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International Symposium on parallel and distributed Processing (IPDPS)

作者： S. Punyamurtula V. Chaudhary Parallel and Distributed Computing Laboratory Department of Electrical and Computer Engineering Wayne State University Detroit MI USA Wayne State University

We address the problem of partitioning nested loops with non-uniform (irregular) dependence vectors. Although many methods exist for nested loop partitioning, most of these perform poorly when parallelizing nested loops with irregular dependencies. We apply the results of classical convex theory and principles of linear programming to iteration spaces and show the correspondence between minimum dependence distance computation and iteration space tiling. The cross-iteration dependencies are analyzed by forming an Integer Dependence Convex Hull (IDCH). A simple way to compute minimum dependence distances from the dependence distance vectors of the extreme points of the IDCH is presented. Using these minimum dependence distances the iteration space can be tiled. Iterations in a tile can be executed in parallel and the tiles can be executed with proper synchronization. We demonstrate that our technique gives much better speedup and extracts more parallelism than the existing techniques.< >

关键词： Tiles distributed computing Concurrent computing Vectors Linear programming parallel processing Laboratories Sequential analysis Data analysis Data mining

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Hierarchical diagnostic approach for performance problems in cloud computing platforms

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Tongxin Xuebao/Journal on Communications 2011年第7期32卷 114-124页

作者： Mi, Hai-Bo Wang, Huai-Min Cai, Hua Yin, Gang Zhou, Qi Sun, Ting-Tao Zhou, Yang-Fan National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China Computing Platform Alibaba Cloud Computing Company Hangzhou 310023 China Shenzhen Research Institute Chinese Univ. of Hong Kong Shenzhen 518057 China

A hierarchical diagnosis approach, namely Magnifier, was proposed, which models the execution path graph of a user request as component layer, module layer and function layer, and detects anomalies from higher layer to lower layer separately. Extensive experiments were conducted on the Alibaba cloud computing platform. The results indicate that, under the conditions of large volume of data and high complexity of execution paths, Magnifier can accurately and efficiently locate the prime causes of performance degradation.

关键词： Cloud computing

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High performance and memory efficient implementation of matrix multiplication on FPGAs

High performance and memory efficient implementation of matr...

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IEEE International Conference on Field-Programmable Technology (FPT)

作者： Guiming Wu Yong Dou Miao Wang National Laboratory of Parallel and Distributed Processing National University of Defense Technology Changsha China Jiangnan Institute of Computing Technology Wuxi China

We present a high performance and memory efficient hardware implementation of matrix multiplication for dense matrices of any size on the FPGA devices. By applying a series of transformations and optimizations on the original serial algorithm, we can obtain an I/O and memory optimized block algorithm for matrix multiplication on FPGAs. A linear array of processing elements (PEs) is proposed to implement this block algorithm. We show significant reduction in hardware resources consuming compared to the related work while increasing clock frequency. Moreover, the memory requirement can be reduced to O(S) from O(S 2 ), where S is the block size. Therefore, more PEs can be integrated into the same FPGA devices.

关键词： Field programmable gate arrays Arrays Random access memory Algorithm design and analysis Hardware Memory management Optimization

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An efficient parallel loop self-scheduling on grid environments

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IFIP International Conference on Network and parallel computing, NPC 2004

作者： Yang, Chao-Tung Cheng, Kuan-Wei Li, Kuan-Ching High Performance Computing Laboratory Dept. of Computer Science and Information Engineering Tunghai University Taichung407 Taiwan Parallel and Distributed Processing Center Dept. of Computer Science and Information Management Providence University Shalu Taichung433 Taiwan

ISBN: (纸本)3540233881

The approaches to deal with scheduling and load balancing on PC-based cluster systems are famous and well-known. Self-scheduling schemes, which are suitable for parallel loops with independent iterations on cluster computer system, they have been designed in the past. In this paper, we propose a new scheme that can adjust the scheduling parameter dynamically on an extremely heterogeneous PC-based cluster and grid computing environments in order to improve system performance. A grid computing environment consists of multiple PC-based clusters is constructed using Globus Toolkit and SUN Grid Engine middleware. The experimental results show that our scheduling can result in higher performance than other similar schemes. © IFIP International Federation for Information Processing 2004.

关键词： Scheduling

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Automatic synthesis of processor arrays with local memories on FPGAs

Automatic synthesis of processor arrays with local memories ...

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IEEE International Conference on Field-Programmable Technology (FPT)

In this paper, we present an automatic synthesis framework to map loop nests to processor arrays with local memories on FPGAs. An affine transformation approach is firstly proposed to address space-time mapping problem. Then a data-driven architecture model is introduced to enable automatic generation of processor arrays by extracting this data-driven architecture model from transformed loop nests. Some techniques including memory allocation, communication generation and control generation are presented. Synthesizable RTL codes can be easily generated from the architecture model built by these techniques. A preliminary synthesis tool is implemented based on PLUTO, an automatic polyhedral source-to-source transformation and parallelization framework.

关键词： parallel processing Registers Field programmable gate arrays Radiation detectors Arrays Computational modeling

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Network and service management and diagnostics solution of a remote patient monitoring system

Network and service management and diagnostics solution of a...

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International Symposium on Logistics and Industrial Informatics, LINDI

作者： Miklos Kozlovszky Zsolt Meixner Gergely Windisch Judit Márton Sándor Ács Pál Bogdanov Anikó Boruzs Péter Kotcauer János Ferenczi Viktor Kozlovszky Laboratory of Parallel and Distributed Computing MTA SZTAKI Budapest Hungary John von Neumann Faculty of Informatics Óbuda University Budapest Hungary

We have developed a combined network and service management and diagnostics solution for our in-house developed remote patient monitoring system. The developed system has included into the ALPHA eHealth/remote patient monitoring system and was successfully used in our large Living Lab infrastructure operating in three different Hungarian regions with 40 patients. In this paper we will identify the key elements of the combined Network and Service Management solution of the remote patient monitoring system.

关键词： Sensors Biomedical monitoring Medical diagnostic imaging Software Patient monitoring Educational institutions

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A Physics and Data-Driven Hybrid PINNs Intelligent computing Method for Nuclear Engineering Simulation 4

A Physics and Data-Driven Hybrid PINNs Intelligent Computing...

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4th International Conference on Electronic Information Engineering and Computer Science, EIECS 2024

作者： Xie, Yufei Wang, Wenlin Wu, Guohua Yu, Yang An, Ping Sun, Zibin Zhang, Haichuan Luo, Shengfeng Li, Yue School of Automation Wuhan University of Technology Wuhan China Sino-German College of Intelligent Manufacturing Shenzhen Technology University Shenzhen China Nuclear Power Institute of China Chengdu China National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing Changsha China

ISBN: (纸本)9798331531409

In the field of nuclear energy, the Loss of Coolant Accident (LOCA) is recognized as one of the most severe types of nuclear reactor accidents, characterized by its complex physical processes and potentially catastrophic consequences. These challenges impose stringent requirements on safety analysis and emergency response. Accurate prediction and analysis of fluid behavior within pipelines under LOCA conditions are critical for evaluating accident outcomes and formulating response strategies. This paper introduces an innovative intelligent computing approach - a Physics-Informed Neural Networks (PINNs) model driven by both physical data and simulation data, specifically tailored for LOCA conditions. To address the challenges posed by multivariable and complex physical relationships, the six-equation two-fluid model is first simplified to represent the physical processes. Subsequently, a dual-driven PINNs network is developed, integrating both simulation data and physical constraints. The proposed model demonstrates a root mean square error (RMSE) of 0.02, a mean absolute error (MAE) of 0.044, and an R2 of 0.81 in predicting the outcomes under the six-equation model. © 2024 IEEE.

关键词： Nuclear energy

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A comparison of parallel approaches for algebraic factorization in logic synthesis

A comparison of parallel approaches for algebraic factorizat...

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International Symposium on parallel Processing

作者： S. Roy P. Banerjee Coordinated Science Laboratory University of Illinois Urbana IL USA Center for Parallel & Distributed Computing Northwestern University Evanston IL USA

Algebraic factorization is an extremely important part of any logic synthesis system, but it is computationally expensive. Hence, it is important to look at parallel processing to speed up the procedure. This paper presents three different parallel algorithms for algebraic factorization. The first algorithm uses circuit replication and uses a divide-and-conquer strategy. A second algorithm uses totally independent factorization on different circuit partitions with no interactions among the partitions. A third algorithm represents a compromise between the two approaches. It uses a novel L-shaped partitioning strategy which provides some interaction among the rectangles obtained in various partitions. For a large circuit like ex1010, the last algorithm runs 11.5 times faster over the sequential kernel extraction algorithms of the SIS sequential circuit synthesis system on six processors with less than 0.2% degradation in quality of the results.

关键词： Logic functions Circuit synthesis Partitioning algorithms Network synthesis Contracts parallel processing Laser sintering Degradation Logic design Sequential circuits

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CHIME: A Cache-Efficient and High-Performance Hybrid Index on Disaggregated Memory 24

CHIME: A Cache-Efficient and High-Performance Hybrid Index o...

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30th ACM Symposium on Operating Systems Principles, SOSP 2024

作者： Luo, Xuchuan Shen, Jiacheng Zuo, Pengfei Wang, Xin Lyu, Michael R. Zhou, Yangfan National Key Laboratory of Parallel and Distributed Computing Changsha China School of Computer Science Fudan University Shanghai China Duke Kunshan University Kunshan China Huawei Cloud Shenzhen China Shanghai Key Laboratory of Intelligent Information Processing Shanghai China The Chinese University of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)9798400712517

Disaggregated memory (DM) is a widely discussed datacenter architecture in academia and industry. It decouples computing and memory resources from monolithic servers into two network-connected resource pools. Range indexes are widely adopted by storage systems on DM to efficiently locate and query remote data. However, existing range indexes on DM suffer from either high computing-side cache consumption or high memory-side read amplifications. In this paper, we propose CHIME, a hybrid index combining B+ trees with hopscotch hashing, to achieve low cache consumption and low read amplifications simultaneously. There are three challenges in constructing CHIME on DM, i.e., the complicated optimistic synchronization, the extra metadata access, and the read amplifications introduced by hopscotch hashing. CHIME leverages 1) a three-level optimistic synchronization scheme to synchronize read and write operations with various granularities, 2) an access-aggregated metadata management technique to eliminate extra metadata accesses by piggybacking and replicating metadata, and 3) an effective hotness-aware speculative read mechanism to mitigate the read amplifications of hopscotch hashing. Experimental results show that CHIME outperforms the state-of-the-art range indexes on DM by up to 5.1× with the same cache size and achieves similar performance with up to 8.7× lower cache consumption. © 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： Memory architecture

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An L-shaped partitioning-based algebraic factorization algorithm

An L-shaped partitioning-based algebraic factorization algor...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： S. Roy P. Banerjee Coordinated Science Laboratory University of Illinois Urbana IL USA Center for Parallel and Distributed Computing Northwestern University Evanston IL USA

Algebraic factorization is an extremely important part of any logic synthesis system but it is computationally expensive. Hence it is important to speed it up. The paper presents an algorithm to speedup the factorization by partitioning the circuit and performing factorizations on the sub-circuits. The approach clusters the entries of the co-kernel cube matrix into dense blocks using a novel L-shaped partitioning and searches these blocks for kernels. The L-shaped approach runs up to five times faster than the kernel extraction routine in SIS.

关键词： Partitioning algorithms Kernel Circuit synthesis distributed computing Network synthesis Contracts Logic functions Concurrent computing Clustering algorithms Logic design

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