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automatic parallelization of irregular applications

PARALLEL COMPUTING 2000年第13-14期26卷 1709-1738页

作者： Gutiérrez, E Asenjo, R Plata, O Zapata, EL Univ Malaga Dept Comp Architecture E-29080 Malaga Spain

Parallel computers are present in a variety of fields, having reached a high degree of architectural maturity. However, there is still a lack of convenient software support for implementing efficient parallel applications. This is specially true for the class of irregular applications, whose computational constructs hardly fit current parallel architectures. In fact, contemporary automatic parallelizers produce, in general, poor parallel code from these applications. This paper discusses techniques and methods to help improve the quality of automatic parallel programs. We focus on two issues: parallelism detection and parallelism implementation. The first issue refers to the detection of specific irregular computation constructs or data access patterns. The second issue considers the case that some frequent construct has been detected but has been sub-optimally parallelized. Both issues are dealt with in depth and in the context of sparse computations (for the first issue) and irregular histogram reductions (for the second issue). (C) 2000 Elsevier Science B.V. All rights reserved.

关键词： automatic parallelization irregular problems parallelism detection sparse matrix computations irregular reductions distributed shared-memory architectures

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automatic parallelization of compiled event driven VHDL simulation

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IEEE TRANSACTIONS ON COMPUTERS 2002年第4期51卷 380-394页

作者： Krishnaswamy, V Hasteer, G Banerjee, P Afara WebSyst San Jose CA 95134 USA Innol Syst San Jose CA 95134 USA Northwestern Univ Dept Elect & Comp Engn Evanston IL 60208 USA

In this paper, we present approaches and algorithms for parallelization of compiled event driven VHDL simulations on shared-memory multiprocessors (SMP). An efficient single-threaded algorithm for simulation of VHDL descriptions is first presented. This algorithm is shown to be competitive with a commercial VHDL simulator. Schemes for multithreaded execution of this algorithm are then described. These have been implemented on top of the POSIX pthreads library and experimental results have been shown on a Sun SparcServer 1000E. Speedups of up to four on eight processors have been achieved for some benchmarks.

关键词： event driven simulation compiled simulation VHDL scheduling partitioning multithreading automatic parallelization

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automatic parallelization of XQuery programs on multi-core systems

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JOURNAL OF SUPERCOMPUTING 2016年第4期72卷 1517-1548页

作者： Chen, Rongxin Liao, Husheng Wang, Zongyue Su, Hang Jimei Univ Comp Engn Coll Xiamen Peoples R China Beijing Univ Technol Sch Software Engn Beijing Peoples R China Beijing Univ Technol Coll Comp Sci Beijing Peoples R China

The popularity of multi-core systems makes software parallelization become an important way to improve performance. As a mainstream XML query language, XQuery is the core of XML processing. It is critical to take full advantage of multi-core computing to improve XML processing performance through parallelization of XQuery. However, usually it is difficult to parallelize XQuery programs because of the nested style of XQuery expressions. Moreover, implicit parallelism is necessary to simplify the development of parallel XML application. In this paper, we propose an automatic parallelization approach, which can automatically select proper types of parallelism for a specific XQuery query. Specifically, we propose a functional intermediate language called pFXQL (parallel Functional XML Query Language) to describe parallel query plans. pFXQL has parallel semantics and is well complied with XQuery. We propose a cost model to effectively support plan generation and the selection of a preferred plan. The model estimates both computational cost and parallel cost. We implement our approach in XQuery engine and conduct experiments on various multi-core systems. Experimental results verify the effectiveness of our approach.

关键词： XQuery automatic parallelization Intermediate language Cost model Multi-core computing

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automatic parallelization of recursive procedures

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INTERNATIONAL JOURNAL OF PARALLEL PROGRAMMING 2000年第6期28卷 537-562页

作者： Gupta, M Mukhopadhyay, S Sinha, N IBM Corp TJ Watson Res Ctr Yorktown Heights NY 10598 USA Mobius Management Syst Rye NY 10580 USA IBM Global Serv India Bangalore 560017 Karnataka India

Parallelizing compilers have traditionally focussed mainly on parallelizing loops. This paper presents a new framework for automatically parallelizing recursive procedures that typically appear in divide-and-conquer algorithms. We present compile-time analysis, using powerful, symbolic array section analysis, to detect the independence of multiple recursive calls in a procedure. This allows exploitation of a scalable form of nested parallelism, where each parallel task can further spawn off parallel work in subsequent recursive calls. We describe a runtime system which efficiently supports this kind of nested parallelism without unnecessarily blocking tasks. We have implemented this framework in a parallelizing compiler, which is able to automatically parallelize programs like quicksort and mergesort, written in C. For cases where even the advanced compile-time analysis we describe is not able to prove the independence of procedure calls, we propose novel techniques for speculative runtime parallelization, which are more efficient and powerful in this context than analogous techniques proposed previously for speculatively parallelizing loops. Our experimental results on an IBM G30 SMP machine show good speedups obtained by following our approach.

关键词： automatic parallelization recursive procedures divide and conquer symbolic analysis array section analysis speculative parallelization

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automatic parallelization: Executing Sequential Programs on a Task-Based Parallel Runtime

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INTERNATIONAL JOURNAL OF PARALLEL PROGRAMMING 2016年第6期44卷 1337-1358页

作者： Fonseca, Alcides Cabral, Bruno Rafael, Joao Correia, Ivo Univ Coimbra Dept Informat Engn Coimbra Portugal

There are billions of lines of sequential code inside nowadays' software which do not benefit from the parallelism available in modern multicore architectures. automatically parallelizing sequential code, to promote an efficient use of the available parallelism, has been a research goal for some time now. This work proposes a new approach for achieving such goal. We created a new parallelizing compiler that analyses the read and write instructions, and control-flow modifications in programs to identify a set of dependencies between the instructions in the program. Afterwards, the compiler, based on the generated dependencies graph, rewrites and organizes the program in a task-oriented structure. Parallel tasks are composed by instructions that cannot be executed in parallel. A work-stealing-based parallel runtime is responsible for scheduling and managing the granularity of the generated tasks. Furthermore, a compile-time granularity control mechanism also avoids creating unnecessary data-structures. This work focuses on the Java language, but the techniques are general enough to be applied to other programming languages. We have evaluated our approach on 8 benchmark programs against OoOJava, achieving higher speedups. In some cases, values were close to those of a manual parallelization. The resulting parallel code also has the advantage of being readable and easily configured to improve further its performance manually.

关键词： automatic parallelization Task-based runtime Symbolic analysis

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AN automatic parallelization FRAMEWORK FOR MULTICOMPUTERS

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COMPUTER LANGUAGES 1994年第3期20卷 135-150页

作者： SHENOY, UN SRIKANT, YN BHATKAR, VP INDIAN INST SCI DEPT COMP SCI & AUTOMATBANGALORE 560012KARNATAKAINDIA

Several researchers have looked into various issues related to automatic parallelization of sequential programs for multicomputers. But there is a need for a coherent framework which encompasses all these issues. In this paper we present a such a framework which takes best advantage of the multicomputer architecture. We resort to tiling transformation for iteration space partitioning and propose a scheme of automatic data partitioning and dynamic data distribution. We have tried a simple implementation of our scheme on a transputer based multicomputer [1] and the results are encouraging.

关键词： automatic parallelization ITERATION SPACE PARTITIONING DATA PARTITIONING SECTIONED DISTRIBUTED SHARED MEMORY

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automatic parallelization OF WHILE-LOOPS USING SPECULATIVE EXECUTION

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INTERNATIONAL JOURNAL OF PARALLEL PROGRAMMING 1995年第2期23卷 191-219页

作者： COLLARD, JF Laboratoire de l'Informatique du Parallélisme (LIP) ENS Lyon Lyon Cedex 07 France

automatic parallelization of imperative sequential programs has focused on nests of for-loops. The most recent of them consist in finding an affine mapping with respect to the loop indices to simultaneously capture the temporal and spatial properties of the parallelized program. Such a mapping is usually called a ''space-time transformation.'' This work describes an extension of these techniques to while-loops using speculative execution. We show that space-time transformations are a good framework for summing up previous restructuration techniques of while-loop, such as pipelining. Moreover, we show that these transformations can be derived and applied automatically.

关键词： automatic parallelization SPACE-TIME TRANSFORMATION SPECULATIVE EXECUTION WHILE-LOOP

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automatic parallelization of canonical loops

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SCIENCE OF COMPUTER PROGRAMMING 2013年第8期78卷 1193-1206页

作者： Padovani da Mata, Leonardo Luiz Quintao Pereira, Fernando Magno Ferreira, Renato Univ Fed Minas Gerais Dept Ciencia Comp BR-31270010 Belo Horizonte MG Brazil

This paper presents a compilation technique that performs the automatic parallelization of canonical loops. Canonical loops are a recurring pattern that we have observed in many well known algorithms, such as frequent itemset, K-means and K nearest neighbors. Our compiler translates C code to sequences of stream filters that communicate through a variety of channel types. We analyze code containing canonical loops, separate the data over a cluster of processors and determine suitable communication strategies between these processors. Experiments performed on a cluster of 36 computers show that, for the three algorithms described above, our method produces speed-ups that are almost linear on the number of available processors. These experiments also show that the code automatically generated is competitive when compared to hand tuned programs. (C) 2012 Elsevier B.V. All rights reserved.

关键词： automatic parallelization Map-reduce Compiler Stream-programming

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automatic parallelization of Probabilistic Models with Varying Load Imbalance 20

Automatic Parallelization of Probabilistic Models with Varyi...

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20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid)

作者： Nemeth, Balazs Haber, Tom Liesenborgs, Jori Lamotte, Wim Hasselt Univ tUL Expertise Ctr Digital Media Martelarenlaan 42 B-3500 Hasselt Belgium

ISBN: (数字)9781728160955

ISBN: (纸本)9781728160955

As scientists are designing increasingly complex and intricate models, the prominent way today to achieve acceptable execution time without sacrificing accuracy is through parallel computing. These techniques can improve execution time either on the level of the optimization methods or on the level of the model evaluations. This paper outlines an automatic parallelization approach for the latter. Processor specific procedures with embedded communication primitives are generated from static schedules produced by an evolutionary algorithm. These are passed to an optimizing compiler to avoid the overhead of typical task runtime systems. The two key insights are that the parallel structure of probabilistic models is revealed when the data is combined with the model and that static schedules can be combined into more robust schedules that can deal with varying load imbalance. For this, LogP model parameters and execution time of each computational task are measured and fed into a discrete event simulator to estimate the running time on the target parallel system. Performance is evaluated with three pharmacological models with different characteristics. The first model lacks enough exploitable parallelism while up to approximately 6x and 8x improvements are achieved for the other models. Compared to a theoretical system with infinite processors and no communication delay, this equates to exploiting 66% and 99% of the available parallelism. Performance improves even when load imbalance varies.

关键词： High Performance Computing Descriptive Language Probabilistic Modeling automatic parallelization Dataflow LogP model Simulation Evolutionary Algorithms Scheduling Load Imbalance

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automatic parallelization of Irregular x86-64 Loops 2019

Automatic Parallelization of Irregular x86-64 Loops

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17th IEEE/ACM International Symposium on Code Generation and Optimization (CGO)

作者： Neth, Brandon Strout, Michelle Mills Univ Arizona Dept Comp Sci Tucson AZ 85719 USA

ISBN: (纸本)9781728114361

Productivity languages such as Python and R are growing in popularity especially in the development of data analysis algorithms. While these languages provide powerful tools to accelerate the development process, they incur heavy overhead due to their interpreted nature. One approach to remove this overhead is to specialize the interpreter for a given script. Then, loops in the specialized code can be parallelized to further improve performance. In contrast to previous work that targets LLVM loops with affine memory access patterns, we are investigating the problem of parallelizing loops with irregular access patterns at the x86 level. To do so, we split hot loops into a sequential master thread that sends tasks to parallel worker threads.

关键词： automatic parallelization dependence analysis scientific computing x86 parallelization

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