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Communications in Computer and Information Science 2009年 17卷 252-261页

作者： Ma, Xiaodong Wang, Ji Dong, Wei National Laboratory for Parallel and Distributed Processing China

ISBN: (纸本)9783540884781

This paper presents a novel algorithm to detect null pointer dereference errors. The algorithm utilizes both of the must and may alias information in a compact way to improve the precision of the detection. Using may alias information obtained by a fast flow- and context- insensitive analysis algorithm, we compute the must alias generated by the assignment statements and the must alias information is also used to improve the precision of the may alias. We can strong update more expressions using the must alias information, which will reduce the false positives of the detection for null pointer dereference. We have implemented our algorithm in the SUIF2 compiler infrastructure and the experiments results are as expected. © Springer-Verlag Berlin Heidelberg 2008.

关键词： Information use

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A novel L1 cache based on volatile STT-RAM 20th

A novel L1 cache based on volatile STT-RAM

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20th Annual Conference on Computer Engineering and Technology, NCCET 2016

作者： Hongguang, Zhang Minxuan, Zhang College of Computer National University of Defense Technology Changsha410073 China National Key Laboratory of Parallel and Distributed Processing National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789811031588

Spin-transfer torque random access memory (STT-RAM) is one of the most promising substitutes for universal main memory and cache due to its excellent scalability, high density and low leakage power. Nevertheless, the current non-volatile STT-RAM cache architecture also has some drawbacks, such as long write latency and high write energy, which limit the application of STTRAM in the top level cache design. To solve these problems, we relax the retention time of STT-RAM to explore its different write performance, and propose a novel STT-RAM L1 cache architecture implemented with volatile STT-RAM as well as its related refresh scheme. The performance of proposed design is the same as SRAM L1 cache while its overall power consumption is only 63.8% of the latter one. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Static random access storage

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Application of grid to GRAPES meso-scale model

Application of grid to GRAPES meso-scale model

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2nd International Conference on Semantics, Knowledge, and Grid, SKG 2006

作者： Yang, Xuesheng Zhang, Weimin Liu, Yongzhu Chen, Dehui LASW/Chinese Academy of Meteorological Sciences Beijing 100081 China Parallel and Distributed Processing for National Laboratory Changsha China

ISBN: (纸本)076952673X

Considering the fact that the computing resources and NWP model developers within the framework of the China Meteorological Administration (CMA) are distributed widespread across the countries, and that the NWP systems very much depend on datasharing, remote collaborative research, heavy computation, massive data and intensive services, the Meso-scale Model Application Grid (MMAG) has been established based on the grid technology. Ultimately this platform has aggregated the distributed computing resources and NWP software at CAMS, NMIC, STI, GRMC and GXMB. The GRAPES Meso-scale model runs routinely on MMAG and users can access the NWP products at the designated website. It also provides a remote collaborative research environment for the geographical distributed scientists to make contributions to the improvement of the GRAPES. © 2006 IEEE.

关键词： distributed computer systems

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Communication Analysis for Multidimensional parallel Training of Large-scale DNN Models 25

Communication Analysis for Multidimensional Parallel Trainin...

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25th IEEE International Conferences on High Performance Computing and Communications, 9th International Conference on Data Science and Systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Lai, Zhiquan Hao, Yanqi Li, Shengwei Li, Dongsheng College of Computer National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing Changsha China

ISBN: (纸本)9798350330014

Multidimensional parallel training has been widely applied to train large-scale deep learning models like GPT-3. The efficiency of parameter communication among training devices/processes is often the performance bottleneck of large model training. Analysis of parameter communication mode and traffic has important reference significance for the research of interconnection network design and computing task scheduling to improve the training performance. In this paper, we analyze the parametric communication modes in typical 3D parallel training (data parallelism, pipeline parallelism, and tensor parallelism), and model the traffic in different communication modes. Finally, taking GPT-3 as an example, we present the communication in its 3D parallel training. © 2023 IEEE.

关键词： Deep neural networks

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SAWSDL service discovery based on Fine-Grained data semantics

SAWSDL service discovery based on Fine-Grained data semantic...

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作者： Wei, Dengping Wang, Ting Wang, Ji School of Computer National University of Defense Technology 410073 Changsha China National Laboratory for Parallel and Distributed Processing 410073 Changsha China

With the aim to improve the effectiveness of SAWSDL service discovery, this paper proposes a novel discovery method for SAWSDL services, which is based on the matchmaking of so-called finegrained data semantics that is defined via sets of atomic elements with built-in data types. The fine-grained data semantics can be obtained by a transformation algorithm that decomposes parameters at message level into a set of atomic elements, considering the characteristics of SAWSDL service structure and semantic annotations. Then, a matchmaking algorithm is proposed for the matching of fine-grained data semantics, which avoids the complex and expensive structural matching at the message level. The fine-grained data semantics is transparent to the specific data structure of message-level parameters, therefore, it can help to match successfully similar Web services with different data structures of parameters. Moreover, a comprehensive measure is proposed by considering together several important components of SAWSDL service descriptions at the same time. Finally, this method is evaluated on SAWSDL service discovery test collection SAWSDL-TC2 and compared with other SAWSDL matchmakers. The experimental results show that our method can improve the effectiveness of SAWSDL service discovery with low average query response time. The results imply that fine-grained parameters fit to represent the data semantics of SAWSDL services, especially when data structures of parameters are not important for semantics. © 2011 The Institute of Electronics, Information and Communication Engineers.

关键词： Data structures

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Failure-divergence refinement of compensating communicating processes

Failure-divergence refinement of compensating communicating ...

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Lecture Notes in Computer Science

作者： Chen, Zhenbang Liu, Zhiming Wang, Ji National Laboratory for Parallel and Distributed Processing Changsha China International Institute for Software Technology United Nations University China

ISBN: (纸本)9783642214363

Compensating CSP (cCSP) extends CSP for specification and verification of long running transactions. The original cCSP is a modest extension to a subset of CSP that does not consider non-deterministic choice, synchronized composition, and recursion. There are a few further extensions. However, it remains a challenge to develop a fixed-point theory of process refinement in cCSP. This paper provides a complete solution to this problem and develops a theory of cCSP, corresponding to the theory of CSP, so that the verification techniques and their tools, such as FDR, can be extended for compensating processes. © 2011 Springer-Verlag.

关键词： Fixed point arithmetic

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A multidimensional approach of evaluating developers 2020

A multidimensional approach of evaluating developers

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2nd International Conference on Big Data Engineering, BDE 2020

作者： Zhang, Changqiang Chen, Ming Key Laboratory of Parallel and Distributed Computing College of Computer National University of Defense Technology China

ISBN: (纸本)9781450377225

In this paper, we propose an approach to assess the ability of developers based on their behavior data from OSS. Specifically, we classify developers' ability into code ability, project management ability, and social ability. Code efficiency is related to the developer's commit record and the pull-request record. The developer's project management ability is achieved by tracking the developer's commit record. We use regular matching to map the commit behavior to the project management behavior and calculate the developer's project management ability according to the proportion of different behaviors. The social ability of developers is related to the data that developers interact with in the open-source community. We dug for developer reviews on commit, issue, and gist fragments. By calculating the proportion of positive emotions in developer reviews and the proportion of developers interacting with others in the reviews, the social ability of developers is obtained. We get behavioral data from 50 random developers. Twitter's data is used to test the effect of different machine learning algorithms on the accuracy of developer comment polarity judgments. It is found that the combination of SVM, xgboost and random forest have the highest prediction accuracy. Finally, we select 5 students to use Likert scale to score the results. Our score shows that the results are basically in line with expectations. © 2020 ACM.

关键词： Decision trees

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A survey of script learning

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Frontiers of Information Technology & Electronic Engineering 2021年第3期22卷 341-373页

作者： Yi HAN Linbo QIAO Jianming ZHENG Hefeng WU Dongsheng LI Xiangke LIAO Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense TechnologyChangsha 410000China Science and Technology on Information Systems Engineering Laboratory National University of Defense TechnologyChangsha 410000China School of Data and Computer Science Sun Yat-sen UniversityGuangzhou 510006China

Script is the structured knowledge representation of prototypical real-life event *** the commonsense knowledge inside the script can be helpful for machines in understanding natural language and drawing commonsensible *** learning is an interesting and promising research direction,in which a trained script learning system can process narrative texts to capture script knowledge and draw ***,there are currently no survey articles on script learning,so we are providing this comprehensive survey to deeply investigate the standard framework and the major research topics on script *** research field contains three main topics:event representations,script learning models,and evaluation *** each topic,we systematically summarize and categorize the existing script learning systems,and carefully analyze and compare the advantages and disadvantages of the representative *** also discuss the current state of the research and possible future directions.

关键词： Script learning Natural language processing Commonsense knowledge modeling Event reasoning

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Coordinate strip-mining and kernel fusion to lower power consumption on GPU

Coordinate strip-mining and kernel fusion to lower power con...

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作者： Wang, Guibin National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha Hunan China

ISBN: (纸本)9783981080179

Although general purpose GPUs have relatively high computing capacity, they also introduce high power consumption compared with general purpose CPUs. Therefore low-power techniques targeted for GPUs will be one of the most hot topics in the future. On the other hand, in several application domains, users are unwilling to sacrifice performance to save power. In this paper, we propose an effective kernel fusion method to reduce the power consumption for GPUs without performance loss. Different from executing multiple kernels serially, the proposed method fuses several kernels into one larger kernel. Owing to the fact that most consecutive kernels in an application have data dependency and could not be fused directly, we split large kernel into multiple slices with strip-mining method, then fuse independent sliced kernels into one kernel. Based on the CUDA programming model, we propose three different kernel fusion implementations, with each one targeting for a special case. Based on the different strip-ming methods, we also propose two fusion mechanisms, which are called invariant-slice fusion and variant-slice fusion. The latter one could be better adapted to the requirements of the kernels to be fused. The experimental results validate that the proposed kernel fusion method could effectively reduce the power consumption for GPU. © 2011 EDAA.

关键词： Electric power utilization

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Funnel: An Efficient Sparse Attention Accelerator with Multi-Dataflow Fusion 22

Funnel: An Efficient Sparse Attention Accelerator with Multi...

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22nd IEEE International Symposium on parallel and distributed processing with Applications, ISPA 2024

作者： Ma, Shenghong Xu, Jinwei Jiang, Jingfei Wang, Yaohua Li, Dongsheng National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing College of Computer Changsha China

ISBN: (纸本)9798331509712

The self-attention mechanism is the core component of Transformer, which provides a powerful ability to understand the sequence context. However, the self-attention mechanism also suffers from a large amount of redundant computation. Model sparsification can effectively reduce computational load, but the irregularity of non-zeros introduced by sparsification significantly decreases hardware efficiency. This paper proposes Funnel, an accelerator that dynamically predicts sparse attention patterns and efficiently processes unstructured sparse data. Firstly, we adopt a fast quantization method based on lookup table to minimize the cost of sparse patterns prediction. Secondly, we propose Funnel Computing Unit (FCU), a hardware architecture that efficiently handles sparse attention through multi-dataflow fusion. Sampled Dense-Dense Matrix Multiplication (SDDMM) and Sparse-Dense Matrix Multiplication (SpMM) are core components of sparse attention mechanism. FCU unifies the computation ways of matrix inner product and row-wise product to support SDDMM and SpMM at the same time, which greatly reduces the storage and movement overhead of intermediate results. Lastly, we devise a lightweight buffer and data tiling strategy tailored to the proposed accelerator, aimed at enhancing data reuse. Experiments demonstrate that our accelerator achieves 0.10-0.25 sparsity with small accuracy loss. When computing the self-attention layer, it attains hardware efficiency ranging from 60% to 85%. Compared to CPU and GPU, it achieves 5.60x and 8.20x speedup. Compared to the state-of-the-art attention accelerators A3, SpAtten, FTRANS, and Sanger, it achieves 7.37x, 4.52x, 9.58x, and 3.08x speedup. © 2024 IEEE.

关键词： FPGA Funnel computing unit Sparse attention Transformer

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