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检索条件"任意字段=9th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming"

共 385 条记录，以下是181-190 订阅

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POSTER: Fast parallel Exact Inference on Bayesian Networks 28

POSTER: Fast Parallel Exact Inference on Bayesian Networks

引用

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...

引用

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

引用

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...

引用

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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Space-efficient implementation of nested parallelism

Space-efficient implementation of nested parallelism

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

作者： Narlikar, Girija J. Blelloch, Guy E. CMU Sch of Computer Science Pittsburgh United States

Many of today9;s high level parallel languages support dynamic, fine-grained parallelism. these languages allow the user to expose all the parallelism in the program, which is typically of a much higher degree than... 详细信息

Many of today's high level parallel languages support dynamic, fine-grained parallelism. these languages allow the user to expose all the parallelism in the program, which is typically of a much higher degree than the number of processors. Hence an efficient scheduling algorithm is required to assign computations to processors at runtime. Besides having low overheads and good load balancing, it is important for the scheduling algorithm to minimize the space usage of the parallel program. this paper presents a scheduling algorithm that is provably space-efficient and time-efficient for nested parallel languages. In addition to proving the space and time bounds of the parallel schedule generated by the algorithm, we demonstrate that it is efficient in practice. We have implemented a runtime system that uses our algorithm to schedule parallel threads. the results of executing parallel programs on this system show that our scheduling algorithm significantly reduces memory usage compared to previous techniques, without compromising performance.

关键词： parallel processing systems

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Helper Locks for Fork-Join parallel programming

Helper Locks for Fork-Join Parallel Programming

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

作者： Agrawal, Kunal Leiserson, Charles E. Sukha, Jim Washington Univ St Louis MO 63130 USA

ISBN: (纸本)9781605587080

Helper locks allow programs with large parallel critical sections, called parallel regions, to execute more efficiently by enlisting processors that might otherwise be waiting on the helper lock to aid in the execution of the parallel region. Suppose that a processor p is executing a parallel region A after having acquired the lock L protecting A. If another processor p' tries to acquire L, then instead of blocking and waiting for p to complete A, processor p' joins p to help it complete A. Additional processors not blocked on L may also help to execute A. the HELPER runtime system can execute fork-join computations augmented with helper locks and parallel regions. HELPER supports the unbounded nesting of parallel regions. We provide theoretical completion-time and space-usage bounds for a design of HELPER based on work stealing. Specifically, let V be the number of parallel regions in a computation, let T-1 be its work, and let (T) over tilde (infinity) be its "aggregate span" - the sum of the spans (critical-path lengths) of all its parallel regions. We prove that HELPER completes the computation in expected time O(T-1/P + (T) over tilde (infinity) + PV) on P processors. this bound indicates that programs with a small number of highly parallel critical sections can attain linear speedup. For the space bound, we prove that HELPER completes a program using only O(P (S) over tilde (1)) stack space, where e (S) over tilde (1) is the sum, over all regions, of the stack space used by each region in a serial execution. Finally, we describe a prototype of HELPER implemented by modifying the Cilk multithreaded runtime system. We used this prototype to implement a concurrent hash table with a resize operation protected by a helper lock.

关键词： Algorithms Performance theory Cilk fork-join multithreading helper lock nested parallelism parallel region scheduling work stealing

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Well-structured futures and cache locality 14

Well-structured futures and cache locality

引用

2014 19th acm sigplan symposium on principles and practice of parallel programming, PPoPP 2014

作者： Herlihy, Maurice Liu, Zhiyu Computer Science Department Brown University United States

ISBN: (纸本)9781450326568

In fork-join parallelism, a sequential program is split into a directed acyclic graph of tasks linked by directed dependency edges, and the tasks are executed, possibly in parallel, in an order consistent with their dependencies. A popular and effective way to extend fork-join parallelism is to allow threads to create futures. A thread creates a future to hold the results of a computation, which may or may not be executed in parallel. that result is returned when some thread touches that future, blocking if necessary until the result is ready. Recent research has shown that while futures can, of course, enhance parallelism in a structured way, they can have a deleterious effect on cache locality. In the worst case, futures can incur Ω(PT ∞ +tT∞) deviations, which implies Ω(CPT∞+CtT∞) additional cache misses, where C is the number of cache lines, P is the number of processors, t is the number of touches, and T∞ is the computation span. Since cache locality has a large impact on software performance on modern multicores, this result is troubling. In this paper, however, we show that if futures are used in a simple, disciplined way, then the situation is much better: if each future is touched only once, either by the thread that created it, or by a later descendant of the thread that created it, then parallel executions with work stealing can incur at most O(CPT2∞ ) additional cache misses, a substantial improvement. this structured use of futures is characteristic of many (but not all) parallel applications. Copyright © 2014 acm.

关键词： parallel programming

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Scalable parallel debugging with statistical assertions 12

Scalable parallel debugging with statistical assertions

引用

17th acm sigplan symposium on principles and practice of parallel programming, PPoPP'12

作者： Dinh, Minh Ngoc Abramson, David Jin, Chao Gontarek, Andrew Moench, Bob DeRose, Luiz Monash University Clayton 3800 VIC Australia Cray Inc. Saint Paul MN 55101-2987 United States

ISBN: (纸本)9781450311601

Traditional debuggers are of limited value for modern scientific codes that manipulate large complex data structures. this paper discusses a novel debug-time assertion, called a "Statistical Assertion", that allows a user to reason about large data structures, and the primitives are parallelised to provide an efficient solution. We present the design and implementation of statistical assertions, and illustrate the debugging technique with a molecular dynamics simulation. We evaluate the performance of the tool on a 12,000 cores Cray XE6.

关键词： Data structures

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Griffin: Uniting CPU and GPU in Information Retrieval Systems for Intra-Query parallelism 18

Griffin: Uniting CPU and GPU in Information Retrieval System...

引用

23rd acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Liu, Yang Wang, Jianguo Swanson, Steven WDC Res Chippenham Wilts England Univ Calif San Diego San Diego CA USA

ISBN: (纸本)9781450349826

Interactive information retrieval services, such as enterprise search and document search, must provide relevant results with consistent, low response times in the face of rapidly growing data sets and query loads. these growing demands have led researchers to consider a wide range of optimizations to reduce response latency, including query processing parallelization and acceleration with co-processors such as GPUs. However, previous work runs queries either on GPU or CPU, ignoring the fact that the best processor for a given query depends on the query's characteristics, which may change as the processing proceeds. We present Griffin, an IR systems that dynamically combines GPU- and CPU-based algorithms to process individual queries according to their characteristics. Griffin uses state-of-the-art CPU-based query processing techniques and incorporates a novel approach to GPU-based query evaluation. Our GPU-based approach, as far as we know, achieves the best available GPU search performance by leveraging a new compression scheme and exploiting an advanced merge-based intersection algorithm. We evaluate Griffin with real world queries and datasets, and show that it improves query performance by 10x compared to a highly optimized CPU-only implementation, and 1.5x compared to our GPU-approach running alone. We also find that Griffin helps reduce the 95th-, 99th-, and 99.9th-percentile query response time by 10.4x, 16.1x, and 26.8x, respectively.

关键词： Information Retrieval Search Engines Query Processing GPU parallel Algorithms

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DATA-FLOW EQUATIONS FOR EXPLICITLY parallel PROGRAMS 93

DATA-FLOW EQUATIONS FOR EXPLICITLY PARALLEL PROGRAMS

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

作者： GRUNWALD, D SRINIVASAN, H UNIV COLORADO DEPT COMP SCIBOULDERCO 80309

ISBN: (纸本)9780897915892

We present a solution to the reaching definitions problem for programs with explicit lexically specified parallel constructs, such as cobegin/coend or parallel-sections, both with and without explicit synchronization operations, such as Post, Wait or Advance. the reaching definitions information for sequential programs is used to solve many standard optimization problems. In parallel programs, this information can also be used to explicitly direct communication and data ownership. Although work has been done on analyzing parallel programs to detect data races, little work has been done on optimizing such programs. We show how the memory consistency model specified by an explicitly parallel programming language can influence the complexity of the reaching definitions problem. By selecting the ''weakest'' memory consistency semantics, we can efficiently solve the reaching definitions problem for correct programs.

关键词： Computer software

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