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Structuring Meaningful Code Changes in Developer Community

Structuring Meaningful Code Changes in Developer Community

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international symposium on parallel architectures, algorithms and programming (PAAP)

作者： Mengxuan Li Shikai Guo Xin Ge Hui Li Rong Chen The College of Information Science and Technology Dalian Maritime University Dalian China

ISBN: (纸本)9781665452199

The rapid development of Open-Source Software (OSS) has resulted in a significant demand for code changes to maintain OSS. Symptoms of poor design and implementation choices in code changes often occur, thus heavily hindering code reviewers to verify correctness and soundness of code changes. Researchers have investigated how to learn meaningful code changes to assist developers in anticipating changes that code reviewers may suggest for the submitted code. However, there are two main limitations to be addressed, including the limitation of long-range dependencies of the source code and the missing syntactic structural information of the source code. To solve these limitations, we propose a novel method named GTCT. GTCT comprises two components: code graph embedding and code transformation learning. To address the missing syntactic structural information, we encoding the source code into a code graph structure from the lexical and syntactic representations of the source code. Subsequently, we uses the multi-head attention mechanism and positional encoding mechanism to address the long-range dependencies limitation. Extensive experiments are conducted to evaluate the performance of GTCT by both quantitative and qualitative analyses. For the quantitative analysis, GTCT relatively outperforms the baseline on six datasets by 210%, 342.86%, 135%, 29.41%, 109.09%, and 91.67% in terms of perfect prediction. Meanwhile, the qualitative analysis shows that each type of code change by GTCT outperforms that of the baseline method in terms of bug fixed, refactoring code, and others’ taxonomy of code changes.

关键词： Codes Statistical analysis Source coding Taxonomy Software algorithms Syntactics programming

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Enabling software DSM system for grid computing

Enabling software DSM system for grid computing

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international symposium on parallel architectures, algorithms and Networks (ISPAN)

作者： Tyng-Yeu Liang Chun-Yi Wu Jyh-Biau Chang Ce-Kuen Shieh Pei-Hsin Fan Department of Electrical Engineering National Kaohsiung University of Applied Sciences Kaohsiung Taiwan Department of Electrical Engineering National Cheng Kung University Tainan Taiwan

In this study, we have successfully developed a grid-enabled software distributed shared memory called Teamster-G. This system provides users with not only a shared memory programming interface but also a transparent resource allocation service to easily develop applications and aggregate distributed resources for solving their problems on the grid environment. Moreover, since the communication cost of maintaining data-consistency is a big problem for the performance of the DSM applications, Teamster-G exploits a cluster cache scheme and a two-level consistency protocol to minimize the number of data-consistency messages transferred over wide area network. We will present the framework and the performance of Teamster-G in this paper.

关键词： Software systems Grid computing Resource management Wide area networks Yarn Protocols Costs Processor scheduling parallel architectures Computer applications

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Generating High Quality Titles in StackOverflow via Data Denoising Method

Generating High Quality Titles in StackOverflow via Data Den...

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international symposium on parallel architectures, algorithms and programming (PAAP)

作者： Shikai Guo Bowen Ping Zixuan Song Hui Li Rong Chen school of information and technology Dalian Maritime University Dalian China

ISBN: (纸本)9781665452199

StackOverflow is one of the most popular question-and-answer platforms on the internet and whether posts on StackOverflow will be answered largely depends on their titles’ quality. Based on recurrent neural networks (RNN) or transformers, previous studies have attempted to use real posts from StackOverflow to generate better titles. However, the challenge of noise in existing data has been ignored, leading models can’t generate higher quality titles. To address this issue, we propose the K-clusters confidence learning for code titles (KCL-CT) model, which contains code clustering and confident learning (CL) denoising components. Specifically, the code clustering component is used to capture the word order and semantic information in code and classify code into different functional categories. The CL denoising component receives the output from the code clustering component and employs a heuristic method based on a confidence threshold to prune raw datasets. We conducted experiments based on Java, Python, JavaScript, SQL and C# datasets, the results of which indicated that in terms of the BLEU and ROUGE scores, the proposed KCL-CT model can outperform previous state-of-the-art models by 2.0%–11.1% and 2.5%–14.0%, respectively.

关键词： Java Codes Recurrent neural networks Noise reduction Semantics programming Transformers

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Run-Time Partitioning of Hybrid Distributed Shared Memory on Multi-core Network-on-Chips

Run-Time Partitioning of Hybrid Distributed Shared Memory on...

引用

international symposium on parallel architectures, algorithms and programming (PAAP)

作者： Xiaowen Chen Zhonghai Lu Axel Jantsch Shuming Chen Department of Electronic Systems KTH-Royal Institute of Technology Stockholm Sweden Institute of Microelectronic and Microprocessor National University of Defense Technology Changsha China

On multi-core Network-on-Chips (NoCs), memories are preferably distributed and supporting Distributed Shared Memory (DSM) is essential for the sake of reusing huge amount of legacy code and easy programming. However, the DSM organization imports the inherent overhead of translating virtual memory addresses into physical memory addresses, resulting in negative performance. We observe that, in parallel applications, different data have different properties (private or shared). For the private data accesses, it's unnecessary to perform Virtual-to-Physical address translations. Even for the same datum, its property may be changeable in different phases of the program execution. Therefore, this paper focuses on decreasing the overhead of Virtual-to-Physical address translation and hence improving the system performance by introducing hybrid DSM organization and supporting run-time partitioning according to the data property. The hybrid DSM organization aims at supporting fast and physical memory accesses for private data and maintaining a global and single virtual memory space for shared data. Based on the data property of parallel applications, the run-time partitioning supports changing the hybrid DSM organization during the program execution. It ensures fast physical memory addressing on private data and conventional virtual memory addressing on shared data, improving the performance of the entire system by reducing virtual-to-physical address translation overhead as much as possible. We formulate the run-time partitioning of hybrid DSM organization in order to analyze its performance. A real DSM based multi-core NoC platform is also constructed. The experimental results of real applications show that the hybrid DSM organization with run-time partitioning demonstrates performance advantage over the conventional DSM counterpart. The percentage of performance improvement depends on problem size, way of data partitioning and computation/communication ratio of parallel ap

关键词： Organizations Delay System performance programming Memory management System-on-a-chip Registers

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A parallel object-oriented framework for stencil algorithms

A parallel object-oriented framework for stencil algorithms

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international symposium on High Performance Distributed Computing

作者： J.F. Karpovich M. Judd W.T. Strayer A.S. Grimshaw Department of Computer Science University of Virginia USA

The authors present an object-oriented framework for constructing parallel implementations of stencil algorithms. This framework simplifies the development process by encapsulating the common aspects of stencil algorithms in a base stencil class so that application-specific derived classes can be easily defined via inheritance and overloading. In addition, the stencil base class contains mechanisms for parallel execution. The result is a high-performance, parallel, application-specific stencil class. The authors present the design rationale for the base class and illustrate the derivation process by defining two subclasses, an image convolution class and a PDE solver. The classes have been implemented in Mentat, an object-oriented parallel programming system that is available on a variety of platforms. Performance results are given for a network of Sun SPARCstation IPCs.< >

关键词： Convolution Iterative algorithms parallel programming Sun Workstations Computer science Partial differential equations Concurrent computing parallel architectures Investments

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BSP Pro: a Java-based BSP performance profiling system

BSP Pro: a Java-based BSP performance profiling system

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international symposium on parallel architectures, algorithms and Networks (ISPAN)

作者： Weiqun Zheng Shamim Khan Hong Xie School of Information Technology Murdoch University Perth WA Australia

The paper introduces a new parallel performance profiling system for the Bulk Synchronous parallel (BSP) model. The profiling system, called BSP Pro, consists of a performance profiling tool, BSP Profiler and a performance visualisation tool, BSP Visualiser. The aim of BSP Pro is to assist in the analysis and improvement of BSP program performance by minimising load imbalance among processes. BSP Pro is different from other systems, such as the profiling tools within the Oxford BSP toolset, in terms of both its features and its implementation. It uses BSP Profiler to trace and generate more comprehensive profiling information resulting from BSP program executions. The profiling information is then visualised and shown as performance profiling graphs using BSP Visualiser. The visualising component of BSP Pro is fully developed in Java and utilises Java graphics to expose and highlight process load imbalance in both computation and interprocess communication.

关键词： Java Performance analysis Visualization Australia parallel programming Predictive models Costs Information technology Graphics Concurrent computing

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A Multi-object Detection Sampling Algorithm For Large Scenes

A Multi-object Detection Sampling Algorithm For Large Scenes

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international symposium on parallel architectures, algorithms and programming (PAAP)

作者： Liang Jin Xiaochuan Li Baoyu Fan Zhenhua Guo Ruidong Li Li Wang Yanwei Wang Yaqian Zhao Rengang Li Inspur Electronic Information Industry Co.Ltd. Jinan China Shandong Yunhai Guochuang Cloud Computing Equipment Industry Innovation Center Co.Ltd. Jinan China

ISBN: (纸本)9781665452199

Multi-object detection in large scenes aims to find objects in images, which usually contain more than one billion pixels. Based on the concept of dividing and conquering, the state-of-the-art (SOTA) methods slice the super-resolution image into patches first and then lower the image solution to detect objects later. The advantage of this method is that it can adapt quickly to regular detection algorithms. However, a set of parameters needs to be set manually, such as the size of sliding windows and overlap, which is quite hard to fit all scenarios. It may result in a loss of samples located at the boundary of the sliding window and the oversampling of inefficient samples that appear within the overlap. In this paper, we propose a object-oriented image sampling algorithm based on anchor boxes during training and multi-scale pyramids during inference. Inspired by the mature object detection baseline Scale-YOLOv4, we present more tricks to fit large scenes. The accuracy can reach 66%, which is 24 points higher than the CascadeRCNN model of the official backbone network ResNet50. Finally, we have won first place in the PANDA object detection tracking using this method.

关键词： Training Object oriented modeling Superresolution Object detection programming Image sampling Inference algorithms

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Comprehensive operating system for highly parallel machine

Comprehensive operating system for highly parallel machine

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international symposium on parallel architectures, algorithms and Networks (ISPAN)

作者： N. Saito H. Tokuda T. Hagino S. Oikawa A. Yonezawa S. Matsuoka S. Inohara Y. Tada H. Sunahara S. Ishii E. Shibayama Y. Shinoda School of Environmental Information Keio University Graduate School of Science University of Tokyo Graduate School of Information Systems University of Electro-Communications Graduate School of Information Science and Technology Tokyo Institute of Technology Japan Advanced Institute of Science and Technology Hokuriku

This paper describes the design and implementation of a comprehensive operating system (COS) for highly parallel machine. This is one of the research themes in the Japanese University Highly parallel Research Project supported by the Special Grant of the Research Funds of Ministry of Education. The target machine is called JUMP-1 originally developed in this project. Several design policies are discussed, and the user service classes are defined. COS architecture is based on the micro kernel, and it includes both Partition OS and Service OS. The development environment is also discussed briefly.< >

关键词： Operating systems parallel machines Kernel Application software Algorithm design and analysis Hardware Information systems Information science parallel programming parallel architectures

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parallel tree building on a range of shared address space multiprocessors: algorithms and application performance

Parallel tree building on a range of shared address space mu...

引用

international symposium on parallel Processing

作者： H. Shan J.P. Singh Department of Computer Science Princeton University USA

Irregular, particle-based applications that use trees, for example hierarchical N-body applications, are important consumers of multiprocessor cycles, and are argued to benefit greatly in programming ease from a coherent shared address space programming model. As more and more supercomputing platforms that can support different programming models become available to users, from tightly-coupled hardware-coherent machines to clusters of workstations or SMPs, to truly deliver on its ease of programming advantages to application users it is important that the shared address space model not only perform and scale well in the tightly-coupled case but also port well in performance across the range of platforms (as the message passing model can). For tree-based N-body applications, this is currently not true: while the actual computation of interactions ports well, the parallel tree building phase can become a severe bottleneck on coherent shared address space platforms, in particular on platforms with less aggressive, commodity-oriented communication architectures (even though it takes less 3 percent of the time in most sequential executions). The authors therefore investigate the performance of five parallel tree building methods in the context of a complete galaxy simulation on four very different platforms that support this programming model.

关键词： Hardware Application software Message passing Protocols Partitioning algorithms Workstations Buildings Context modeling Coherence Dynamic programming

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A simple and efficient parallel disk mergesort

A simple and efficient parallel disk mergesort

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11th Annual ACM symposium on parallel algorithms and architectures

作者： Barve, RD Vitter, JS Winphoria Networks Andheri 400093 Mumbai India Duke Univ Dept Comp Sci Ctr Geometr & Biol Comp Durham NC 27708 USA

External sorting-the process of sorting a file that is too large to fit into the computer's internal memory and must be stored externally on disks-is a fundamental subroutine in database systems [G], [IBM]. Of prime importance are techniques that use multiple disks in parallel in order to speed up the performance of external sorting. The simple randomized merging (SRM) mergesort algorithm proposed by Barve et al. [BGV] is the first parallel disk sorting algorithm that requires a provably optimal number of passes and that is fast in practice. Knuth [K, Section 5.4.9] recently identified SRM (which he calls "randomized striping") as the method of choice for sorting with parallel disks. In this paper we present an efficient implementation of SRM, based upon novel and elegant data structures. We give a new implementation for SRM's lookahead forecasting technique for parallel prefetching and its forecast and flush technique for buffer management. Our techniques amount to a significant improvement in the way SRM carries out the parallel, independent disk accesses necessary to read blocks of input runs efficiently during external merging. Our implementation is based on synchronous parallel I/O primitives provided by the TPIE programming environment [TPI], whenever our program issues an I/O read (write) operation, one block of data is synchronously read from (written to) each disk in parallel. We compare the performance of SRM over a wide range of input sizes with that of disk-striped mergesort (DSM), which is widely used in practice. DSM consists of a standard mergesort in conjunction with striped I/O for parallel disk access. SRM merges together significantly more runs at a time compared with DSM, and thus it requires fewer merge passes. We demonstrate in practical scenarios that even though the streaming speeds for merging with DSM are a little higher than those for SRM (since DSM merges fewer runs at a time), sorting using SRM is often significantly faster than with DSM

关键词： Computation theory

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