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检索条件"任意字段=14th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming"

共 382 条记录，以下是181-190 订阅

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A library for portable and composable data locality optimizations for NUMA systems 2015

A library for portable and composable data locality optimiza...

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20th acm sigplan symposium on principles and practice of parallel programming, PPoPP 2015

作者： Majo, Zoltan Gross, thomas R. Department of Computer Science ETH Zurich Switzerland

ISBN: (纸本)9781450332057

Many recent multiprocessor systems are realized with a nonuniform memory architecture (NUMA) and accesses to remote memory locations take more time than local memory accesses. Optimizing NUMA memory system performance is difficult and costly for three principal reasons: (1) today's programming languages/libraries have no explicit support for NUMA systems, (2) NUMA optimizations are not portable, and (3) optimizations are not composable (i.e., they can become ineffective or worsen performance in environments that support composable parallel software). this paper presents TBB-NUMA, a parallel programming library based on Intel threading Building Blocks (TBB) that supports portable and composable NUMA-aware programming. TBB-NUMA provides a model of task affinity that captures a programmer's insights on mapping tasks to resources. NUMA-awareness affects all layers of the library (i.e., resource management, task scheduling, and high-level parallel algorithm templates) and requires close coupling between all these layers. Optimizations implemented with TBB-NUMA (for a set of standard benchmark programs) result in up to 44% performance improvement over standard TBB, but more important, optimized programs are portable across different NUMA architectures and preserve data locality also when composed with other parallel computations. Copyright 2015 acm.

关键词： parallel programming

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High performance synchronization algorithms for multiprogrammed multiprocessors

High performance synchronization algorithms for multiprogram...

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

作者： Wisniewski, Robert W. Kontothanassis, Leonidas I. Scott, Michael L. Univ of Rochester Rochester United States

Scalable busy-wait synchronization algorithms are essential for achieving good parallel program performance on large scale multiprocessors. Such algorithms include mutual exclusion locks, reader-writer locks, and barrier synchronization. Unfortunately, scalable synchronization algorithms are particularly sensitive to the effects of multiprogramming: their performance degrades sharply when processors are shared among different applications, or even among processes of the same application. In this paper we describe the design and evaluation of scalable scheduler-conscious mutual exclusion locks, reader-writer locks, and barriers, and show that by sharing information across the kernel/application interface we can improve the performance of scheduler-oblivious implementations by more than an order of magnitude.

关键词： parallel algorithms

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Communication-Centric Optimizations by Dynamically Detecting Collective Operations 12

Communication-Centric Optimizations by Dynamically Detecting...

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

作者： Hoefler, Torsten Schneider, Timo Univ Illinois Dept Comp Sci Urbana IL USA Tech Univ Chemnitz Dept Comp Sci Chemnitz Germany

ISBN: (纸本)9781450311601

the steady increase of parallelism in high-performance computing platforms implies that communication will be most important in large-scale applications. In this work, we tackle the problem of transparent optimization of large-scale communication patterns using online compilation techniques. We utilize the Group Operation Assembly Language (GOAL), an abstract parallel dataflow definition language, to specify our transformations in a device-independent manner. We develop fast schemes that analyze dataflow and synchronization semantics in GOAL and detect if parts of the (or the whole) communication pattern express a known collective communication operation. the detection of collective operations allows us to replace the detected patterns with highly optimized algorithms or low-level hardware calls and thus improve performance significantly. Benchmark results suggest that our technique can lead to a performance improvement of orders of magnitude compared with various optimized algorithms written in Co-Array Fortran. Detecting collective operations also improves the programmability of parallel languages in that the user does not have to understand the detailed semantics of high-level communication operations in order to generate efficient and scalable code.

关键词： Performance Languages Collective Communication parallel Compiler Optimization parallel Dataflow

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GraphCube: Interconnection Hierarchy-aware Graph Processing 24

GraphCube: Interconnection Hierarchy-aware Graph Processing

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

作者： Gan, Xinbiao Wu, Guang Qiu, Shenghao Xiong, Feng Si, Jiaqi Fang, Jianbin Dong, Dezun Gong, Chunye Li, Tiejun Wang, Zheng NUDT Beijing Peoples R China Univ Leeds Leeds W Yorkshire England Natl Supercomputer Ctr Tianjin Peoples R China

ISBN: (纸本)9798400704352

Processing large-scale graphs with billions to trillions of edges requires efficiently utilizing parallel systems. However, current graph processing engines do not scale well beyond a few tens of computing nodes because they are oblivious to the communication cost variations across the interconnection hierarchy. We introduce GraphCube, a better approach to optimizing graph processing on large-scale parallel systems with complex interconnections. GraphCube features a new graph partitioning approach to achieve better load balancing and minimize communication overhead across multiple levels of the interconnection hierarchy. We evaluate GraphCube by applying it to fundamental graph operations performed on synthetic and real-world graph datasets. Our evaluation used up to 79,024 computing nodes and 1.2+ million processor cores. Our large-scale experiments show that GraphCube outperforms state-of-the-art parallel graph processing methods in throughput and scalability. Furthermore, GraphCube outperformed the top-ranked systems on the Graph 500 list.

关键词： Graph processing Graph partitioning parallel computing Vectorization Graph500

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ZOOMM: A parallel web browser engine for multicore mobile devices 13

ZOOMM: A parallel web browser engine for multicore mobile de...

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18th acm sigplan symposium on principles and practice of parallel programming, PPoPP 2013

作者： Caşcaval, CǍlin Fowler, Seth Montesinos-Ortego, Pablo Piekarski, Wayne Reshadi, Mehrdad Robatmili, Behnam Weber, Michael Bhavsar, Vrajesh Qualcomm Research Silicon Valley Santa Clara CA United States

ISBN: (纸本)9781450319225

We explore the challenges in expressing and managing concurrency in browsers on mobile devices. Browsers are complex applications that implement multiple standards, need to support legacy behavior, and are highly dynamic and interactive. We present ZOOMM, a highly concurrent web browser engine prototype and show how concurrency is effectively exploited at different levels: speed up computation performance, preload network resources, and preprocess resources outside the critical path of page loading. On a dual-core Android mobile device we demonstrate that ZOOMM is two times faster than the native WebKit based browser when loading the set of pages defined in the Vellamo benchmark. © 2013 acm.

关键词： Web browsers

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Evaluating the locality benefits of active messages

Evaluating the locality benefits of active messages

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

作者： Spertus, Ellen Dally, William J. Massachusetts Inst of Technology Cambridge United States

A major challenge in fine-grained computing is achieving locality without excessive scheduling overhead. We built two J-Machine implementations of a fine-grained programming model, the Berkeley threaded Abstract Machine. One implementation takes an Active Messages approach, maintaining a scheduling hierarchy in software in order to improve data cache performance. Another approach relies on the J-Machine's message queues and fast task switch, lowering the control costs at the expense of data locality. Our analysis measures the costs and benefits of each approach, for a variety of programs and cache configurations. the Active Messages implementation is strongest when miss penalties are high and for the finest-grained programs. the hardware-buffered implementation is strongest in direct-mapped caches, where it achieves substantially better instruction cache performance.

关键词： parallel processing systems

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POSTER: Fast parallel Exact Inference on Bayesian Networks 28

POSTER: Fast Parallel Exact Inference on Bayesian Networks

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28th acm sigplan Annual symposium on principles and practice of parallel programming, PPoPP 2023

作者： Jiang, Jiantong Wen, Zeyi Mansoor, Atif Mian, Ajmal The University of Western Australia Australia Hong Kong University of Science and Technology Guangzhou China

ISBN: (纸本)9798400700156

Bayesian networks (BNs) are attractive, because they are graphical and interpretable machine learning models. However, exact inference on BNs is time-consuming, especially for complex problems. To improve the efficiency, we propose a fast BN exact inference solution named Fast-BNI on multi-core CPUs. Fast-BNI enhances the efficiency of exact inference through hybrid parallelism that tightly integrates coarse- and fine-grained parallelism. We also propose techniques to further simplify the bottleneck operations of BN exact inference. Fast-BNI source code is freely available at https://***/jjiantong/FastBN. © 2023 Owner/Author.

关键词： Bayesian networks

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PERFLOW: A Domain Specific Framework for Automatic Performance Analysis of parallel Applications 22

PERFLOW: A Domain Specific Framework for Automatic Performan...

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

作者： Jin, Yuyang Wang, Haojie Zhong, Runxin Zhang, Chen Zhai, Jidong Tsinghua Univ Beijing Peoples R China

ISBN: (纸本)9781450392044

Performance analysis is widely used to identify performance issues of parallel applications. However, complex communications and data dependence, as well as the interactions between different kinds of performance issues make high-efficiency performance analysis even harder. Although a large number of performance tools have been designed, accurately pinpointing root causes for such complex performance issues still needs specific in-depth analysis. To implement each such analysis, significant human efforts and domain knowledge are normally required. To reduce the burden of implementing accurate performance analysis, we propose a domain specific programming framework, named PERFLOW. PERFLOW abstracts the step-by-step process of performance analysis as a dataflow graph. this dataflow graph consists of main performance analysis sub-tasks, called passes, which can either be provided by PERFLOW'S built-in analysis library, or be implemented by developers to meet their requirements. Moreover, to achieve effective analysis, we propose a Program Abstraction Graph to represent the performance of a program execution and then leverage various graph algorithms to automate the analysis. We demonstrate the efficacy of PERFLOW by three case studies of real-world applications with up to 700K lines of code. Results show that PERFLOW significantly eases the implementation of customized analysis tasks. In addition, PERFLOW is able to perform analysis and locate performance bugs automatically and effectively.

关键词： Performance Analysis Domain Specific Framework Dataflow Graph

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Data and computation transformations for multiprocessors

Data and computation transformations for multiprocessors

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

作者： Anderson, Jennifer M. Amarasinghe, Saman P. Lam, Monica S. Stanford Univ Stanford United States

Effective memory hierarchy utilization is critical to the performance of modem multiprocessor architectures. We have developed the first compiler system that fully automatically parallelizes sequential programs and changes the original array layouts to improve memory system performance. Our optimization algorithm consists of two steps. the first step chooses the parallelization and computation assignment such that synchronization and data sharing are minimized. the second step then restructures the layout of the data in the shared address space with an algorithm that is based on a new data transformation framework. We ran our compiler on a set of application programs and measured their performance on the Stanford DASH multiprocessor. Our results show that the compiler can effectively optimize parallelism in conjunction with memory subsystem performance.

关键词： parallel processing systems

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GOPipe: A granularity-oblivious programming framework for pipelined stencil executions on GPU 19

GOPipe: A granularity-oblivious programming framework for pi...

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24th acm sigplan symposium on principles and practice of parallel programming, PPoPP 2019

作者： Oh, Chanyoung Zheng, Zhen Shen, Xipeng Zhai, Jidong Yi, Youngmin University of Seoul Korea Republic of Tsinghua University China North Carolina State University United States

ISBN: (纸本)9781450362252

Recent studies have shown promising performance benefits of pipelined stencil applications. An important factor for the computing eficiency of such pipelines is the granularity of a task. We presents GOPipe, the first granularity-oblivious programming framework for eficient pipelined stencil executions. With GOPipe, programmers no longer need to specify the appropriate task granularity. GOPipe automatically finds it, and schedules tasks of that granularity while observing all inter-task and inter-stage data dependencies. In our experiments on four real-life applications, GOPipe outperforms the state-of-the-art by up to 4.57× with a much better programming productivity. © 2019 Copyright held by the owner/author(s).

关键词： Graphics processing unit

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