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the STAPL parallel Container Framework 11

The STAPL Parallel Container Framework

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16th ACM symposium on principles and practice of parallel programming

作者： Tanase, Gabriel Buss, Antal Fidel, Adam Harshvardhan Papadopoulos, Ioannis Pearce, Olga Smith, Timmie thomas, Nathan Xu, Xiabing Mourad, Nedal Vu, Jeremy Bianco, Mauro Amato, Nancy M. Rauchwerger, Lawrence Texas A&M Univ Parasol Lab Dept Comp Sci & Engn College Stn TX 77843 USA

ISBN: (纸本)9781450301190

the Standard Template Adaptive parallel Library (STAPL) is a parallel programming infrastructure that extends C++ with support for parallelism. It includes a collection of distributed data structures called pContainers that are thread-safe, concurrent objects, i.e., shared objects that provide parallel methods that can be invoked concurrently. In this work, we present the STAPL parallel Container Framework (PCF), that is designed to facilitate the development of generic parallel containers. We introduce a set of concepts and a methodology for assembling a pContainer from existing sequential or parallel containers, without requiring the programmer to deal with concurrency or data distribution issues. the PCF provides a large number of basic parallel data structures (e.g., pArray, pList, pVector, pMatrix, pGraph, pMap, pSet). the PCF provides a class hierarchy and a composition mechanism that allows users to extend and customize the current container base for improved application expressivity and performance. We evaluate STAPL pContainer performance on a CRAY XT4 massively parallel system and show that pContainer methods, generic pAlgorithms, and different applications provide good scalability on more than 16,000 processors.

关键词： parallel programming Languages Libraries Data Structures Languages Design Performance

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Provably Fast and Space-Efficient parallel Biconnectivity 23

Provably Fast and Space-Efficient Parallel Biconnectivity

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28th ACM SIGPLAN Annual symposium on principles and practice of parallel programming, PPoPP 2023

作者： Dong, Xiaojun Wang, Letong Gu, Yan Sun, Yihan UC Riverside

ISBN: (纸本)9798400700156

Computing biconnected components (BCC) of a graph is a fundamental graph problem. the canonical parallel BCC algorithm is the Tarjan-Vishkin algorithm, which has O(n + m) optimal work and polylogarithmic span on a graph with n vertices and m edges. However, Tarjan-Vishkin is not widely used in practice. We believe the reason is the space-inefficiency (it uses O(m) extra space). In practice, existing parallel implementations are based on breath-first search (BFS). Since BFS has span proportional to the diameter of the graph, existing parallel BCC implementations suffer from poor performance on large-diameter graphs and can be slower than the sequential algorithm on many real-world graphs. We propose the first p arallel b iconnectivity algorithm (FAST-BCC) that has optimal work, polylogarithmic span, and is space-efficient. Our algorithm creates a skeleton graph based on any spanning tree of the input graph. then we use the connectivity information of the skeleton to compute the biconnectivity of the original input. We carefully analyze the correctness of our algorithm, which is highly non-trivial. We implemented FAST-BCC and compared it with existing implementations, including GBBS, Slota and Madduri's algorithm, and the sequential Hopcroft-Tarjan algorithm. We tested them on a 96-core machine on 27 graphs with varying edge distributions. FAST-BCC is the fastest on all graphs. On average (geometric means), FAST-BCC is 3.1× faster than the best existing baseline on each graph. © 2023 Owner/Author.

关键词： Graphic methods

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Barrier elision for production parallel programs 2015

Barrier elision for production parallel programs

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20th ACM SIGPLAN symposium on principles and practice of parallel programming, PPoPP 2015

作者： Chabbi, Milind Lavrijsen, Wim De Jong, Wibe Sen, Koushik Mellor-Crummey, John Iancu, Costin Rice University United States Lawrence Berkeley National Laboratory United States UC Berkeley United States

ISBN: (纸本)9781450332057

Large scientific code bases are often composed of several layers of runtime libraries, implemented in multiple programming languages. In such situation, programmers often choose conservative synchronization patterns leading to suboptimal performance. In this paper, we present context-sensitive dynamic optimizations that elide barriers redundant during the program execution. In our technique, we perform data race detection alongside the program to identify redundant barriers in their calling contexts;after an initial learning, we start eliding all future instances of barriers occurring in the same calling context. We present an automatic on-the-fly optimization and a multi-pass guided optimization. We apply our techniques to NWChem - a 6 million line computational chemistry code written in C/C++/Fortran that uses several runtime libraries such as Global Arrays, ComEx, DMAPP, and MPI. Our technique elides a surprisingly high fraction of barriers (as many as 63%) in production runs. this redundancy elimination translates to application speedups as high as 14% on 2048 cores. Our techniques also provided valuable insight about the application behavior, later used by NWChem developers. Overall, we demonstrate the value of holistic context-sensitive analyses that consider the domain science in conjunction with the associated runtime software stack. Copyright 2015 ACM.

关键词： Computational chemistry

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BiPart: A parallel and deterministic hypergraph partitioner 21

BiPart: A parallel and deterministic hypergraph partitioner

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26th ACM SIGPLAN symposium on principles and practice of parallel programming, PPoPP 2021

作者： Maleki, Sepideh Agarwal, Udit Burtscher, Martin Pingali, Keshav The University of Texas Austin United States Texas State University United States

ISBN: (纸本)9781450382946

Hypergraph partitioning is used in many problem domains including VLSI design, linear algebra, Boolean satisfiability, and data mining. Most versions of this problem are NP-complete or NP-hard, so practical hypergraph partitioners generate approximate partitioning solutions for all but the smallest inputs. One way to speed up hypergraph partitioners is to exploit parallelism. However, existing parallel hypergraph partitioners are not deterministic, which is considered unacceptable in domains like VLSI design where the same partitions must be produced every time a given hypergraph is partitioned. In this paper, we describe BiPart, the first deterministic, parallel hypergraph partitioner. Experimental results show that BiPart outperforms state-of-the-art hypergraph partitioners in runtime and partition quality while generating partitions deterministically. © 2021 ACM.

关键词： Data mining

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Efficient Massively parallel Methods for Dynamic programming 2017

Efficient Massively Parallel Methods for Dynamic Programming

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49th Annual ACM-SIGACT symposium on theory of Computing (STOC)

作者： Im, Sungjin Moseley, Benjamin Sun, Xiaorui Univ Calif Elect Engn & Comp Sci 5200 N Lake Rd Merced CA 95344 USA Washington Univ Dept Comp Sci & Engn 1 Brookings Dr St Louis MO 63130 USA Univ Calif Berkeley Simons Inst Theory Comp Berkeley CA 94702 USA Simons Inst Theory Comp Berkeley CA USA

ISBN: (纸本)9781450345286

Modern science and engineering is driven by massively large data sets and its advance heavily relies on massively parallel computing platforms such as Spark, MapReduce, and Hadoop. theoretical models have been proposed to understand the power and limitations of such platforms. Recent study of developed theoretical models has led to the discovery of new algorithms that are fast and efficient in both theory and practice, thereby beginning to unlock their underlying power. Given recent promising results, the area has turned its focus on discovering widely applicable algorithmic techniques for solving problems efficiently. In this paper we make progress towards this goal by giving principles for simulating a large class of sequential dynamic programs in the distributed setting. In particular, we identify two key properties, monotonicity and decomposibility, which allow us to derive efficient distributed algorithms for problems possessing the properties. We showcase our framework by considering several core dynamic programming applications, Longest Increasing Subsequence, Optimal Binary Search Tree, and Weighted Interval Selection. For these problems, we derive algorithms yielding solutions that are arbitrarily close to the optimum, using O(1) rounds and (O) over tilde (n/m) memory on each machine where n is the input size and m is the number of machines available.

关键词： Massively parallel computing Dynamic programming

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Real-Time Matching of Antescofo Temporal Patterns 14

Real-Time Matching of <i>Antescofo</i> Temporal Patterns

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16th International symposium on principles and practice of Declarative programming (PPDP)

作者： Giavitto, Jean-Louis Echeveste, Jose IRCAM UMR STMS 9912 CNRS 1 Pl Igor Stravinsky F-75004 Paris France INRIA MuTant Project 1 Pl Igor Stravinsky F-75004 Paris France Univ Paris 06 Sorbonne Univ 1 Pl Igor Stravinsky F-75004 Paris France

ISBN: (纸本)9781450329477

online matching. Antescofo is a real-time system for performance coordination between musicians and computer processes during live music concert. ATP are used to define complex events that correspond to a combination of perceived events in the musical environment as well as arbitrary logical and metrical temporal conditions. the real-time recognition of such event is used to trigger arbitrary actions in the style of event-condition-action rules. the musical context, the rationales of temporal patterns and several illustrative examples are introduced to motivate the design of ATP. the semantics of ATP matching is defined to parallel the well-known notion of regular expression and Brzozowski's derivatives but extended to handle an infinite alphabet, arbitrary predicates, elapsing time and inhibitory conditions. this approach is compared to those developed in log auditing and for the runtime verification of realtime logics. ATP are implemented by translation into a core subset of the Antescofo domain-specific language. this compilation has proven efficient enough to avoid the extension of the real-time runtime of the language and has been validated with composers in actual pieces.

关键词： timed regular expressions event-driven programming score following timed and reactive system domain-specific language computer music Antescofo

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Data structures for task-based priority scheduling 14

Data structures for task-based priority scheduling

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2014 19th ACM SIGPLAN symposium on principles and practice of parallel programming, PPoPP 2014

作者： Wimmer, Martin Versaci, Francesco Träff, Jesper Larsson Cederman, Daniel Tsigas, Philippas Faculty of Informatics Parallel Computing Vienna University of Technology 1040 Vienna/Wien Austria Computer Science and Engineering Chalmers University of Technology 412 96 Göteborg Sweden

ISBN: (纸本)9781450326568

We present three lock-free data structures for priority task scheduling: a priority work-stealing one, a centralized one with ρ-relaxed semantics, and a hybrid one combining both concepts. With the single-source shortest path (SSSP) problem as example, we show how the different approaches affect the prioritization and provide upper bounds on the number of examined nodes. We argue that priority task scheduling allows for an intuitive and easy way to parallelize the SSSP problem, notoriously a hard task. Experimental evidence supports the good scalability of the resulting algorithm. the larger aim of this work is to understand the trade-offs between scalability and priority guarantees in task scheduling systems. We show that ρ-relaxation is a valuable technique for improving the first, while still allowing semantic constraints to be satisfied: the lock-free, hybrid κ-priority data structure can scale as well as work-stealing, while still providing strong priority scheduling guarantees, which depend on the parameter κ. Our theoretical results open up possibilities for even more scalable data structures by adopting a weaker form of ρ-relaxation, which still enables the semantic constraints to be respected.

关键词： Scalability

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LogP: Towards a realistic model of parallel computation 93

LogP: Towards a realistic model of parallel computation

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4th ACM SIGPLAN symposium on principles and practice of parallel programming, PPOPP 1993

作者： Culler, David Karp, Richard Patterson, David Sahay, Abhijit Erik Schauser, Klaus Santos, Eunice Subramonian, Ramesh Von Eicken, thorsten Computer Science Division University of California Berkeley United States International Computer Science Institute Berkeley United States

ISBN: (纸本)0897915895

A vast body of theoretical research has focused either on overly simplistic models of parallel computation, notably the PRAM, or overly specific models that have few representatives in the real world. Both kinds of models encourage exploitation of formal loopholes, rather than rewarding development of techniques that yield performance across a range of current and future parallel machines. this paper offers a new parallel machine model, called LogP, that reflects the critical technology trends underlying parallel computers. It is intended to serve as a basis for developing fast, portable parallel algorithms and to offer guidelines to machine designers. Such a model must strike a balance between detail and simplicity in order to reveal important bottlenecks without making analysis of interesting problems intractable. the model is based on four parameters that specify abstractly the computing bandwidth, the communication bandwidth, the communication delay, and the efficiency of coupling communication and computation. Portable parallel algorithms typically adapt to the machine configuration, in terms of these parameters. the utility of the model is demonstrated through examples that are implemented on the CM-5. © 1993 ACM.

关键词： parallel algorithms

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Reference idempotency analysis: A framework for optimizing speculative execution

Reference idempotency analysis: A framework for optimizing s...

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8th ACM SIGPLAN symposium on principles and practice of parallel programming

作者： Seon Wook Kim Ooi, C.-L. Eigenmann, R. Falsafi, B. Vijaykumar, T.N. Intel Corp. Champaign IL United States

Recent proposals for multithreaded architectures allow threads with unknown dependences to execute speculatively in parallel. these architectures use hardware speculative storage to buffer uncertain data, track data dependences and roll back incorrect executions. Because all memory references access the speculative storage, current proposals implement this storage using small memory structures for fast access. the limited capacity of the speculative storage causes considerable performance loss due to speculative storage overflow whenever a thread's speculative state exceeds the storage capacity. Larger threads exacerbate the over-flow problem but are preferable to smaller threads, as larger threads uncover more parallelism. In this paper, we discover a new program property called memory reference idempotency. Idempotent references need not be tracked in the speculative storage, and instead can directly access non-speculative storage (i.e., the conventional memory hierarchy). thus, we reduce the demand fo r speculative storage space. We define a formal framework for reference idempotency and present a novel compiler-assisted speculative execution model. We prove the necessary and sufficient conditions for reference idempotency using our model. We present a compiler algorithm to label idempotent memory references for the hardware. Experimental results show that for our benchmarks, over 60% of the references in non-parallelizable program sections are idempotent.

关键词： parallel processing systems

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VAPRO: Performance Variance Detection and Diagnosis for Production-Run parallel Applications 22

VAPRO: Performance Variance Detection and Diagnosis for Prod...

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

作者： Zheng, Liyan Zhai, Jidong Tang, Xiongchao Wang, Haojie Yu, Teng Jin, Yuyang Song, Shuaiwen Leon Chen, Wenguang Tsinghua Univ Beijing Peoples R China Sangfor Technol Inc Shenzhen Guangdong Peoples R China Univ Sydney Sydney NSW Australia BNRist Beijing Peoples R China

ISBN: (纸本)9781450392044

Performance variance is a serious problem for parallel applications, which can cause performance degradation and make applications' behavior hard to understand. therefore, detecting and diagnosing performance variance are of crucial importance for users and application developers. However, previous detection approaches either bring too large overhead and hurt applications' performance, or rely on nontrivial source code analysis that is impractical for production-run parallel applications. In this work, we propose VAPRO, a performance variance detection and diagnosis framework for production-run parallel applications. Our approach is based on an important observation that most parallel applications contain code snippets that are repeatedly executed with fixed workload, which can be used for performance variance detection. To effectively identify these snippets at runtime even without program source code, we introduce State Transition Graph (STG) to track program execution and then conduct lightweight workload analysis on STG to locate variance. To diagnose the detected variance, VAPRO leverages a progressive diagnosis method based on a hybrid model leveraging variance breakdown and statistical analysis. Results show that the performance overhead of VAPRO is only 1.38% on average. VAPRO can detect the variance in real applications caused by hardware bugs, memory, and IQ After fixing the detected variance, the standard deviation of the execution time is reduced by up to 73.5%. Compared with the state-of-the-art variance detection tool based on source code analysis, VAPRO achieves 30.0% higher detection coverage.

关键词： Performance Variance Anomaly Detection System Noise

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