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Advanced synchronization techniques for task-based runtime systems 21

Advanced synchronization techniques for task-based runtime s...

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

作者： Álvarez, David Sala, Kevin Maroñas, Marcos Roca, Aleix Beltran, Vincenç Barcelona Supercomputing Center Barcelona Spain

ISBN: (纸本)9781450382946

Task-based programming models like OmpSs-2 and OpenMP provide a flexible data-flow execution model to exploit dynamic, irregular and nested parallelism. Providing an efficient implementation that scales well with small granularity tasks remains a challenge, and bottlenecks can manifest in several runtime components. In this paper, we analyze the limiting factors in the scalability of a task-based runtime system and propose individual solutions for each of the challenges, including a wait-free dependency system and a novel scalable scheduler design based on delegation. We evaluate how the optimizations impact the overall performance of the runtime, both individually and in combination. We also compare the resulting runtime against state of the art OpenMP implementations, showing equivalent or better performance, especially for fine-grained tasks. © 2021 acm.

关键词： parallel programming

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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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Dynamic pointer alignment: tiling and communication optimizations for parallel pointer-based computations

Dynamic pointer alignment: tiling and communication optimiza...

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

作者： Zhang, Xingbin Chien, Andrew A. Univ of Illinois at Urbana-Champaign

Loop tiling and communication optimizations, such as message pipelining and aggregation, can achieve optimized and robust memory performance by proactively managing storage and data movement. In this paper, we generalize these techniques to pointer-based data structures (PBDSs). Our approach, dynamic pointer alignment (DPA), has two components. the compiler decomposes a program into non-blocking threads that operate on specific pointers and labels thread creation sites with their corresponding pointers. At runtime, an explicit mapping from pointers to dependent threads is updated at thread creation and is used to dynamically schedule both threads and communication, such that threads using the same objects execute together, communication overlaps with local work, and messages are aggregated. We have implemented DPA to optimize remote reads to global PBDSs on parallel machines. Our empirical results on the force computation phases of two applications that use sophisticated PBDSs, Barnes-Hut and FMM, show that DPA achieves good absolute performance and speedups by enabling tiling and communication optimizations on the CRAY T3D.

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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Contention elimination by replication of sequential sections in distributed shared memory programs 01

Contention elimination by replication of sequential sections...

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8th acm sigplan symposium on principles and practice of parallel programming

作者： Lu, H. Cox, A.L. Zwaenepoel, W. Department of Computer Science Rice University Houston TX 77005 United States

ISBN: (纸本)9781581133462

In shared memory programs contention often occurs at the transition between a sequential and a parallel section of the code. As all threads start executing the parallel section, they often access data just modified by the thread that executed the sequential section, causing a flurry of data requests to converge on that processor. We address this problem in a software distributed shared memory system by replicating the execution of the sequential sections on all processors. Communication during this replicated sequential execution is reduced by using multicast. We have implemented replicated sequential execution with multicast support in OpenMP/NOW, a version of of OpenMP that runs on networks of workstations. We do not rely on compile-time data analysis, and therefore we can handle irregular and pointer-based applications. We show significant improvement for two pointer-based applications that suffer from severe contention without replicated sequential execution.

关键词： parallel processing systems

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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...

引用

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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Portable parallel Performance from Sequential, Productive, Embedded Domain-Specific Languages 12

Portable Parallel Performance from Sequential, Productive, E...

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

作者： Kamil, Shoaib Coetzee, Derrick Beamer, Scott Cook, Henry Gonina, Ekaterina Harper, Jonathan Morlan, Jeffrey Fox, Armando Univ Calif Berkeley Berkeley CA 94720 USA Mississippi State Univ Mississippi State MS USA

ISBN: (纸本)9781450311601

Domain-expert productivity programmers desire scalable application performance, but usually must rely on efficiency programmers who are experts in explicit parallel programming to achieve it. Since such programmers are rare, to maximize reuse of their work we propose encapsulating their strategies in mini-compilers for domain-specific embedded languages (DSELs) glued together by a common high-level host language familiar to productivity programmers. the nontrivial applications that use these DSELs perform up to 98% of peak attainable performance, and comparable to or better than existing hand-coded implementations. Our approach is unique in that each mini-compiler not only performs conventional compiler transformations and optimizations, but includes imperative procedural code that captures an efficiency expert's strategy for mapping a narrow domain onto a specific type of hardware. the result is source-and performance-portability for productivity programmers and parallel performance that rivals that of hand-coded efficiency-language implementations of the same applications. We describe a framework that supports our methodology and five implemented DSELs supporting common computation kernels. Our results demonstrate that for several interesting classes of problems, efficiency-level parallel performance can be achieved by packaging efficiency programmers' expertise in a reusable framework that is easy to use for both productivity programmers and efficiency programmers.

关键词： Design Languages Performance Asp SEJITS Python Domain-Specific Languages

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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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PHANTOM: Predicting Performance of parallel Applications on Large-Scale parallel Machines Using a Single Node

PHANTOM: Predicting Performance of Parallel Applications on ...

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

作者： Zhai, Jidong Chen, Wenguang Zheng, Weimin Tsinghua Univ Tsinghua Natl Lab Informat Sci & Technol Dept Comp Sci & Technol Beijing 100084 Peoples R China

ISBN: (纸本)9781605587080

For designers of large-scale parallel computers, it is greatly desired that performance of parallel applications can be predicted at the design phase. However, this is difficult because the execution time of parallel applications is determined by several factors, including sequential computation time in each process, communication time and their convolution. Despite previous efforts, it remains an open problem to estimate sequential computation time in each process accurately and efficiently for large-scale parallel applications on non-existing target machines. this paper proposes a novel approach to predict the sequential computation time accurately and efficiently. We assume that there is at least one node of the target platform but the whole target system need not be available. We make two main technical contributions. First, we employ deterministic replay techniques to execute any process of a parallel application on a single node at real speed. As a result, we can simply measure the real sequential computation time on a target node for each process one by one. Second, we observe that computation behavior of processes in parallel applications can be clustered into a few groups while processes in each group have similar computation behavior. this observation helps us reduce measurement time significantly because we only need to execute representative parallel processes instead of all of them. We have implemented a performance prediction framework, called PHANTOM, which integrates the above computation-time acquisition approach with a trace-driven network simulator. We validate our approach on several platforms. For ASCI Sweep3D, the error of our approach is less than 5% on 1024 processor cores. Compared to a recent regression-based prediction approach, PHANTOM presents better prediction accuracy across different platforms.

关键词： Performance Prediction parallel Application Deterministic Replay Trace-driven Simulation

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Ligra: A Lightweight Graph Processing Framework for Shared Memory 13

Ligra: A Lightweight Graph Processing Framework for Shared M...

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

作者： Shun, Julian Blelloch, Guy E. Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9781450319225

there has been significant recent interest in parallel frameworks for processing graphs due to their applicability in studying social networks, the Web graph, networks in biology, and unstructured meshes in scientific simulation. Due to the desire to process large graphs, these systems have emphasized the ability to run on distributed memory machines. Today, however, a single multicore server can support more than a terabyte of memory, which can fit graphs with tens or even hundreds of billions of edges. Furthermore, for graph algorithms, shared-memory multicores are generally significantly more efficient on a per core, per dollar, and per joule basis than distributed memory systems, and shared-memory algorithms tend to be simpler than their distributed counterparts. In this paper, we present a lightweight graph processing framework that is specific for shared-memory parallel/multicore machines, which makes graph traversal algorithms easy to write. the framework has two very simple routines, one for mapping over edges and one for mapping over vertices. Our routines can be applied to any subset of the vertices, which makes the framework useful for many graph traversal algorithms that operate on subsets of the vertices. Based on recent ideas used in a very fast algorithm for breadth-first search (BFS), our routines automatically adapt to the density of vertex sets. We implement several algorithms in this framework, including BFS, graph radii estimation, graph connectivity, betweenness centrality, PageRank and single-source shortest paths. Our algorithms expressed using this framework are very simple and concise, and perform almost as well as highly optimized code. Furthermore, they get good speedups on a 40-core machine and are significantly more efficient than previously reported results using graph frameworks on machines with many more cores.

关键词： Algorithms Performance Shared Memory Graph Algorithms parallel programming

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