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Annual ACM-SIAM Symposium on Discrete algorithms

作者： Isabelle Stanton Google Inc.

ISBN: (纸本)9781611973389

With recent advances in storage technology, it is now possible to store the vast amounts of data generated by cloud computing applications. The sheer size of `big data' motivates the need for streaming algorithms that can compute approximate solutions without full random access to all of the data. In this paper, we consider the problem of loading a graph onto a distributed cluster with the goal of optimizing later computation. We model this as computing an approximately balanced k-partitioning of a graph in a streaming fashion with only one pass over the data. We give lower bounds on this problem, showing that no algorithm can obtain an o(n) approximation with a random or adversarial stream ordering. We analyze two variants of a randomized greedy algorithm (looking at the distribution of edges from the vertex to be assigned, one prefers the partition that is the arg max and one that assigns the vertex proportional to the edge distribution) on random graphs with embedded balanced k-cuts and are able to theoretically bound the performance of each algorithms - the arg max algorithm is able to recover the embedded k-cut while the proportional variant can not. This matches the experimental results in [30].

关键词： Streaming ASSAY SCALE Storage technologies partitioning algorithms big data Line graph Random algorithms Arginine arg Lower bound

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Process variation-aware workload partitioning algorithms for GPUs supporting spatial-multitasking 14

Process variation-aware workload partitioning algorithms for...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Paula Aguilera Jungseob Lee Amin Farmahini-Farahani Katherine Morrow Michael Schulte Nam Sung Kim University of Wisconsin Madison Advanced Micro Devices

ISBN: (纸本)9783981537024

High-level programming languages have transformed graphics processing units (GPUs) from domain-restricted devices into powerful compute platforms. Yet many “generalpurpose GPU” (GPGPU) applications fail to fully utilize the GPU resources. Executing multiple applications simultaneously on different regions of the GPU (spatial multitasking) thus improves system performance. However, within-die process variations lead to significantly different maximum operating frequencies (F max ) of the streaming multiprocessors (SMs) within a GPU. As the chip size and number of SMs per chip increase, the frequency variation is also expected to increase, exacerbating the problem. The increased number of SMs also provides a unique opportunity: we can allocate resources to concurrently-executing applications based on how those applications are affected by the different available F max values. In this paper, we study the effects of per-SM clocking on spatial multitasking-capable GPUs. We demonstrate two factors that affect the performance of simultaneously-running applications: (i) the SM partitioning algorithm that decides how many resources to assign to each application, and (ii) the assignment of SMs to applications based on the operating frequencies of those SMs and the applications characteristics. Our experimental results show that spatial multitasking that partitions SMs based on application characteristics, when combined with per-SM clocking, can greatly improve application performance by up to 46% on average compared to cooperative multitasking with global clocking.

关键词： Graphics processing units Multitasking Clocks Business process re-engineering partitioning algorithms Kernel Frequency control

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Coupling-aware graph partitioning algorithms: Preliminary study

Coupling-aware graph partitioning algorithms: Preliminary st...

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International Conference on High Performance Computing

作者： Maria Predari Aurélien Esnard Univ. Bordeaux LaBRI Talence France CNRS LaBRI Talence France

In the field of scientific computing, load balancing is a major issue that determines the performance of parallel applications. Nowadays, simulations of real-life problems are becoming more and more complex, involving numerous coupled codes, representing different models. In this context, reaching high performance can be a great challenge. In this paper, we present graph partitioning techniques, called co-partitioning, that address the problem of load balancing for two coupled codes: the key idea is to perform a “coupling-aware” partitioning, instead of partitioning these codes independently, as it is usually done. Finally, we present a preliminary experimental study which compares our methods against the usual approach.

关键词： Couplings Program processors Computational modeling partitioning algorithms Load modeling Load management Atmospheric modeling

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Optimal Online Balanced Graph partitioning 40

Optimal Online Balanced Graph Partitioning

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40th IEEE Conference on Computer Communications (IEEE INFOCOM)

作者： Pacut, Maciej Parham, Mahmoud Schmid, Stefan Univ Vienna Fac Comp Sci Vienna Austria

ISBN: (纸本)9780738112817

Distributed applications generate a significant amount of network traffic. By collocating frequently communicating nodes (e.g., virtual machines) on the same clusters (e.g., server or rack), we can reduce the network load and improve application performance. However, the communication pattern of different applications is often unknown a priori and may change over time, hence it needs to be learned in an online manner. This paper revisits the online balanced partitioning problem that asks for an algorithm that strikes an optimal tradeoff between the benefits of collocation (i.e., lower network load) and its costs (i.e., migrations). Our first contribution is a significantly improved deterministic lower bound of Omega(k . l) on the competitive ratio, where l is the number of clusters and k is the cluster size, even for a scenario in which the communication pattern is static and can be perfectly partitioned;we also provide an asymptotically tight upper bound of O (k . l) for this scenario. For k = 3, we contribute an asymptotically tight upper bound of Theta(l) for the general model in which the communication pattern can change arbitrarily over time. We improve the result for k = 2 by providing a strictly 6-competitive upper bound for the general model.

关键词： Upper bound Computational modeling Conferences Clustering algorithms Telecommunication traffic Virtual machining partitioning algorithms

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Late Breaking Results: Novel Discrete Dynamic Filled Function Algorithm for Acyclic Graph partitioning 58

Late Breaking Results: Novel Discrete Dynamic Filled Functio...

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58th ACM/IEEE Design Automation Conference (DAC)

作者： Chen, Jianli Chen, Jiarui Shi, Xiao Sun, Lichong Yu, Jun Fudan Univ State Key Lab ASIC & Syst Shanghai 200433 Peoples R China Fuzhou Univ Ctr Discrete Math & Theoret Comp Sci Fuzhou 350108 Peoples R China Southeast Univ Sch Comp Sci & Engn Nanjing 210096 Peoples R China HiSilicon Technol Co Ltd Shenzhen 518129 Peoples R China

ISBN: (纸本)9781665432740

A parallel simulation that partitions a large circuit into sub-circuits is widely used to reduce simulation rtmtime. To achieve higher simulation throughput, we shall consider signal directions, and thus the final partitioning solution must he acyclic. In this paper, we model a circuit as a directed graph imd consider acyclic graph partitioning to minimize edge cuts. This problem differs from the traditional partitioning problem because of the additional acyclicity constraint. Unlike traditional heuristics that tend to be trapped in local minima, especially for large graphs, we present a novel discrete dynamic filled function algorithm for the acyclic graph partitioning problem. Our algorithm can guarantee convergence and effectively move from one discrete local minimizer to another better one. Experimental results show that our algorithm achieves 8% average cutsize reduction over the state-of-the-art works in a comparable runtime.

关键词： Runtime Design automation Heuristic algorithms Directed graphs Throughput partitioning algorithms Integrated circuit modeling

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Fast Multi-Type Tree Partition for H.266/VVC Inter Coding

Fast Multi-Type Tree Partition for H.266/VVC Inter Coding

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IEEE International Conference on Consumer Electronics - Taiwan (ICCE-TW)

作者： Ciou, Yi-Sheng Chen, Mei-Juan Yeh, Chia-Hung Lu, Chen-Rung Hsieh, Meng-Chun Lo, Chen Natl Dong Hwa Univ Dept Elect Engn Hualien Taiwan Natl Taiwan Normal Univ Dept Elect Engn Taipei Taiwan Natl Sun Yat Sen Univ Dept Elect Engn Kaohsiung Taiwan

ISBN: (数字)9781665470506

ISBN: (纸本)9781665470506

Versatile Video Coding (H.266/VVC), the latest international video coding standard, effectively encodes ultra-high-definition video. Compared to the quadtree (QT) split of High Efficiency Video Coding (H.265/HEVC), the quadtree with nested multi-type tree (QT-MTT) structure applying binary tree (BT) and ternary tree (TT) coding blocks in H.266/VVC provides various coding unit (CU) partitions. The functionality improves the compression performance but greatly increases encoding complexity. Therefore, the acceleration of encoding is an essential issue. In this paper, the image feature extracted by edge detection is utilized to make fast decisions about the TT split and direction in the MTT structure of CU. Moreover, the maximum partition depth of the coding tree unit is predicted from the reference frames for the early termination of the encoding process. Experimental results demonstrate that the coding time of the proposed algorithm is reduced while the bitrate is well-maintained under random access configuration. The proposed method significantly outperforms the previous work.

关键词： Image coding Correlation Image edge detection Prediction algorithms Feature extraction Encoding partitioning algorithms

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On Coverage Control for Limited Range Multi-Robot Systems

On Coverage Control for Limited Range Multi-Robot Systems

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Pratissoli, Federico Capelli, Beatrice Sabattini, Lorenzo Univ Modena & Reggio Emilia Dept Sci & Methods Engn DISMI Modena Italy

ISBN: (数字)9781665479271

ISBN: (纸本)9781665479271

This paper presents a coverage based control algorithm to coordinate a group of autonomous robots. Most of the solutions presented in the literature rely on an exact Voronoi partitioning, whose computation requires complete knowledge of the environment to be covered. This can be achieved only by robots with unlimited sensing capabilities, or through communication among robots in a limited sensing scenario. To overcome these limitations, we present a distributed control strategy to cover an unknown environment with a group of robots with limited sensing capabilities and in the absence of reliable communication. The control law is based on a limited Voronoi partitioning of the sensing area, and we demonstrate that the group of robots can optimally cover the environment using only information that is locally detected (without communication). The proposed method is validated by means of simulations and experiments carried out on a group of mobile robots.

关键词： Robot kinematics Decentralized control Robot sensing systems Sensors partitioning algorithms Reliability Multi-robot systems

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Optimal EVs Charge Station Allocation Considering Residents Dispersion Using a Genetic Algorithm and Weighted K-Means

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IEEE ACCESS 2024年 12卷 191071-191085页

作者： Monteagudo, Rafael Castronuovo, Edgardo D. Barber, Ramon FCC Madrid 28050 Spain Univ Carlos III Madrid Elect Engn Dept Leganes 28911 Spain Univ Carlos III Madrid Syst Engn & Automat Leganes 28911 Spain

In this work, an innovative methodology for the strategic placement of electric vehicle (EV) charging stations is presented, considering both population density and proximity to the stations, in order to optimize accessibility. This approach synergistic leverages the advantages of genetic algorithms (GAs) and weighted K-means clustering, creating a phased process that circumvents the typical constraints presented by the two methods in developing efficient EV charging infrastructures. Initially, a GA is used to obtain a spectrum of potential locations, setting a preliminary distribution of charging stations. Then, a K-means clustering method is used to refine this distribution and obtain the most advantageous sites. The number of charging stations is modulated by variable alpha, which adjusts the influence of the GA and K-means in the final solution. The outcome is a more effective and realistic distribution of EV charging stations that can adapt to the actual patterns of urban population distribution, the economy of resources and EV demand. The proposed methodology is applied to an urban environment in two Spanish cities. The solution decreases between 60.60 and 95 % the number of the charging stations relative to those obtained by using k-mean and between 38.09 and 70 % those obtained using GAs, resulting in an economic and efficient grid of charging stations.

关键词： Charging stations Genetic algorithms Electric vehicle charging Resource management Clustering algorithms Dispersion Costs Buildings partitioning algorithms Investment weighted K-means clustering EV charging stations placement optimization

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MPDA: Multivariate Probability Distribution Autoencoder for Hyperspectral Anomaly Detection

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2024年 62卷

作者： Mu, Zhenhua Wang, Yihan Zhang, Yating Song, Chuanming Wang, Xianghai Liaoning Normal Univ Sch Geog Dalian 116029 Peoples R China Liaoning Normal Univ Sch Comp Sci & Artificial Intelligence Dalian 116029 Peoples R China Dalian Univ Sch Informat Engn Dalian 116622 Peoples R China

In recent years, the significant success of deep learning (DL) in computer vision has contributed to its continuous development in the field of hyperspectral image (HSI) anomaly detection (AD). However, in practical applications, HSI-AD based on DL faces many challenges due to the inability to effectively acquire training samples and predict the types of anomaly targets. This makes it a challenging task, especially for AD in complex scenes. In this article, we propose an unsupervised DL framework for HSI-AD based on the multivariate probability distribution autoencoder (MPDA). First, to explore the distribution characteristics of high-dimensional data, we use the probability density histogram to statistically distribute the frequencies of each interval adaptively, dividing the HSI and obtaining an AD-guided image through the designed grid structure. Second, we propose an unsupervised multilayer autoencoder network based on energy-weighted skip connections. By coupling the detection-guided image in the network, we achieve reverse-guided module reconstruction, weakening the feature representation of anomalous in the reconstructed information and enhancing the separability of targets. Finally, we model the reconstructed error images using the multivariate skewed t-distribution based on data distribution characteristics to obtain the final AD map. Through the comparative experiments with other innovative AD algorithms on authentic HSI datasets captured in five different scenarios, the proposed algorithm demonstrates strong generalization and detection capabilities. The source code of the MPDA will be public at https://***/muzhenhuam/MPDA/tree/master.

关键词： Image reconstruction Probability distribution Probability Feature extraction Detectors partitioning algorithms Nonhomogeneous media Histograms Gaussian distribution Anomaly detection Anomaly detection (AD) autoencoder hyperspectral image (HSI) probability density distribution skewed distribution unsupervised deep learning (DL)

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Parallelized Technology Mapping to General PLBs by Adaptive Circuit partitioning 20

Parallelized Technology Mapping to General PLBs by Adaptive ...

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20th International Conference on Field-Programmable Technology (ICFPT)

作者： Wang, Xiaoxi Yang, Moucheng Li, Zhen Wang, Lingli Fudan Univ State Key Lab ASIC & Syst Shanghai Peoples R China

ISBN: (纸本)9781665420105

Technology mapping from logic netlists to programmable logic blocks (PLB) plays an important role in FPGA EDA flow, especially for architecture exploration of PLBs. However, technology mapping becomes time-consuming due to the booming scale and complexity of IC designs as well as the growing complexity of PLB architectures. To speed up this process, a parallelized technology mapping approach based on adaptive circuit partitioning is proposed in this paper to perform fast multi-thread technology mapping. First, We choose the best of the three candidate partitioning strategies for the given netlist by circuit analysis to partition the original netlist into several independent sub-netlists. Secondly, these sub-netlists are mapped to the given PLB architecture simultaneously in their corresponding mapping threads. Finally, the complete mapped netlist is generated by merging the mapped sub-netlists. The proposed approach is implemented in ABC, independent of the detailed mapping algorithm. 13 large circuits from the Titan23 benchmark set are used as benchmarks to evaluate the proposed approach. Experimental results show that the proposed approach leads to an average of 5.76x speedup over the single-thread version (up to 8.21x individually) with no delay loss and less than 0.57% average area penalty.

关键词： Instruction sets Merging Decision making Benchmark testing Delays Complexity theory partitioning algorithms

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