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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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Ordered vs. Unordered: a Comparison of parallelism and Work-efficiency in Irregular Algorithms 11

Ordered <i>vs</i>. Unordered: a Comparison of Parallelism an...

引用

16th acm symposium on principles and practice of parallel programming

作者： Hassaan, M. Amber Burtscher, Martin Pingali, Keshav Texas State Univ San Marcos Dept Comp Sci San Marcos TX USA Univ Texas Austin Dept Comp Sci Austin TX 78712 USA

ISBN: (纸本)9781450301190

Outside of computational science, most problems are formulated in terms of irregular data structures such as graphs, trees and sets. Unfortunately, we understand relatively little about the structure of parallelism and locality in irregular algorithms. In this paper, we study several algorithms for four such problems: discrete-event simulation, single-source shortest path, breadth-first search, and minimal spanning trees. We show that these algorithms can be classified into two categories that we call unordered and ordered, and demonstrate experimentally that there is a trade-off between parallelism and work efficiency: unordered algorithms usually have more parallelism than their ordered counterparts for the same problem, but they may also perform more work. Nevertheless, our experimental results show that unordered algorithms typically lead to more scalable implementations, demonstrating that less work-efficient irregular algorithms may be better for parallel execution.

关键词： Irregular Algorithms Amorphous Data-parallelism parallel Breadth-first Search Single-Source Shortest Path Discrete-Event Simulation Minimal Spanning Tree Multicore processors Galois system Algorithms Languages Performance

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COREMU: A Scalable and Portable parallel Full-system Emulator 11

COREMU: A Scalable and Portable Parallel Full-system Emulato...

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16th acm symposium on principles and practice of parallel programming

作者： Wang, Zhaoguo Liu, Ran Chen, Yufei Wu, Xi Chen, Haibo Zhang, Weihua Zang, Binyu Fudan Univ Parallel Proc Inst Shanghai Peoples R China

ISBN: (纸本)9781450301190

this paper presents the open-source COREMU, a scalable and portable parallel emulation framework that decouples the complexity of parallelizing full-system emulators from building a mature sequential one. the key observation is that CPU cores and devices in current (and likely future) multiprocessors are loosely-coupled and communicate through well-defined interfaces. Based on this observation, COREMU emulates multiple cores by creating multiple instances of existing sequential emulators, and uses a thin library layer to handle the inter-core and device communication and synchronization, to maintain a consistent view of system resources. COREMU also incorporates lightweight memory transactions, feedback-directed scheduling, lazy code invalidation and adaptive signal control to provide scalable performance. To make COREMU useful in practice, we also provide some preliminary tools and APIs that can help programmers to diagnose performance problems and (concurrency) bugs. A working prototype, which reuses the widely-used QEMU as the sequential emulator, is with only 2500 lines of code (LOCs) changes to QEMU. It currently supports x64 and ARM platforms, and can emulates up to 255 (1) cores running commodity OSes with practical performance, while QEMU cannot scale above 32 cores. A set of performance evaluation against QEMU indicates that, COREMU has negligible uniprocessor emulation overhead, performs and scales significantly better than QEMU. We also show how COREMU could be used to diagnose performance problems and concurrency bugs of both OS kernel and parallel applications.

关键词： Full-system Emulator parallel Emulator Multicore Design Experimentation Performance

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Scalable parallel minimum spanning forest computation 12

Scalable parallel minimum spanning forest computation

引用

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

作者： Nobari, Sadegh Cao, thanh-Tung Karras, Panagiotis Bressan, St´ephane National University of Singapore Singapore Rutgers University United States

ISBN: (纸本)9781450311601

the proliferation of data in graph form calls for the development of scalable graph algorithms that exploit parallel processing environments. One such problem is the computation of a graph's minimum spanning forest (MSF). Past research has proposed several parallel algorithms for this problem, yet none of them scales to large, high-density graphs. In this paper we propose a novel, scalable, parallel MSF algorithm for undirected weighted graphs. Our algorithm leverages Prim's algorithm in a parallel fashion, concurrently expanding several subsets of the computed MSF. Our effort focuses on minimizing the communication among different processors without constraining the local growth of a processor's computed subtree. In effect, we achieve a scalability that previous approaches lacked. We implement our algorithm in CUDA, running on a GPU and study its performance using real and synthetic, sparse as well as dense, structured and unstructured graph data. Our experimental study demonstrates that our algorithm outperforms the previous state-of-the-art GPU-based MSF algorithm, while being several order of magnitude faster than sequential CPU-based algorithms. Copyright © 2012 acm.

关键词： Graphics processing unit

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AGAthA: Fast and Efficient GPU Acceleration of Guided Sequence Alignment for Long Read Mapping 24

AGAThA: Fast and Efficient GPU Acceleration of Guided Sequen...

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

作者： Park, Seongyeon Hong, Junguk Song, Jaeyong Kim, Hajin Kim, Youngsok Lee, Jinho Seoul Natl Univ Seoul South Korea Yonsei Univ Seoul South Korea

ISBN: (纸本)9798400704352

With the advance in genome sequencing technology, the lengths of deoxyribonucleic acid (DNA) sequencing results are rapidly increasing at lower prices than ever. However, the longer lengths come at the cost of a heavy computational burden on aligning them. For example, aligning sequences to a human reference genome can take tens or even hundreds of hours. the current de facto standard approach for alignment is based on the guided dynamic programming method. Although this takes a long time and could potentially benefit from high-throughput graphic processing units (GPUs), the existing GPU-accelerated approaches often compromise the algorithm's structure, due to the GPU-unfriendly nature of the computational pattern. Unfortunately, such compromise in the algorithm is not tolerable in the field, because sequence alignment is a part of complicated bioinformatics analysis pipelines. In such circumstances, we propose AGAthA, an exact and efficient GPU-based acceleration of guided sequence alignment. We diagnose and address the problems of the algorithm being unfriendly to GPUs, which comprises strided/redundant memory accesses and workload imbalances that are difficult to predict. According to the experiments on modern GPUs, AGAthA achieves 18.8x speedup against the CPU-based baseline, 9.6x against the best GPU-based baseline, and 3.6x against GPU-based algorithms with different heuristics.

关键词： GPU Acceleration Genome Sequence Alignment Long Reads Dynamic programming

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Proactive Work Stealing for Futures 19

Proactive Work Stealing for Futures

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24th acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Singer, Kyle Xu, Yifan Lee, I-Ting Angelina Washington Univ St Louis MO USA

ISBN: (纸本)9781450362252

the use of futures provides a flexible way to express parallelism and can generate arbitrary dependences among parallel subcomputations. the additional flexibility that futures provide comes with a cost, however. When scheduled using classic work stealing, a program with futures, compared to a program that uses only fork-join parallelism, can incur a much higher number of "deviations," a metric for evaluating the performance of parallel executions. All prior works assume a parsimonious work-stealing scheduler, however, where a worker thread (surrogate of a processor) steals work only when its local deque becomes empty. In this work, we investigate an alternative scheduling approach, called ProWS, where the workers perform proactive work stealing when handling future operations. We show that ProWS, for programs that use futures, can provide provably efficient execution time and equal or better bounds on the number of deviations compared to classic parsimonious work stealing. Given a computation with T-1 work and T-infinity span, ProWS executes the computation on P processors in expected time O(T-1/P + T-infinity lg P), with an additional lg P overhead on the span term compared to the parsimonious variant. For structured use of futures, where each future is single touch with no race on the future handle, the algorithm incurs O(PT infinity 2) deviations, matching that of the parsimonious variant. For general use of futures, the algorithm incurs O(m(k)T(infinity) + PT infinity lg P) deviations, where m(k) is the maximum number of future touches that are logically parallel. Compared to the bound for the parsimonious variant, O(kT(infinity) + PT infinity), with k being the total number of touches in the entire computation, this bound is better assuming m(k) = Omega(P lg P) and is smaller than k, which holds true for all the benchmarks we examined.

关键词： parallel processing systems

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Implementation of a portable nested data-parallel language 93

Implementation of a portable nested data-parallel language

引用

4th acm sigplan symposium on principles and practice of parallel programming, PPOPP 1993

作者： Blelloch, Guy E. Chatterjee, Siddhartha Hardwick, Jonathan C. Sipelstein, Jay Zagha, Marco School of Computer Science Carnegie Mellon University PittsburghPA15213 United States RIACS Mail Stop T045-1 NASA Ames Research Center Moffett FieldCA94035 United States

ISBN: (纸本)0897915895

this paper gives an overview of the implementation of NESL, a portable nested data-parallel language. this language and its implementation are the first to fully support nested data structures as well as nested data-parallel function calls. these features allow the concise description of parallel algorithms on irregular data, such as sparse matrices and graphs. In addition, they maintain the advantages of data-parallel languages: a simple programming model and portability. the current NESL implementation is based on an intermediate language called VcODE and a library of vector routines called CVL. It runs on the Connection Machine CM-2, the Cray Y-MP C90, and serial machines. We compare initial benchmark results of NESL with those of machine-specific code on these machines for three algorithms: least-squares line-fitting, median finding, and a sparse-matrix vector product. these results show that NESL'S performance is competitive with that of machine-specific codes for regular dense data, and is often superior for irregular data. © 1993 acm.

关键词： Matrix algebra

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S-EnKF: Co-designing for Scalable Ensemble Kalman Filter 19

S-EnKF: Co-designing for Scalable Ensemble Kalman Filter

引用

24th acm sigplan symposium on principles and practice of parallel programming (PPoPP)

作者： Xiao, Junmin Wang, Shijie Wan, Weiqiang Hong, Xuehai Tan, Guangming Univ Chinese Acad Sci Inst Comp Technol State Key Lab Comp Architecture Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9781450362252

Ensemble Kalman filter (EnKF) is one of the most important methods for data assimilation, which is widely applied to the reconstruction of observed historical data for providing initial conditions of numerical atmospheric and oceanic models. With the improvement of data resolution and the increase in the amount of model data, the scalability of recent parallel implementations suffers from high overhead on data transfer. In this paper, we propose, S-EnKF: a scalable and distributed EnKF adaptation for modern clusters. With an in-depth analysis of new requirements brought forward by recent frameworks and limitations of current designs, we present a co-design of S-EnKF. For fully exploiting the resources available in modern parallel file systems, we design a concurrent access approach to accelerate the process of reading large amounts of background data. through a deeper investigation of the data dependence relations, we modify EnKF's workflow to maximize the overlap of file reading and local analysis with a new multi-stage computation approach. Furthermore, we push the envelope of performance further with aggressive co-design of auto-tuning through tradeoff between the benefit on runtime and the cost on processors based on classic cost models. the experimental evaluation of S-EnKF demonstrates nearly ideal strong scalability on up to 12,000 processors. the largest run sustains a performance of 3x-speedup compared with P-EnKF, which represents the state-of-art parallel implementation of EnKF.

关键词： ensemble Kalman filter parallel implementation domain localization data assimilation scalability

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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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Effective garbage collection strategy for parallel programming languages on large scale distributed-memory machines

Effective garbage collection strategy for parallel programmi...

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

作者： Taura, Kenjiro Yonezawa, Akinori Univ of Tokyo Tokyo Japan

this paper describes the design and implementation of a garbage collection scheme on large-scale distributed-memory computers and reports various experimental results. the collector is based on the conservative GC library by Boehm & Weiser. Each processor traces local pointers using the GC library while traversing remote pointers by exchanging 'mark messages' between processors. It exhibits a promising performance - in the most space-intensive settings we tested, the total collection overhead ranges from 5% up to 15% of the application running time (excluding idle time). We not only examine basic performance figures such as the total overhead or latency of a global collection, but also demonstrate how local collection scheduling strategies affect application performance. In our collector, a local collection is scheduled either independently or synchronously. Experimental results show that the benefit of independent local collections has been overstated in the literature. Independent local collections slowed down application performance to 40%, by increasing the average communication latency. Synchronized local collections exhibit much more robust performance characteristics than independent local collections and the overhead for global synchronization is not significant. Furthermore, we show that an adaptive collection scheduler can select the appropriate local collection strategy based on the application's behavior. the collector has been used in a concurrent object-oriented language ABCL/f and the performance is measured on a large-scale parallel computer (256 processors) using four non-trivial applications written in ABCL/f.

关键词： parallel processing systems

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