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A new, fast, and efficient image codec based on set partitioning in hierarchical trees

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 1996年第3期6卷 243-250页

作者： Said, A Pearlman, WA RENSSELAER POLYTECH INST DEPT ELECT COMP & SYST ENGNTROYNY 12180

Embedded zerotree wavelet (EZW) coding, introduced by J. M. Shapiro, is a very effective and computationally simple technique for image compression, Here we offer an alternative explanation of the principles of its operation, so that the reasons for its excellent performance can be better understood, These principles are partial ordering by magnitude with a set partitioning sorting algorithm, ordered bit plane transmission, and exploitation of self-similarity across different scales of an image wavelet transform, Moreover, we present a new and different implementation based on set partitioning in hierarchical trees (SPIHT), which provides even better performance than our previously reported extension of EZW that surpassed the performance of the original EZW, The image coding results, calculated from actual file sizes and images reconstructed by the decoding algorithm, are either comparable to or surpass previous results obtained through much more sophisticated and computationally complex methods, In addition, the new coding and decoding procedures are extremely fast, and they can be made even faster, with only small loss in performance, by omitting entropy coding of the bit stream by arithmetic code.

关键词： Codecs Image coding partitioning algorithms Signal processing algorithms Decoding Signal processing Sorting Wavelet transforms Image reconstruction Performance loss

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A Probabilistic Niching Evolutionary Computation Framework Based on Binary Space partitioning

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IEEE TRANSACTIONS ON CYBERNETICS 2022年第1期52卷 51-64页

作者： Huang, Ting Gong, Yue-Jiao Chen, Wei-Neng Wang, Hua Zhang, Jun South China Univ Technol Sch Comp Sci & Engn Guangzhou 510006 Peoples R China Univ Victoria ISILC Melbourne Vic 8001 Australia

Multimodal optimization problems have multiple satisfactory solutions to identify. Most of the existing works conduct the search based on the information of the current population, which can be inefficient. This article proposes a probabilistic niching evolutionary computation framework that guides the future search based on more sufficient historical information, in order to locate diverse and high-quality solutions. A binary space partition tree is built to structurally organize the space visiting information. Based on the tree, a probabilistic niching strategy is defined to reinforce exploration and exploitation by making full use of the structural historical information. The proposed framework is universal for incorporating various baseline niching algorithms. In this article, we integrate the proposed framework with two niching algorithms: 1) a distance-based differential evolution algorithm and 2) a topology-based particle swarm optimization algorithm. The two new algorithms are evaluated on 20 multimodal optimization test functions. The experimental results show that the proposed framework helps the algorithms obtain competitive performance. They outperform a number of state-of-the-art niching algorithms on most of the test functions.

关键词： Sociology Statistics partitioning algorithms Topology Vegetation Probabilistic logic Optimization Binary space partition (BSP) evolutionary algorithm (EA) multimodal optimization probabilistic niching computation

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LOCAL RATIO CUT AND SET COVERING partitioning FOR HUGE LOGIC EMULATION SYSTEMS

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IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 1995年第9期14卷 1085-1092页

作者： CHOU, NC LIU, LT CHENG, CK DAI, WJ LINDELOF, R AT&T BELL LABS MURRAY HILLNJ 07974 UNIV CALIF SAN DIEGO DEPT COMP SCI & ENGNLA JOLLACA 92093

Given a system represented at gate level, we propose an algorithm mapping the design into the minimum number of FPGA's for logic emulation. We first devise a Local Ratiocut clustering scheme to reduce the circuit complexity. Then a Set Covering partitioning approach, utilizing the paradigm of Espresso II, is proposed as an alternative to the widely adopted recursive partitioning paradigm. Experimental results have shown that our approach achieved significant improvement with much shorter run times compared to the recursive Fiduccia-Mattheyses approach on large designs. For instance, on a benchmark of 160K gates and 90K nets, we reduced the number of FPGA's required and the run time by 41 and 86%, respectively.

关键词： Emulation partitioning algorithms Logic design Logic circuits Clustering algorithms Algorithm design and analysis Complexity theory Design methodology Hardware Fabrication

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partitioning and analysis of static digital CMOS circuits

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IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 1997年第11期16卷 1292-1310页

作者： Hubner, U Vierhaus, HT Camposano, R Tech Univ Brandenburg Cottbus Germany Synopsys Inc Mountain View CA USA

Performance optimization of automatic test pattern generation (ATPG) algorithms has received considerable attention. While the application of high-performance algorithms is often limited to simple gates such as AND's, OR's, and XOR, the cell libraries of silicon vendors usually contain more sophisticated structures. To deal with this problem, we present a library independent algorithm for the partitioning and analysis of static digital CMOS circuits described at the snitch level. The algorithm recognizes inverters, NAND's, and NOR's. It also checks whether a partition can set ifs output to a high impedance state, thus being capable of partitioning large bus structures with tristate gates. Our approach supports existing ATPG algorithms at the gate level, Moreover, it allows a mixed-level approach for ATPG using detailed fault models at the switch level for whatever partitions it is necessary. Our implementation processes in the alder of 2000 transistors per second. This is for circuits containing combinational and sequential logic on a state-of-the-art workstation, We processed complete chips with up to 72 000 transistors, which is clearly adequate for practical purposes.

关键词： CMOS digital integrated circuits partitioning algorithms Automatic test pattern generation Switches Software libraries Optimization Silicon Algorithm design and analysis Switching circuits Inverters

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A New Combinatorial Characteristic Parameter for Clustering-Based Traffic Network partitioning

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IEEE ACCESS 2019年 7卷 40175-40182页

作者： Liu, Duanyang Wang, Mengting Shen, Guojiang Zhejiang Univ Technol Coll Comp Sci & Technol Hangzhou 310023 Zhejiang Peoples R China

Traffic network partitioning is of great importance in regional coordinated traffic signal control in urban areas. Most partitioning algorithms only use a single traffic parameter to represent dynamic traffic information, which will lead to inaccurate results. Moreover, traditional clustering and heuristic partitioning algorithms are not practical in applications. Thus, in this paper, we first propose a new combinatorial characteristic parameter for clustering-based partitioning algorithm by using the Pearson correlation coefficient and data normalization. Then, we refer to the idea of "snake'' algorithm and use a linear programming model to obtain the exact partitioning result, and such algorithm avoids local optimum of heuristic algorithms. Finally, based on the real traffic data of a Chinese city, we conduct the experiments and verify the effectiveness of the new combinatorial parameter.

关键词： Intelligent transportation systems partitioning algorithms clustering methods correlation linear programming

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A NEURAL NETWORK DESIGN FOR CIRCUIT partitioning

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IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 1990年第12期9卷 1265-1271页

作者： YIH, JS MAZUMDER, P Dept. of Electr. Eng. & Comput. Sci. Michigan Univ. Ann Arbor MI USA Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA

A neural network model is proposed for circuit bipartitioning. The massive parallelism of neural nets has been successfully exploited to balance the partitions of circuit and to reduce the external wiring between the partitions. The experimental results obtained by neural nets are found to be comparable with those achieved by the C.M. Fiduccia and R.M. Mattheyses (1982) algorithm. The proposed approach can be implemented in hardware to accelerate time-consuming partitioning procedures.< >

关键词： Neural networks partitioning algorithms Wires Artificial neural networks Wiring Parallel processing Hardware Acceleration Integrated circuit interconnections Minimization

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partitioning Stateful Data Stream Applications in Dynamic Edge Cloud Environments

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IEEE TRANSACTIONS ON SERVICES COMPUTING 2022年第4期15卷 2368-2381页

作者： Ding, Shaoshuai Yang, Lei Cao, Jiannong Cai, Wei Tan, Mingkui Wang, Zhenyu South China Univ Technol Sch Software Engn Guangzhou 510641 Peoples R China Hong Kong Polytech Univ Dept Comp Hong Kong Peoples R China Chinese Univ Hong Kong Sch Sci & Engn Shenzhen 518000 Guangdong Peoples R China Shenzhen Inst Artificial Intelligence & Robot Soc Shenzhen 518000 Peoples R China

Computation partitioning is an important technique to improve the application performance by selectively offloading some computations from the mobile devices to the nearby edge cloud. In a dynamic environment in which the network bandwidth to the edge cloud may change frequently, the partitioning of the computation needs to be updated accordingly. The frequent updating of partitioning leads to high state migration cost between the mobile side and edge cloud. However, existing works don't take the state migration overhead into consideration. Consequently, the partitioning decisions may cause significant network congestion and increase overall completion time tremendously. In this article, with considering the state migration overhead, we propose a set of novel algorithms to update the partitioning based on the changing network bandwidth. To the best of our knowledge, this is the first work on computation partitioning for stateful data stream applications in dynamic environments. The algorithms aim to alleviate the network congestion and minimize the make-span through selectively migrating state in dynamic edge cloud environments. Extensive simulations show our solution not only could selectively migrate state but also outperforms other classical benchmark algorithms in terms of make-span. The proposed model and algorithms will enrich the scheduling theory for stateful tasks, which has not been explored before.

关键词： Cloud computing Mobile handsets partitioning algorithms Heuristic algorithms Object tracking Data models Servers Edge cloud computation partitioning stateful data stream applications

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PDD: partitioning DAG-Topology DNNs for Streaming Tasks

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IEEE INTERNET OF THINGS JOURNAL 2024年第6期11卷 9258-9268页

作者： Wu, Liantao Gao, Guoliang Yu, Jing Zhou, Fangtong Yang, Yang Wang, Tengfei East China Normal Univ Software Engn Inst Shanghai Key Lab Trustworthy Comp Shanghai 200062 Peoples R China ShanghaiTech Univ Sch Informat Sci & Technol Shanghai 201210 Peoples R China Hong Kong Univ Sci & Technol Guangzhou IoT Thrust Guangzhou 510000 Peoples R China Wuhan Univ Technol State Key Lab Maritime Technol & Safety Wuhan 430063 Peoples R China Wuhan Univ Technol Sch Transportat & Logist Engn Wuhan 430063 Peoples R China

To enable the inference of high-precision deep neural networks (DNNs) on resource-constrained devices, DNN offloading has been widely explored in recent years. Some works have also integrated the chain-topology DNN (CDNN) offloading with pipeline processing to further reduce inference delay when processing streaming tasks. To improve the accuracy of the inference results, the topology of DNN tends to evolve from chain topology to directed acyclic graph (DAG) topology. However, most of the existing works do not study partitioning and offloading DAG-topology DNNs (DDNNs) for streaming tasks. Moreover, when partitioning computationally expensive DNN models, multipartitioning probably outperforms the bi-partitioning method, and most of the works do not study multipartitioning DAG-topology DNNs. In this article, we propose a more general multipartitioning and offloading method for large-scale DDNNs to process streaming tasks, which can adaptively partition DDNNs into multiple parts considering the computing power and bandwidth of all available computing units. Specifically, we first present a transforming method based on topological sorting that can losslessly transform DAG-topology DNNs into CDNNs. Then, based on greedy and dichotomy ideas, a multipartitioning algorithm is designed to partition and offload CDNNs. In this way, we can solve DDNNs' multipartitioning problem based on the proposed transforming and partitioning algorithms. Experimentshttps://***/sreasearcher/PDD-Code show that the method proposed in this article significantly outperforms bi-partitioning and nonpartitioning methods when offloading computationally expensive DNN models.

关键词： Computational modeling Task analysis Artificial neural networks Delays Copper partitioning algorithms Topology Directed acyclic graph (DAG) topology deep neural network (DNN) partitioning streaming tasks

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Distributed Pose-Graph Optimization With Multi-Level partitioning for Multi-Robot SLAM

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IEEE ROBOTICS AND AUTOMATION LETTERS 2024年第6期9卷 4926-4933页

作者： Li, Cunhao Guo, Guanghui Yi, Peng Hong, Yiguang Tongji Univ Dept Control Scienceand Engn Shanghai 200070 Peoples R China Tongji Univ Shanghai Res Inst Intelligent Autonomous Syst Sci Ctr Intelligent Autonomous Syst Natl Key Lab Autonomous Intelligent Unmanned Syst Shanghai 200070 Peoples R China

The back-end module of Distributed Collaborative Simultaneous Localization and Mapping (DCSLAM) requires solving a nonlinear Pose Graph Optimization (PGO) under a distributed setting, also known as SE(d)-synchronization. Most existing distributed graph optimization algorithms employ a simple sequential partitioning scheme, which may result in unbalanced subgraph dimensions due to the different geographic locations of each robot, and hence imposes extra communication load. Moreover, the performance of current Riemannian optimization algorithms can be further accelerated. In this letter, we propose a novel distributed pose graph optimization algorithm combining multi-level partitioning with an accelerated Riemannian optimization method. Firstly, we employ the multi-level graph partitioning algorithm to preprocess the naive pose graph to formulate a balanced optimization problem. In addition, inspired by the accelerated coordinate descent method, we devise an Improved Riemannian Block Coordinate Descent (IRBCD) algorithm and the critical point obtained is globally optimal. Finally, we evaluate the effects of four common graph partitioning approaches on the correlation of the inter-subgraphs, and discover that the Highest scheme has the best partitioning performance. Also, we implement simulations to quantitatively demonstrate that our proposed algorithm outperforms the state-of-the-art distributed pose graph optimization protocols.

关键词： Optimization Robots partitioning algorithms Robot kinematics Simultaneous localization and mapping Collaboration Manifolds Distributed pose graph optimization graph partitioning CSLAM accelerated riemannian optimization

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OPTIMIZED partitioning OF A WAVELENGTH DISTRIBUTED DATA INTERFACE RING NETWORK

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JOURNAL OF LIGHTWAVE TECHNOLOGY 1995年第10期13卷 1971-1984页

作者： RAMAMURTHY, S MUKHERJEE, B MOSLEHI, B OPTIVIS INC PALO ALTOCA 94304

A fiber optic ring network, such as Fiber Distributed Data Interface (FDDI), can be operated over multiple wavelengths on its existing fiber plant consisting of point-to-point fiber links. Using wavelength division multiplexing (WDM) technology, FDDI nodes can be partitioned to operate over multiple subnetworks, with each subnetwork operating independently on a different wavelength, and inter-subnetwork traffic forwarding performed by a bridge, For this multiwavelength version of FDDI, which we refer to as Wavelength Distributed Data Interface (WDDI), we examine the necessary upgrades to the architecture of a FDDI node, including its possibility to serve as a bridge. The main motivation behind this study is that, as network traffic scales beyond (the single-wavelength) FDDI's information-carrying capacity, its multiwavelength version, WDDI, can gracefully accommodate such traffic growth, A number of design choices exist in constructing a good WDDI network. Specifically, we investigate algorithms using which, based on prevailing traffic conditions, partitioning of nodes into subnetworks can be performed in an optimized fashion. Our algorithms partition the nodes into subrings, such that the total traffic flow in the network and/or the network-wide average packet delay is minimized.

关键词： FDDI Wavelength division multiplexing Optical fiber networks Telecommunication traffic Optical fibers Bridges partitioning algorithms Optical fiber devices Telecommunication network reliability Fault detection

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