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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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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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Efficient support for irregular applications on distributed-memory machines

Efficient support for irregular applications on distributed-...

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

作者： Mukherjee, Shubhendu S. Sharma, Shamik D. Hill, Mark D. Larus, James R. Rogers, Anne Saltz, Joel Univ of Wisconsin-Madison Madison United States

Irregular computation problems underlie many important scientific applications. Although these problems are computationally expensive, and so would seem appropriate for parallel machines, their irregular and unpredictable run-time behavior makes this type of parallel program difficult to write and adversely affects run-time performance. this paper explores three issues - partitioning, mutual exclusion, and data transfer - crucial to the efficient execution of irregular problems on distributed-memory machines. Unlike previous work, we studied the same programs running in three alternative systems on the same hardware base (a thinking Machines CM-5): the CHAOS irregular application library, Transparent Shared Memory (TSM), and extensible Shared Memory (XSM). CHAOS and XSM performed equivalently for all three applications. Both systems were somewhat (13%) to significantly faster (991%) than TSM.

关键词： parallel processing systems

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Modernizing parallel code with pattern analysis 21

Modernizing parallel code with pattern analysis

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

作者： Lozano, Roberto Castañeda Cole, Murray Franke, Björn University of Edinburgh School of Informatics Edinburgh United Kingdom

ISBN: (纸本)9781450382946

Fifty years of parallel programming has generated a substantial legacy parallel codebase, creating a new portability challenge: re-parallelizing already parallel code. Our solution exploits inherently portable parallel patterns, and addresses the challenge of identifying patternization opportunities in legacy parallel code via constraint matching on traced dynamic dataflow graphs. Notably, this makes the analysis source-independent and equally applicable to sequential and parallel legacy code. We identify various map and reduction patterns, including compositions, in Pthreads code. Experiments with the Starbench suite show that our analysis is effective (finding 86% of the patterns known in the literature), accurate (reporting actual patterns in 98% of the cases), and efficient (scaling linearly with the size of the execution traces). We re-express the found patterns via a parallel pattern library, making code freely portable across CPU/GPU systems and performing competitively with hand-tuned implementations at zero additional effort. © 2021 acm.

关键词： Pattern matching

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Scaling implicit parallelism via dynamic control replication 21

Scaling implicit parallelism via dynamic control replication

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

作者： Bauer, Michael Lee, Wonchan Slaughter, Elliott Jia, Zhihao Di Renzo, Mario Papadakis, Manolis Shipman, Galen McCormick, Patrick Garland, Michael Aiken, Alex NVIDIA United States Slac National Accelerator Laboratory United States Carnegie Mellon University United States Sapienza University of Rome Italy Los Alamos National Laboratory United States Stanford University United States

ISBN: (纸本)9781450382946

We present dynamic control replication, a run-time program analysis that enables scalable execution of implicitly parallel programs on large machines through a distributed and efficient dynamic dependence analysis. Dynamic control replication distributes dependence analysis by executing multiple copies of an implicitly parallel program while ensuring that they still collectively behave as a single execution. By distributing and parallelizing the dependence analysis, dynamic control replication supports efficient, on-the-fly computation of dependences for programs with arbitrary control flow at scale. We describe an asymptotically scalable algorithm for implementing dynamic control replication that maintains the sequential semantics of implicitly parallel programs. An implementation of dynamic control replication in the Legion runtime delivers the same programmer productivity as writing in other implicitly parallel programming models, such as Dask or TensorFlow, while providing better performance (11.4X and 14.9X respectively in our experiments), and scalability to hundreds of nodes. We also show that dynamic control replication provides good absolute performance and scaling for HPC applications, competitive in many cases with explicitly parallel programming systems. © 2021 acm.

关键词： parallel programming

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Impala: a middleware system for managing autonomic, parallel sensor systems 03

Impala: a middleware system for managing autonomic, parallel...

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9th acm sigplan symposium on principles and practice of parallel programming

作者： Liu, T Martonosi, M Princeton Univ Dept Comp Sci Princeton NJ 08544 USA Princeton Univ Dept Elect Engn Princeton NJ 08544 USA

ISBN: (纸本)9781581135886

Sensor networks are long-running computer systems with many sensing/compute nodes working to gather information about their environment, process and fuse that information, and in some cases, actuate control mechanisms in response. Like traditional parallel systems, communication between nodes is of fundamental importance, but is typically accomplished via wireless transceivers. One further key attribute of sensor networks is that they are almost always long-running systems, intended to operate in situ, with minimal direct human intervention, for months or years. this requirement for long-running autonomy mandates careful design of the runtime system that manages applications on each node, to ensure reliability and ease of upgrades over the life of the system. this paper describes Impala, a middleware architecture that enables application modularity, adaptivity, and repair-ability in wireless sensor networks. Impala allows software updates to be received via the node's wireless transceiver and to be applied to the running system dynamically. In addition, Impala also provides an interface for on-the-fly application adaptation in order to improve the performance, energy-efficiency, and reliability of the software system. Impala has been designed to be a part of the ZebraNet mobile sensor network, but we are also prototyping it within HP/Compaq iPAQ Pocket PC handhelds. We present performance data for both real system measurements of the Pocket PC version as well as simulations of a full mobile sensor system deployment. Overall, Impala is a lightweight runtime system that can greatly improve system reliability, performance, and energy-efficiency. the ideas introduced here for sensor networks have applicability more broadly in other long-running autonomous parallel systems as well.

关键词： design experimentation performance sensor networks middleware system software adaptation software update

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INFINEL: An efficient GPU-based processing method for unpredictable large output graph queries 24

INFINEL: An efficient GPU-based processing method for unpred...

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

作者： Park, Sungwoo Oh, Seyeon Kim, Min-Soo Korea Adv Inst Sci & Technol Seoul South Korea GraphAI Seoul South Korea

ISBN: (纸本)9798400704352

With the introduction of GPUs, which are specialized for iterative parallel computations, the execution of computationintensive graph queries using a GPU has seen significant performance improvements. However, due to the memory constraints of GPUs, there has been limited research on handling large-scale output graph queries with unpredictable output sizes on a GPU. Traditionally, two-phase methods have been used, where the query is re-executed after splitting it into sub-tasks while only considering the size of the output in a static manner. However, two-phase methods become highly inefficient when used with graph data with extreme skew, failing to maximize the GPU performance. this paper proposes INFINEL, which handles unpredictable large output graph queries in a one-phase method through chunk allocation per thread and kernel stop/restart methods. We also propose applicable optimization techniques due to the corresponding unique characteristics of operating with low time/space overhead and not heavily relying on the GPU output buffer size. through extensive experiments, we demonstrate that our one-phase method of INFINEL improves the performance by up to 31.5 times over the conventional twophase methods for triangle listing ULO query.

关键词： Graph query processing Large output parallel computing GPU

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Flattening and parallelizing irregular, recurrent loop nests 95

Flattening and parallelizing irregular, recurrent loop nests

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

作者： Ghuloum, Anwar M. Fisher, Allan L. Carnegie Mellon Univ Pittsburgh PA United States

ISBN: (纸本)9780897917001

Irregular loop nests in which the loop bounds are determined dynamically by indexed arrays are difficult to compile into expressive parallel constructs, such as segmented scans and reductions. In this paper, we describe a suite of transformations to automatically parallelize such irregular loop nests, even in the presence of recurrences. We describe a simple, general loop flattening transformation, along with new optimizations which make it a viable compiler transformation. A robust recurrence parallelization technique is coupled to the loop flattening transformation, allowing parallelization of segmented reductions, scans, and combining-sends over arbitrary associative operators. We discuss the implementation and performance results of the transformations in a parallelizing Fortran 77 compiler for the Cray C90 supercomputer. In particular, we focus on important sparse matrix-vector multiplication kernels, for one of which we are able to automatically derive an algorithm used by one of the fastest library routines available.

关键词： parallel processing systems

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Combining phase identification and statistic modeling for automated parallel benchmark generation 2015

Combining phase identification and statistic modeling for au...

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

作者： Jin, Ye Liu, Mingliang Ma, Xiaosong Liu, Qing Logan, Jeremy Podhorszki, Norbert Choi, Jong Youl Klasky, Scott NCSU United States QCRI Qatar Oak Ridge National Lab. United States

ISBN: (纸本)9781450332057

parallel application benchmarks are indispensable for evaluating/optimizing HPC software and hardware. However, it is very challenging and costly to obtain high-fidelity benchmarks reflecting the scale and complexity of state-of-the-art parallel applications. Hand-extracted synthetic benchmarks are time- and labor-intensive to create. Real applications themselves, while offering most accurate performance evaluation, are expensive to compile, port, reconfigure, and often plainly inaccessible due to security or ownership concerns. this work contributes APPRIME, a novel tool for trace-based automatic parallel benchmark generation. Taking as input standard communication-I/O traces of an application's execution, it couples accurate automatic phase identification with statistical regeneration of event parameters to create compact, portable, and to some degree reconfigurable parallel application benchmarks. Experiments with four NAS parallel Benchmarks (NPB) and three real scientific simulation codes confirm the fidelity of APPRIME benchmarks. they retain the original applications' performance characteristics, in particular the relative performance across platforms.

关键词： Benchmarking

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Array operation synthesis scheme to optimize Fortran 90 programs

Array operation synthesis scheme to optimize Fortran 90 prog...

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

作者： Hwang, Gwan-Hwan Lee, Jenq Kuen Ju, Dz-Ching Natl Tsing-Hua Univ Taiwan

An increasing number of programming languages, such as Fortran 90 and APL, are providing a rich set of intrinsic array functions and array expressions. these constructs which constitute an important part of data parallel languages provide excellent opportunities for compiler optimizations. In this paper, we present a new approach to combine consecutive data access patterns of array constructs into a composite access function to the source arrays. Our scheme is based on the composition of access functions, which is similar to a composition of mathematic functions. Our new scheme can handle not only data movements of arrays of different numbers of dimensions and segmented array operations but also masked array expressions and multiple sources array operations. As a result, our proposed scheme is the first synthesis scheme which can synthesize Fortran 90 RESHAPE, EOSHIFT, MERGE, and WHERE constructs together. Experimental results show speedups from 1.21 to 2.95 for code fragments from real applications on a Sequent multiprocessor machine by incorporating the proposed optimizations.

关键词： FORTRAN (programming language)

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