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Poster: the Problem-Based Benchmark Suite PBBS), V2 27

Poster: The Problem-Based Benchmark Suite PBBS), V2

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

作者： Anderson, Daniel Blelloch, Guy E. Dhulipala, Laxman Dobson, Magdalen Sun, Yihan Carnegie Mellon Univ Pittsburgh Pittsburgh PA USA Univ Maryland Coll Park MD USA UC Riverside Riverside Riverside CA USA

ISBN: (纸本)9781450392044

the Problem-Based Benchmark Suite (PBBS) is a set of benchmark problems designed for comparing algorithms, implementations and platforms. For each problem, the suite defines the problem in terms of the input-output relationship, and supplies a set of input instances along with input generators, a default implementation, code for checking correctness or accuracy, and a timing harness. the suite makes it possible to compare different algorithms, platforms (e.g. CPU vs CPU), and implementations using different programming languages or libraries. the purpose is to better understand how well a wide variety of problems parallelize, and what techniques/algorithms are most effective. the suite was first announced in 2012 with 14 benchmark problems. Here we describe some significant updates. In particular, we have added nine new benchmarks from a mix of problems in text processing, computational geometry and machine learning. We have further optimized the default implementations;several are the fastest available for multicore CPUs, often achieving near perfect speedup on the 72 core machine we test them on. the suite now also supplies significantly larger default test instances, as well as a broader variety, with many derived from real-world data.

关键词： benchmarking parallel algorithms performance

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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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24th International Conference on the principles and practice of Constraint programming, CP 2018

24th International Conference on the Principles and Practice...

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24th International Conference on the principles and practice of Constraint programming, CP 2018

ISBN: (纸本)9783319983332

the proceedings contain 47 papers. the special focus in this conference is on . the topics include: An incremental SAT-based approach to reason efficiently on qualitative constraint networks;clause learning and new bounds for graph coloring;Portfolio-based algorithm selection for circuit QBFs;making compact-table compact;Approximation strategies for incomplete MaxSAT;a novel graph-based heuristic approach for solving sport scheduling problem;augmenting stream constraint programming with eventuality conditions;A complete tolerant algebraic side-channel attack for AES with CP;Evaluating QBF solvers: Quantifier alternations matter;propagating Regular membership with dashed strings;quantified valued constraint satisfaction problem;MLIC: A MaxSAT-based framework for learning interpretable classification rules;objective as a feature for robust search strategies;PW-AC: Extending compact-table to enforce pairwise consistency on table constraints;automatic generation and selection of streamlined constraint models via monte carlo search on a model lattice;efficient methods for constraint acquisition;a circuit constraint for multiple tours problems;towards semi-automatic learning-based model transformation;finding solutions by finding inconsistencies;the effect of structural measures and merges on SAT solver performance;a constraint-based encoding for domain-independent temporal planning;learning-sensitive backdoors with restarts;process plant layout optimization: Equipment allocation;a constraint programming approach for solving patient transportation problems;unifying reserve design strategies with graph theory and constraint programming;self-configuring cost-sensitive hierarchical clustering with recourse;user’s constraints in itemset mining;on maximal frequent itemsets mining with constraints;A parallel SAT-based framework for closed frequent itemsets mining;towards effective deep learning for constraint satisfaction problems;extending the capacity of 1/f noise generation.

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Effective Performance Measurement and Analysis of Multithreaded Applications

Effective Performance Measurement and Analysis of Multithrea...

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14th ACM SIGPLAN symposium on principles and practice of parallel programming

作者： Tallent, Nathan R. Mellor-Crummey, John M. Rice Univ Houston TX 77251 USA

ISBN: (纸本)9781605583976

Understanding why the performance of a multithreaded program does not improve linearly with the number of cores in a shared-memory node populated with one or more multicore processors is a problem of growing practical importance. this paper makes three contributions to performance analysis of multithreaded programs. First, we describe how to measure and attribute parallel idleness, namely, where threads are stalled and unable to work. this technique applies broadly to programming models ranging from explicit threading (e. g., Pthreads) to higher-level models such as Cilk and OpenMP. Second, we describe how to measure and attribute parallel overhead-when a thread is performing miscellaneous work other than executing the user's computation. By employing a combination of compiler support and post-mortem analysis, we incur no measurement cost beyond normal profiling to glean this information. Using idleness and overhead metrics enables one to pinpoint areas of an application where concurrency should be increased (to reduce idleness), decreased (to reduce overhead), or where the present parallelization is hopeless (where idleness and overhead are both high). third, we describe how to measure and attribute arbitrary performance metrics for high-level multithreaded programming models, such as Cilk. this requires bridging the gap between the expression of logical concurrency in programs and its realization at run-time as it is adaptively partitioned and scheduled onto a pool of threads. We have prototyped these ideas in the context of Rice University's HPCTOOLKIT performance tools. We describe our approach, implementation, and experiences applying this approach to measure and attribute work, idleness, and overhead in executions of Cilk programs.

关键词： Performance Measurement Algorithms Performance Analysis Call Path Profiling Multithreaded programming Models HPCTOOLKIT

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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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Accurate data redistribution cost estimation in software distributed shared memory systems 01

Accurate data redistribution cost estimation in software dis...

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

作者： Morris III, D.G. Lowenthal, D.K. Hewlett-Packard Company 19447 Pruneridge Avenue Cupertino CA 95014 United States

ISBN: (纸本)9781581133462

Distributing data is one of the key problems in implementing efficient distributed-memory parallel programs. the problem becomes more difficult in programs where data redistribution between computational phases is considered. the global data distribution problem is to find the optimal distribution in multi-phase parallel programs. Solving this problem requires accurate knowledge of data redistribution cost. We are investigating this problem in the context of a software distributed shared memory (SDSM) system, in which obtaining accurate redistribution cost estimates is difficult. this is because SDSM communication is implicit: It depends on access patterns, page locations, and the SDSM consistency protocol. We have developed integrated compile- and run-time analysis for SDSM systems to determine accurate redistribution cost estimates with low overhead. Our resulting system, SUIF-Adapt, can efficiently and accurately estimate execution time, including redistribution, to within 5% of the actual time in all of our test cases and is often much closer. these precise costs enable SUIF-Adapt to find efficient global data distributions in multiple-phase programs.

关键词： parallel processing systems

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Improving parallelism and Locality with Asynchronous Algorithms

Improving Parallelism and Locality with Asynchronous Algorit...

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15th ACM SIGPLAN symposium on principles and practice of parallel programming

作者： Liu, Lixia Li, Zhiyuan Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA

ISBN: (纸本)9781605587080

As multicore chips become the main building blocks for high performance computers, many numerical applications face a performance impediment due to the limited hardware capacity to move data between the CPU and the off-chip memory. this is especially true for large computing problems solved by iterative algorithms because of the large data set typically used. Loop tiling, also known as loop blocking, was shown previously to be an effective way to enhance data locality, and hence to reduce the memory bandwidth pressure, for a class of iterative algorithms executed on a single processor. Unfortunately, the tiled programs suffer from reduced parallelism because only the loop iterations within a single tile can be easily parallelized. In this work, we propose to use the asynchronous model to enable effective loop tiling such that both parallelism and locality can be attained simultaneously. Asynchronous algorithms were previously proposed to reduce the communication cost and synchronization overhead between processors. Our new discovery is that carefully controlled asynchrony and loop tiling can significantly improve the performance of parallel iterative algorithms on multicore processors due to simultaneously attained data locality and loop-level parallelism. We present supporting evidence from experiments with three well-known numerical kernels.

关键词： asynchronous algorithms loop tiling parallel numerical programs data locality memory performance

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Multi-Queues Can Be State-of-the-Art Priority Schedulers 22

Multi-Queues Can Be State-of-the-Art Priority Schedulers

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

作者： Postnikova, Anastasiia Koval, Nikita Nadiradze, Giorgi Alistarh, Dan ITMO Univ St Petersburg Russia JetBrains Prague Czech Republic IST Austria Klosterneuburg Austria

ISBN: (纸本)9781450392044

Designing and implementing efficient parallel priority schedulers is an active research area. An intriguing proposed design is the Multi-Queue: given n threads and m >= n distinct priority queues, task insertions are performed uniformly at random, while, to delete, a thread picks two queues uniformly at random, and removes the observed task of higher priority. this approach scales well, and has probabilistic rank guarantees: roughly, the rank of each task removed, relative to remaining tasks in all other queues, is O(m) in expectation. Yet, the performance of this pattern is below that of well-engineered schedulers, which eschew theoretical guarantees for practical efficiency. We investigate whether it is possible to design and implement a Multi-Queue-based task scheduler that is both highly-efficient and has analytical guarantees. We propose a new variant called the Stealing Multi-Queue (SMQ), a cache-efficient variant of the Multi-Queue, which leverages both queue affinity-each thread has a local queue, from which tasks are usually removed;but, with some probability, threads also attempt to steal higher-priority tasks from the other queues-and task batching, that is, the processing of several tasks in a single insert / remove step. these ideas are well-known for task scheduling without priorities;our theoretical contribution is showing that, despite relaxations, this design can still provide rank guarantees, which in turn implies bounds on total work performed. We provide a general SMQ implementation which can surpass state-of-the-art schedulers such as OBIM and PMOD in terms of performance on popular graph-processing benchmarks. Notably, the performance improvement comes mainly from the superior rank guarantees provided by our scheduler, confirming that analytically-reasoned approaches can still provide performance improvements for priority task scheduling. the full version of this paper is available in [24].

关键词： priority scheduling relaxed algorithms concurrency parallel graph processing

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24th European symposium on programming, ESOP 2015 Held as Part of the European Joint Conferences on theory and practice of Software, ETAPS 2015

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24th European symposium on programming, ESOP 2015 held as part of the European Joint Conferences on theory and practice of Software, ETAPS 2015

ISBN: (纸本)9783662466681

the proceedings contain 35 papers. the special focus in this conference is on programming Languages and Systems. the topics include: Static analysis of spreadsheet applications for type-unsafe operations detection;running probabilistic programs backwards;a verified compiler for probability density functions;segment abstraction for worst-case execution time analysis;automatic static cost analysis for parallel programs;sound, modular and compositional verification of the input/output behavior of programs;unrestricted termination and non-termination arguments for bit-vector programs;combining navigational and pattern matching approaches;the problem of PL concurrency semantics;trading efficiency and optimality in fence insertion for TSO;specifying and verifying concurrent algorithms with histories and subjectivity;automatically generating well-typed terms from the definition of a type-system;refinement types for incremental computational complexity;monotonic references for efficient gradual typing;inter-procedural two-variable herbrand equalities;desynchronized multi-state abstractions for open programs in dynamic languages;fine-grained detection of privilege escalation attacks on browser extensions;analysis of asynchronous programs with event-based synchronization;a new approach to practical complete predicate refinement;propositional reasoning about safety and termination of heap-manipulating programs;concurrent local subjective logic;a separation logic for fictional sequential consistency;binding structures as an abstract data type and type-based allocation analysis for co-recursion in lazy functional languages.

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Backtracking-based Load Balancing

Backtracking-based Load Balancing

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14th ACM SIGPLAN symposium on principles and practice of parallel programming

作者： Hiraishi, Tasuku Yasugi, Masahiro Umatani, Seiji Yuasa, Taiichi Kyoto Univ Acad Ctr Comp & Media Studies Kyoto 6068501 Japan Kyoto Univ Grad Sch Informat Kyoto 6068501 Japan

ISBN: (纸本)9781605583976

High-productivity languages for parallel computing become more important as parallel environments including multicores become more common. Cilk is such a language. It provides good load balancing for many applications including irregular ones;that is, it keeps all workers busy by creating plenty of "logical" threads and adopting the oldest-first work stealing strategy. this paper proposes a "logical thread"-free framework called Tascell, which achieves a higher performance and supports a wider range of parallel environments including clusters without loss of productivity. A Tascell worker spawns a "real" task only when requested by another idle worker. the worker performs the spawning by temporarily "backtracking" and restoring its oldest task-spawnable state. Our approach eliminates the cost of spawning/managing logical threads. It also promotes the reuse of workspaces and improves the locality of reference since it does not need to prepare a workspace for each concurrently runnable logical thread. Furthermore, Tascell enables elegant and highly-efficient backtrack search algorithms with delayed workspace copying. For instance, our 16-queens problem solver is 1.86 times faster than Cilk on a system with two dual-core processors. Our approach also enables a single program to run in both shared and distributed memory environments with reasonable efficiency and scalability.

关键词： Design Languages Performance load balancing parallel computing backtracking backtrack search

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