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TRAPEZOID SELF-SCHEDULING - A PRACTICAL SCHEDULING SCHEME FOR parallel compilerS

IEEE TRANSACTIONS ON parallel AND DISTRIBUTED SYSTEMS 1993年第1期4卷 87-98页

作者： TZEN, TH NI, LM MICHIGAN STATE UNIV DEPT COMP SCIE LANSINGMI 48824 MICHIGAN STATE UNIV ADV COMP SYST LABE LANSINGMI 48824

In this paper, we present a new practical processor self-scheduling scheme, Trapezoid Self-Scheduling, for arbitrary parallel nested loops in shared-memory multiprocessors. Generally, loops are the richest source of parallelism in parallel programs. To dynamically allocate loop iterations to processors, one may achieve load balancing among processors at the expense of run-time scheduling overhead. By linearly decreasing the chunk size at run time, the best tradeoff between the scheduling overhead and balanced workload can be obtained in the proposed trapezoid self-scheduling approach. Due to its simplicity and flexibility, this approach can be efficiently implemented in any parallel compilers. The small and predictable number of chores also allow efficient management of memory in a static fashion. Out experiments conducted in a 96-node Butterfly GP-1000 clearly show the advantage of the trapezoid self-scheduling over other well-known self-scheduling approaches.

关键词： CHUNK SIZE CRITICAL SECTION LOAD BALANCING MEMORY MANAGEMENT parallel compiler parallel LOOPS SCHEDULING OVERHEAD SELF-SCHEDULING SHARED-MEMORY MULTIPROCESSOR

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A compiler for Agnostic Programming and Deployment of Big Data Analytics on Multiple Platforms

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IEEE TRANSACTIONS ON parallel AND DISTRIBUTED SYSTEMS 2019年第9期30卷 1920-1931页

作者： Di Martino, Beniamino Esposito, Antonio D'Angelo, Salvatore Maisto, Salvatore Augusto Nacchia, Stefania CINI Consorzio Interuniv Nazl Informat Roma I-00198 Rome Lazio Italy Univ Campania Luigi Vanvitelli Dept Engn I-81100 Caserta CE Italy

To run proper Big Data Analytics, small and medium enterprises (SMEs) need to acquire expertise, hardware and software, which often translates to relevant initial investments for activities not directly connected to the company's business. To reduce such investments, the TOREADOR project proposes a Big Data Analytics framework which supports users in devising their own Big Data solutions by keeping the inherent costs at a minimum, and leveraging pre-existent knowledge and expertise. Among the objectives of the TOREADOR framework is supporting developers in parallelizing and deploying their Big Data algorithms, in order to develop their own analytics solutions. This paper describes the Code-Based approach, adopted within the TOREADOR framework to parallelize users' algorithms and deploy them on distributed platforms, via the annotation of parallelizable code portions with parallelization primitives. The approach, which relies on the guidance of parallel Patterns to implement the parallelization, and on Skeletons to automatically build execution and deployment templates, is realized through a source-to-source compiler, also described in the present paper.

关键词： TOREADOR parallel compiler skeletons parallel patterns parallel primitives big data analytics

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Using elementary linear algebra to solve data alignment for arrays with linear or quadratic references

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IEEE TRANSACTIONS ON parallel AND DISTRIBUTED SYSTEMS 2004年第1期15卷 28-39页

作者： Chang, WL Huang, JW Chu, CP So Taiwan Univ Technol Dept Informat Management Tainan 710 Taiwan Natl Cheng Kung Univ Dept Comp Sci & Informat Engn Tainan 701 Taiwan

Data alignment that facilitates data locality so that the data access communication costs can be minimized, helps distributed memory parallel machines improve their throughput. Most data alignment methods are devised mainly to align the arrays referenced using linear subscripts or quadratic subscripts with few (one or two) loop index variables. In this paper, we propose two communication-free alignment techniques to align the arrays referenced using linear subscripts or quadratic subscripts with multiple loop index variables. The experimental results from our techniques on Vector Loop and TRFD of the Perfect Benchmarks reveal that our techniques can improve the execution times of the subroutines in these benchmarks.

关键词： parallel compiler communication-free alignment parallel computing loop optimization data dependence analysis load balancing

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An efficient communication scheduling method for the processor mapping technique applied data redistribution

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JOURNAL OF SUPERCOMPUTING 2006年第3期37卷 297-318页

作者： Huang, Jih-Woei Chu, Chih-Ping Natl Cheng Kung Univ Dept Comp Sci & Informat Engn Tainan 701 Taiwan

Array redistribution is usually required for more efficiently executing a data-parallel program on distributed memory multi-computers. In performing array redistribution using synchronous communication mode, data communications among the processors should be properly arranged to avoid incurring higher data transfer cost. Some efficient communication scheduling methods for the Block-Cyclic redistribution have been proposed. On the other hand, the processor mapping technique can help reduce the data transfer cost of redistribution. To avoid degrading the benefit of data transfer cost reduction, it is needed to construct optimal communication schedules for the redistribution in which the processor mapping technique is applied. In this paper, we present a unified approach to constructing optimal communication schedules for the processor mapping technique applied Block-Cyclic redistribution. The proposed method is founded on the processor mapping technique and can more efficiently construct the required communication schedules than other optimal scheduling methods.

关键词： parallel compiler data-parallel programming data redistribution communication scheduling processor mapping MPI

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Shared Variable Oriented parallel Precompiler for SPMD Model

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Journal of Computer Science & Technology 1995年第5期10卷 476-480页

作者：康继昌朱怡安洪远麟应必善 Northwestern Polytechnical Univ Xi'an China

For the moment, commercial parallel computer systems with distributed memory architecture are usually provided with parallel FORTRAN or parallel C compliers, which are just traditional sequential FORTRAN or C compilers expanded with communication statements. Programmers suffer from writing parallel programs with communication *** Shared Variable Oriented parallel Precompiler (SVOPP) proposed in this paper can automatically generate appropriate communication statements based on shared variables for SPMD (Single Program Multiple Data) computa-tion model and greatly ease the parallel programming with high communication efficiency. The core function of parallel C precompi1er has been successfully veri-fied on a transputer-based parallel computer. Its prominent performance shows that SVOPP is probably a break-through in parallel programming technique.

关键词： parallel computer parallel compiler parallel precompiler communication statement

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Integrated range comparison for data-parallel compilation systems

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IEEE TRANSACTIONS ON parallel AND DISTRIBUTED SYSTEMS 1999年第5期10卷 448-458页

作者： Sun, XH Pantano, M Fahringer, T Louisiana State Univ Dept Comp Sci Baton Rouge LA 70803 USA Univ Illinois Dept Comp Sci Urbana IL 61801 USA Univ Vienna Inst Software Technol & Parallel Syst A-1090 Vienna Austria

A major difficulty in restructuring compilation, and in parallel programming in general, is how to compare parallel performance over a range of system and problem sizes. Execution time varies with system and problem size and an initially fast implementation may become slow when system and problem size scale up. This paper introduces the concept of range comparison. Unlike conventional execution time comparison in which performance is compared for a particular system and problem size. range comparison compares the performance of programs over a range of ensemble and problem sizes via scalability and performance crossing point analysis. A novel algorithm is developed to predict the crossing point automatically. The correctness of the algorithm is proven and a methodology is developed to integrate range comparison into restructuring compilations for data-parallel programming. A preliminary prototype of the methodology is implemented and tested under Vienna Fortran Compilation System. Experimental results demonstrate that range comparison is feasible and effective. It is an important asset for program evaluation, restructuring compilation, and parallel programming.

关键词： performance evaluation parallel compiler scalable computing software systems

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Rotation scheduling: A loop pipelining algorithm

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IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 1997年第3期16卷 229-239页

作者： Chao, LF LaPaugh, AS Sha, EHM PRINCETON UNIV DEPT COMP SCIPRINCETONNJ 08544 UNIV NOTRE DAME DEPT COMP SCI & ENGNNOTRE DAMEIN 46556

We consider the resource-constrained scheduling of loops with interiteration dependencies. A loop is modeled as a data flow graph (DFG), where edges are labeled with the number of iterations between dependencies. We design a novel and flexible technique, called rotation scheduling, for scheduling cyclic DFG's using loop pipelining. The rotation technique repeatedly transforms a schedule to a more compact schedule. We provide a theoretical basis for the operations based on retiming. We propose two heuristics to perform rotation scheduling and give experimental results showing that they have very good performance.

关键词： high-level synthesis loop pipelining parallel compiler retiming scheduling

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Exploiting Loop parallelism with Redundant Execution

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Journal of Computer Science & Technology 1997年第2期12卷 105-112页

作者：唐卫宇施武臧斌宇朱传琪 Institute of Parallel Processing Fudan University Shanghai

In this paper, a new loop transformation is proposed that can exploit parallelism in loops which cannot be found by traditional methods. Then the method is extended to show how to achieve maximum speedup of loops if there are infinite processors and how to balance the workload of parallel sections in loops i f there is fixed number of processors.

关键词： parallel compiler loop transformation parallel section maximum speedup

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ODCHP: a new effective mechanism to maximize parallelism of nested loops with non-uniform dependences

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JOURNAL OF SYSTEMS AND SOFTWARE 2001年第3期56卷 279-297页

作者： Pean, DL Chen, C Natl Chiao Tung Univ Dept Comp Sci & Informat Engn Hsinchu 30050 Taiwan

There are many methods for nested loop partitioning. However, most of them perform poorly when partitioning loops with nonuniform dependences. This paper proposes a generalized and optimized loop partitioning mechanism to exploit parallelism from nested loops with non-uniform dependences. Our approach, based on dependence convex theory, will divide the loop into variable size partitions. Furthermore, the proposed algorithm partitions a nested loop by using the copy-renaming and the optimized partitioning techniques to minimize the number of parallel regions of the iteration space. Consequently, it outperforms the previous partitioning mechanisms of nested loops with non-uniform dependences. Many optimization techniques are used to reduce the complexity of the algorithm. Compared with other popular techniques, our scheme shows a dramatic improvement in the preliminary performance results. (C) 2001 Elsevier Science Inc. All rights reserved.

关键词： compilers non-uniform dependence loop parallelization parallel compiler parallel processing dependence convex hull

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IMPROVED AFFINE PARTITION ALGORITHM FOR COMPILE-TIME AND RUNTIME PERFORMANCE

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INTELLIGENT AUTOMATION AND SOFT COMPUTING 2011年第8期17卷 1179-1191页

作者： Yuan Xinyu Li Ying Deng Shuiguang Cheng Jie Zhejiang Univ Coll Comp Sci & Technol Hangzhou 310003 Zhejiang Peoples R China Ningbo Univ Coll Comp Sci & Technol Ningbo 315211 Zhejiang Peoples R China

The Affine partitioning framework, which unifies many useful program transforms such as unimodular transformations, loop fusion, fission, scaling, reindexing, and statement reordering, has been proved to be successful in automatic discovery of the loop-level parallelization in programs. The affine partition algorithm was improved from the aspects of compile-time and runtime efficiency in this paper. Firstly, it improves compile-time speed of affine partition algorithm by using of generalized GCD test which is a basic dependence testing algorithm. This paper proved that generalized GCD test has a strong relationship with affine partition algorithm which can improve the compiling speed of the affine partition algorithm. Secondly, a method is put forward to select an optimal solution among the infinite legal solutions of the affine partition algorithm which ensures the minimum communication volume and the simplified processor space expression. Proved by experiments, the two innovations mentioned above can promote the compile-time and runtime efficiency of the affine partition algorithm.

关键词： parallel compiler affine partition dependence testing

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