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An Efficient and Flexible Deterministic Framework for Multithreaded Programs

Journal of Computer science & technology 2015年第1期30卷 42-56页

作者：卢凯周旭王小平 Tom Bergan 陈沉 Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha 410073 China College of Computer National University of Defense Technology Changsha 410073 China Department of Computer Science and Engineering University of Washington Seattle WA 98195-2350 U.S.A.

Determinism is very useful to multithreaded programs in debugging, testing, etc. Many deterministic ap- proaches have been proposed, such as deterministic multithreading （DMT） and deterministic replay. However, these sys- tems either are inefficient or target a single purpose, which is not flexible. In this paper, we propose an efficient and flexible deterministic framework for multithreaded programs. Our framework implements determinism in two steps： relaxed determinism and strong determinism. Relaxed determinism solves data races eificiently by using a proper weak memory consistency model. After that, we implement strong determinism by solving lock contentions deterministically. Since we can apply different approaches for these two steps independently, our framework provides a spectrum of deterministic choices, including nondeterministic system （fast）, weak deterministic system （fast and conditionally deterministic）, DMT system, and deternfinistic replay system. Our evaluation shows that the DMT configuration of this framework could even outperform a state-of-the-art DMT system.

关键词： determinism multithreading framework flexible

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Identifying repeated interleavings to improve the efficiency of concurrency bug detection 15th

Identifying repeated interleavings to improve the efficiency...

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15th International Conference on Algorithms and Architectures for parallel processing, ICA3PP 2015

作者： Wu, Zhendong Lu, Kai Wang, Xiaoping Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha410073 China

ISBN: (纸本)9783319271392

Detecting concurrency bugs is becoming increasingly important. Many pattern-based concurrency bug detectors focus on the specific types of interleavings that are correlated to concurrency bugs. To detect multiple types of concurrency bugs, general detectors focus on multiple types of interleaving patterns, including data race pattern, atomicity violation pattern, and atomic-set violation pattern. Unfortunately, they suffer from redundant analysis due to repeated interleavings, which may affect the efficiency of concurrency bug detection. Hence, we propose an approach to identify the repeated interleavings. To the best of our knowledge, this is the first approach that can prune repeated interleavings to improve the efficiency of concurrency bug detection. We apply our approach to existing general detectors (PECAN and Maple) to avoid analyzing repeated interleavings. We evaluated the general detectors with and without our approach, respectively. The experimental results show that the bug detection results are not affected. With our approach, the bug detection time of PECAN and Maple are reduced by 40.0% and 44.4%, respectively. Additionally, our approach does not affect the overhead of bug detection, and consumes only a little memory. © Springer International Publishing Switzerland 2015.

关键词： Efficiency

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EmSBoT: A lightweight modular software framework for networked robotic systems

EmSBoT: A lightweight modular software framework for network...

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International Conference on Advances in Computational Tools for Engineering Applications, ACTEA

作者： Long Peng Fei Guan Luc Perneel Hasan Fayyad-Kazan Martin Timmerman Department of Electronics and Informatics Vrije Universiteit Brussel (VUB) Brussel-Belgium National Key Laboratory of Parallel and Distributed Processing National University of Defense Technology Changsha China

ISBN: (纸本)9781467385244

Developing applications for modern complex networked robotic systems is more challenging due to the introduction of possibly sophisticated communication and coordination aspects. In this paper, we propose EmSBoT, a lightweight embedded component-based software framework targeting resource-constrained networked robotic systems. EmSBoT provides a unified Application Program Interface (API) that hides the heterogeneous distributed environment from applications. Its OS abstraction layer endows it with OS independence and portability. A port-based communication mechanism is adopted to exchange message between loosely coupled components, making the system with fault-tolerance capability. By isolating the communication channels as separate agents, the framework provides uniform and transparent message-passing for agents over node boundaries. We describe the architecture, programming model and core features of EmSBoT in this paper, together with the performance evaluation and behavior validation to demonstrate its efficiency and feasibility.

关键词： Ports (Computers) Robot kinematics Real-time systems Programming Operating systems

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Area-efficient high-throughput sorted QR decomposition-based MIMO detector on FPGA

Area-efficient high-throughput sorted QR decomposition-based...

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IEEE International Conference on Computer and Communications, ICCC 2015

作者： Zhou, Tong Guo, Song Lei, Yuanwu Dou, Yong National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

ISBN: (纸本)9781467381253

This paper aimed to improve MIMO detector's performance in both throughput and cost. Thus, it presents a FPGA architecture implementation for the SQRD detection in a 4 × 4 16-QAM MIMO wireless communication systems. The exploitation of fine-grained parallelism and coarse-grained parallelism strategies are responsible for bettering the performance of the implementation. Besides, this paper proposes a method to ensure the correctness of the implementation of time-sharing modules, which is general and applicable to any MIMO detector implementation. The work results in a real-time FPGA-based implementation delivering 32 MSQRD/s with 5.2 us latency and lowering more than 50\% cost in hardware resources on a Xilinx Virtex6. © 2015 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Optimized deep belief networks on CUDA GPUs

Optimized deep belief networks on CUDA GPUs

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International Joint Conference on Neural Networks, IJCNN 2015

作者： Li, Teng Dou, Yong Jiang, Jingfei Wang, Yueqing Lv, Qi National Laboratory for Parallel and Distributed Processing National University of Defense and Technology Changsha China

ISBN: (纸本)9781479919604

A deep belief network (DBN) is an important branch of deep learning models and has been successfully applied in many machine learning and pattern recognition fields such as computer vision and speech recognition. However, the training of billions of parameters in DBN is computationally challenging for modern central processing units (CPUs). Many studies have reported the efficient implementations of the pre-training process of DBNs for graphics processing units (GPUs), but few studies have mentioned the fine-tuning process of DBNs. In this paper, we describe an efficient DBN implementation on the GPU, including the pre-training and fine-tuning processes. Experimental results show that our proposed method on the GPU (NVIDIA Tesla K40c) achieves up to 22 speedups on the pre-training process and 33 speedups on the fine-tuning processes compared with conventional CPU (Intel Core i7-4790K) implementations. Moreover, the performance of our algorithm is superior to that of the OpenBLAS library on the CPU and the CUBLAS library on the GPU. © 2015 IEEE.

关键词： Graphics processing unit

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Cooperative repair based on tree structure for multiple failures in distributed storage systems with regenerating codes 15

Cooperative repair based on tree structure for multiple fail...

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12th ACM International Conference on Computing Frontiers, CF 2015

作者： Pei, Xiaoqiang Wang, Yijie Ma, Xingkong Fu, Yongquan Xu, Fangliang Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha Hunan410073 China

ISBN: (纸本)9781450333580

Regenerating codes have been proposed to achieve an optimal trade-off curve between the amount of storage space and the network traffic for repair. However, existing repair schemes based on regenerating codes are inadequate to meet the requirements of small network traffic cost and high efficiency when repairing multiple failures. In this paper, we propose a cooperative repair scheme based on tree structure for multiple failures with regenerating codes, called CTREE. For generality, we propose a two-layer repair framework to support both repairs for single and multiple failures. For high repair efficiency, a parallel tree-structured data transmission technique is proposed to organize the data transmissions between the providers and newcomers. For small network network traffic cost, a core-based data exchange technique is proposed to organize the data exchanges between the coordinator and the other newcomers. To evaluate the performance of CTREE, we conduct experiments on both 30 physical and 200 virtual servers. Numerical analysis and extensive experiments confirm that CTREE can support both single and multiple failure repairs, significantly reduces the network traffic cost and improves the repair efficiency compared with the state-of-the-art approaches under various parameter settings. © Copyright 2015 ACM.

关键词： Repair

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Efficient detection of dangling pointer error for C/C++ programs

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Journal of Physics: Conference Series 2017年第1期887卷

作者： Wenzhe Zhang Science and Technology on Parallel and Distributed Laboratory State Key Laboratory of High Performance Computing State Key Laboratory of High-end Server & Storage Technology College of Computer National University of Defense Technology Changsha PR China

Dangling pointer error is pervasive in C/C++ programs and it is very hard to detect. This paper introduces an efficient detector to detect dangling pointer error in C/C++ programs. By selectively leave some memory accesses unmonitored, our method could reduce the memory monitoring overhead and thus achieves better performance over previous methods. Experiments show that our method could achieve an average speed up of 9% over previous compiler instrumentation based method and more than 50% over previous page protection based method.

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parallel pipeline implementation for moving objects detection in traffic video analysis on a heterogeneous platform 4th

Parallel pipeline implementation for moving objects detectio...

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4th International Conference on Computer Engineering and Networks, CENet2014

作者： Li, Teng Dou, Yong Jiang, Jingfei Qiao, Peng Department of Computer Science National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha410073 China

ISBN: (纸本)9783319111032

Moving objects detection is important in traffic video analysis, and many algorithms are being increasingly applied to moving objects detection. Most of these algorithms are time-consuming and cannot satisfy real-time demand in traffic video analysis by using a conventional central processing unit (CPU) sequential method. The emergence of the graphics processing unit (GPU) and multi-core CPU provides a method to accelerate the aforementioned algorithms to meet demand. In this study, we provide a GPU-accelerated implementation of the background subtraction algorithm and the morphological operation algorithm. Then, the connected component labeling algorithm is parallelized on a multi-core CPU with Open Multi-processing (OpenMP). Furthermore, parallel pipeline implementation on a heterogeneous platform is proposed by integrating the aforementioned algorithms. Experimental results show that the proposed implementation achieves a significant speedup of up to 5×, compared with sequential implementation on a CPU. © Springer International Publishing Switzerland 2015.

关键词： Program processors

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Deadline-oriented task scheduling for mapreduce environments 15th

Deadline-oriented task scheduling for mapreduce environments

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15th International Conference on Algorithms and Architectures for parallel processing, ICA3PP 2015

作者： Hu, Minghao Wang, Changjian You, Pengfei Huang, Zhen Peng, Yuxing National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha410072 China

ISBN: (纸本)9783319271217

To provide timely results for ‘Big Data Analytics’, it is crucial to satisfy deadline requirements for MapReduce jobs in production environments. In this paper, we propose a deadline-oriented task scheduling approach, named Dart, to meet the given deadline and maximize the input size if only part of the dataset can be processed before the time limit. Dart uses an iterative estimation method which is based on both historical data and job running status to precisely estimate the realtime job completion time. By comparing the estimated time with the deadline constraint, a YARN-based task scheduler dynamically decides whether continuing or terminating the map *** have validated our approach using workloads from OpenCloud and Facebook on a cluster of 60 virtual machines. The results show that Dart can not only effectively meet the deadline but also process near-maximal data volumes even when the deadline is set to be extremely small and limited resources are allocated. © Springer International Publishing Switzerland 2015.

关键词： MapReduce

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Hyperspectral image classification via kernel extreme learning machine using local receptive fields

Hyperspectral image classification via kernel extreme learni...

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IEEE International Conference on Image processing

作者： Qi Lv Xin Niu Yong Dou Yueqing Wang Jiaqing Xu Jie Zhou College of Computer National University of Defense Technology Changsha China National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China National University of Defense Technology Changsha Hunan CN

This paper proposes a classification approach for hyperspectral image (HSI) using the local receptive fields based kernel extreme learning machine. Extreme learning machine (ELM) has drawn increasing attention in the pattern recognition filed due to its simpleness, speediness and good generalization ability. A kernel method is often used to promote ELM's performance, which is known as kernel ELM. The local receptive field concept originates from research in neuroscience. Considering the local correlations of spectral features, it is promising to improve the performance of HSI classification by combining local receptive fields with kernel ELM. Experimental results on the Pavia University dataset confirm the effectiveness of the proposed HSI classification method.

关键词： Kernel Training Hyperspectral imaging Convolution Neurons Feature extraction

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