoding large datasets is identified as the main bottleneck of most existing approaches. In this paper, we propose a parallel SAT based framework for itemset mining problem to push forward the solving efficiency. the proposed approach is based on a divide-and-conquer paradigm, where the transaction database is partitioned using item-based guiding paths. Such decomposition allows us to derive smaller and independent Boolean formulas that can be solved in parallel. the performance and scalability of the proposed algorithm are evaluated through extensive experiments on several datasets. We demonstrate that our partition-based parallel SAT approach outperforms other CP approaches even in the sequential case, while significantly reducing the performances gap with specialized approaches.

关键词： Constraint programming

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