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Deterministic parallel Random-Number Generation for Dynamic-Multithreading Platforms 12

Deterministic Parallel Random-Number Generation for Dynamic-...

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

作者： Leiserson, Charles E. Schardl, Tao B. Sukha, Jim MIT Comp Sci & Artificial Intelligence Lab Cambridge MA 02139 USA

ISBN: (纸本)9781450311601

Existing concurrency platforms for dynamic multithreading do not provide repeatable parallel random-number generators. this paper proposes that a mechanism called pedigrees be built into the runtime system to enable efficient deterministic parallel random-number generation. Experiments with the open-source MIT Cilk runtime system show that the overhead for maintaining pedigrees is negligible. Specifically, on a suite of 10 benchmarks, the relative overhead of Cilk with pedigrees to the original Cilk has a geometric mean of less than 1%. We persuaded Intel to modify its commercial C/C++ compiler, which provides the Cilk Plus concurrency platform, to include pedigrees, and we built a library implementation of a deterministic parallel random-number generator called DOTMIX that compresses the pedigree and then "RC6-mixes" the result. the statistical quality of DOTMIX is comparable to that of the popular Mersenne twister, but somewhat slower than a nondeterministic parallel version of this efficient and high-quality serial random-number generator. the cost of calling DOTMIX depends on the "spawn depth" of the invocation. For a naive Fibonacci calculation with n = 40 that calls DOTMIX in every node of the computation, this "price of determinism" is about a factor of 2.3 in running time over the nondeterministic Mersenne twister, but for more realistic applications with less intense use of random numbers - such as a maximal-independent-set algorithm, a practical samplesort program, and a Monte Carlo discrete-hedging application from QuantLib - the observed "price" was at most 2 1%, and sometimes much less. Moreover, even if overheads were several times greater, applications using DOTMIX should be amply fast for debugging purposes, which is a major reason for desiring repeatability.

关键词： Algorithms Performance theory Cilk determinism dynamic multithreading nondeterminism parallel computing pedigree random-number generator

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ParlayANN: Scalable and Deterministic parallel Graph-Based Approximate Nearest Neighbor Search Algorithms 24

ParlayANN: Scalable and Deterministic Parallel Graph-Based A...

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

作者： Manohar, Magdalen Dobson Shen, Zheqi Blelloch, Guy E. Dhulipala, Laxman Gu, Yan Simhadri, Harsha Vardhan Sun, Yihan Carnegie Mellon Univ Pittsburgh PA 15213 USA UC Riverside Riverside CA USA Univ Maryland Baltimore MD USA Microsoft Res Redmond WA USA

ISBN: (纸本)9798400704352

Approximate nearest-neighbor search (ANNS) algorithms are a key part of the modern deep learning stack due to enabling efficient similarity search over high-dimensional vector space representations (i.e., embeddings) of data. Among various ANNS algorithms, graph-based algorithms are known to achieve the best throughput-recall tradeoffs. Despite the large scale of modern ANNS datasets, existing parallel graphbased implementations suffer from significant challenges to scale to large datasets due to heavy use of locks and other sequential bottlenecks, which 1) prevents them from efficiently scaling to a large number of processors, and 2) results in nondeterminism that is undesirable in certain applications. In this paper, we introduce ParlayANN, a library of deterministic and parallel graph-based approximate nearest neighbor search algorithms, along with a set of useful tools for developing such algorithms. In this library, we develop novel parallel implementations for four state-of-the-art graph-based ANNS algorithms that scale to billion-scale datasets. Our algorithms are deterministic and achieve high scalability across a diverse set of challenging datasets. In addition to the new algorithmic ideas, we also conduct a detailed experimental study of our new algorithms as well as two existing non-graph approaches. Our experimental results both validate the effectiveness of our new techniques, and lead to a comprehensive comparison among ANNS algorithms on large scale datasets with a list of interesting findings.

关键词： nearest neighbor search vector search parallel algorithms

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Efficient Race Detection with Futures 19

Efficient Race Detection with Futures

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24th acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Utterback, Robert Agrawal, Kunal Fineman, Jeremy Lee, I-Ting Angelina Monmouth Coll Monmouth IL 61462 USA Washington Univ St Louis MO 14263 USA Georgetown Univ Washington DC 20057 USA

ISBN: (纸本)9781450362252

this paper addresses the problem of provably efficient and practically good on-the-fly determinacy race detection in task parallel programs that use futures. Prior works on determinacy race detection have mostly focused on either task parallel programs that follow a series-parallel dependence structure or ones with unrestricted use of futures that generate arbitrary dependences. In this work, we consider a restricted use of futures and show that we can detect races more efficiently than with general use of futures. Specifically, we present two algorithms: MultiBags and MultiBags+. MultiBags targets programs that use futures in a restricted fashion and runs in time O(T-1 alpha(m, n)), where T-1 is the sequential running time of the program, a is the inverse Ackermann's function, m is the total number of memory accesses, n is the dynamic count of places at which parallelism is created. Since a is a very slowly growing function (upper bounded by 4 for all practical purposes), it can be treated as a close-to-constant overhead. MultiBags+ is an extension of MultiBags that target programs with general use of futures. It runs in time O((T-1 + k(2))alpha(m, n)) where T-1, alpha, m and n are defined as before, and k is the number of future operations in the computation. We implemented both algorithms and empirically demonstrate their efficiency.

关键词： dynamic program analysis determinacy race race detection series-parallel maintenance

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AN EQUATIONAL LANGUAGE FOR DATA-parallelISM 93

AN EQUATIONAL LANGUAGE FOR DATA-PARALLELISM

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4th SYMP ON principles AND practice OF parallel programming ( PPOPP )

作者： RAO, P WALINSKY, C PORTLAND GRP WILSONVILLEOR 97070 DARTMOUTH COLL HANOVERNH 03755

ISBN: (纸本)9780897915892

Data-parallelism provides a clean conceptual framework for parallel programming. We are developing two programming languages: a high level equational language, called EL*, and a low-level implementation language. Both languages exploit data-parallelism instead of control-parallelism. EL* is a declarative data-parallel language. EL* programs are high-level equational specifications that use extensive pattern-matching and recursion. the language's syntax and semantics are intended to be clear and simple. Recursive forms are restricted to enable translation to efficient data-parallel operations. EL* programs are compiled into FP*, a variant of Backus's FP, where parallel operations are more explicit and low-level. the target language has a rich set of functions for performing communication, and computation. It also has a powerful set of combining forms that generate large highly-parallel functions from smaller program units. Prototype compilers have been implemented for both languages, and they demonstrate good performance. Several linear algebra and non-numeric problems have been programmed with relative ease using EL*. We are currently developing compilation techniques for a wider range of scientific problems that have more complex parallel solutions, and are continuing to expand the language's scope.

关键词： parallel programming

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LoPC: modeling contention in parallel algorithms

LoPC: modeling contention in parallel algorithms

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Proceedings of the 1997 6th acm sigplan symposium on principles and practice of parallel programming

作者： Frank, Matthew I. Agarwal, Anant Vernon, Mary K. Massachusetts Inst of Technology Cambridge United States

parallel algorithm designers need computational models that take first order system costs into account, but are also simple enough to use in practice. this paper introduces the LoPC model, which is inspired by the LogP model but accounts for contention for message processing resources in parallel algorithms on a multiprocessor or network of workstations. LoPC takes the L, o and P parameters directly from the LogP model and uses them to predict the cost of contention, C. this paper defines the LoPC model and derives the general form of the model for parallel applications that communicate via active messages. Model modifications for systems that implement coherent shared memory abstractions are also discussed. We carry out the analysis for two important classes of applications that have irregular communication. In the case of parallel applications with homogeneous all-to-any communication, such as sparse matrix computations, the analysis yields a simple rule of thumb and insight into contention costs. In the case of parallel client-server algorithms, the LoPC analysis provides a simple and accurate calculation of the optimal allocation of nodes between clients and servers. the LoPC estimates for these applications are shown to be accurate when compared against event driven simulation and against a sparse matrix computation on the MIT Alewife multiprocessor.

关键词： parallel algorithms

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High performance fortran without templates: An alternative model for distribution and alignment 93

High performance fortran without templates: An alternative m...

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

作者： Chapman, Barbara M. Mehrotra, Piyush Zima, Hans P. Department for Software Technology and Parallel Systems University of Vienna Austria ICASE MS 132C NASA Langley Research Center HamptonVA23681 United States

ISBN: (纸本)0897915895

Language extensions of Fortran are being developed which permit the user to map data structures to the individual processors of distributed memory machines. these languages allow a programming style in which global data references are used. Current efforts are fo-cussed on designing a common basis for such languages, the result of which is known as High Performance For-tran (HPF). One of the central debates in the HPF effort revolves around the concept of templates, introduced as an abstract index space to which data could be aligned. In this paper, we present a model for the mapping of data which provides the functionality of High Performance Fortran distributions without the use of templates. © 1993 acm.

关键词： FORTRAN (programming language)

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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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Software caching and computation migration in Olden 95

Software caching and computation migration in Olden

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Proceedings of the 5th acm sigplan symposium on principles and practice of parallel programming

作者： Carlisle, Martin C. Rogers, Anne Princeton Univ Princeton NJ United States

ISBN: (纸本)9780897917001

the goal of the Olden project is to build a system that provides parallelism for general purpose C programs with minimal programmer annotations. We focus on programs using dynamic structures such as trees, lists, and DAGs. We demonstrate that providing both software caching and computation migration can improve the performance of these programs, and provide a compile-time heuristic that selects between them for each pointer dereference. We have implemented a prototype system on the thinking Machines CM-5. We describe our implementation and report on experiments with ten benchmarks.

关键词： parallel processing systems

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On the parallel I/O optimality of linear algebra kernels: Near-optimal LU factorization 21

On the parallel I/O optimality of linear algebra kernels: Ne...

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26th acm sigplan symposium on principles and practice of parallel programming, PPoPP 2021

作者： Kwasniewski, Grzegorz Ben-Nun, Tal Ziogas, Alexandros Nikolaos Schneider, Timo Besta, MacIej Hoefler, Torsten Timo Schneider Maciej Besta Torsten Hoefler Department of Computer Science Eth Zurich Switzerland

ISBN: (纸本)9781450382946

Dense linear algebra kernels are fundamental components of many scientific computing applications. In this work we present a novel method of deriving parallel I/O lower bounds for this broad family of programs. Based on the X-Partitioning abstraction, our method explicitly captures inter-statement dependencies. Applying our analysis to LU factorization, we derive COnfLUX, an LU algorithm with the parallel I/O cost of N3/([EQUATION]) communicated elements per processor - only 1/3× over our established lower bound. We evaluate COnfLUX on various problem sizes, demonstrating empirical results that match our theoretical analysis, communicating less than Cray ScaLAPACK, SLATE, and the asymptotically-optimal CANDMC library. Running on 1,024 nodes of Piz Daint, COnfLUX communicates 1.6× less than the second-best implementation and is expected to communicate 2.1× less on a full-scale run on Summit. © 2021 Owner/Author.

关键词： Factorization

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Experiences using the parascope editor: An interactive parallel programming tool 93

Experiences using the parascope editor: An interactive paral...

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

作者： Hall, Mary W. Harvey, Timothy J. Kennedy, Ken McIntosh, Nathaniel McKinley, Kathryn S. Oldham, Jeffrey D. Paleczny, Michael H. Roth, Gerald Center for Integrated Systems Stanford University Palo AltoCA94305 United States Department of Computer Science Rice University HoustonTX77251-1892 United States 35 rue Saint Honoré Fontainebleau CedexF-77305 France

ISBN: (纸本)0897915895

the ParaScope Editor is an interactive parallel programming tool that assists knowledgeable users in developing scientific Fortran programs. It displays the results of sophisticated program analyses, provides a set of powerful interactive transformations, and supports program editing. this paper summarizes experiences of scientific programmers and tool designers using the ParaScope Editor. We evaluate existing features and describe enhancements in three key areas: user interface, analysis, and transformation. Many existing features prove crucial to successful program parallelization. they include interprocedural array side-effect analysis and program and dependence view filtering. Desirable functionality includes improved program navigation based on performance estimation, incorporating user assertions in analysis and more guidance in selecting transformations. these results offer insights for the authors of a variety of programming tools and parallelizing compilers. © 1993 acm.

关键词： parallel programming

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