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Exploring Hierarchical Patterns for Alert Aggregation in Supercomputers

Exploring Hierarchical Patterns for Alert Aggregation in Sup...

引用

International Symposium on Software Reliability Engineering (ISSRE)

作者： Yuan Yuan Tongqing Zhou Xiuhong Tan Yongqian Sun Yuqi Li Zhixing Li Zhiping Cai Tiejun Li National University of Defense Technology Changsha University of Science & Technology Nankai University National Supercomputer Center in Tianjin

ISBN: (数字)9798350353884

ISBN: (纸本)9798350353891

Alongside the high performance built on massive hardware, ever-larger computer systems bear tons of hardware alerts every day during reliability maintenance. Based on an exploratory study on a representative supercomputer system, this work first characterizes supercomputer alerts as an overload of continuous bursts for the operators. Yet, existing similarity-based aggregation solutions, tuned for in-band textual alerts, are myopic by finding dissimilar representatives instead of looking into the semantics in the supercomputer context. To fill the void of supercomputer alert aggregation, we propose the SuperAgg framework to extract the hierarchical patterns of real-world alerts and use them for online alert management. SuperAgg jointly integrates unsupervised state detection of time series and expert analysis to successfully discover 4 categories of sensor-tier alert patterns and exploits primary-and-secondary statistics between sensors for system-tier correlation patterns. With such extracted knowledge, SuperAgg then identifies the formulated patterns online and uses spatiotemporal combined strategies to reduce the alert influx. Evaluations on alerts generated from a production supercomputer show that SuperAgg provides over 98% aggregation rate and significantly higher aggregation accuracy (over 83.8% and 43.2% on different datasets) than 3 baselines. Production deployment further demonstrates its effectiveness from the perspective of system operators. The source code is available at: https://***/Txh-User/SuperAgg.

关键词： Correlation source coding Time series analysis Supercomputers Hardware Sensor systems Software reliability Spatiotemporal phenomena Sensors Unsupervised learning

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Variable-size vector entropy coding of speech and audio

Variable-size vector entropy coding of speech and audio

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Y. Shoham Bell Laboratories Lucent Technologies Inc. Murray Hill NJ USA

Many modern analog media coders employ some form of entropy coding (EC). Usually, a simple per-letter EC is used to keep the coder's complexity and price low. In some coders, individual symbols are grouped into small fixed-size vectors before EC is applied. We extend this approach to form variable-size vector EC (VSVEC) in which vector sizes may be from 1 to several hundreds. The method is, however, complexity-constrained in the sense that the vector size is always as large as allowed by a pre-set complexity limit. The idea is studied in the framework of a modified discrete cosine transform (MDCT) coder. It is shown experimentally, using diverse audio material, that a rate reduction of about 37% can be achieved. The method is, however, not specific to MDCT coding but can be incorporated in various speech, audio, image and video coders.

关键词： Entropy coding Speech coding Image coding Code standards Laboratories Video compression source coding Streaming media Huffman coding Arithmetic

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ICCCN 2008 Distinguished Invited Speakers

ICCCN 2008 Distinguished Invited Speakers

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International Conference on Computer Communications and Networks (ICCCN)

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Closer through commonality: Enhancing hypergraph contrastive learning with shared groups

Closer through commonality: Enhancing hypergraph contrastive...

引用

IEEE International Conference on Big Data

作者： Daeyoung Roh Donghee Han Daehee Kim Keejun Han Mun Yi Graduate School of Data Science KAIST Republic of Korea School of Computer Engineering Hansung University Republic of Korea Department of Industrial and Systems Engineering KAIST Republic of Korea

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

Hypergraphs provide a superior modeling frame-work for representing complex multidimensional relationships in the context of real-world interactions that often occur in groups, overcoming the limitations of traditional homogeneous graphs. However, there have been few studies on hypergraph-based contrastive learning, and existing graph-based contrastive learning methods have not been able to fully exploit the high-order correlation information in hypergraphs. Here, we propose a Hypergraph Fine-grained contrastive learning (HyFi) method designed to exploit the complex high-dimensional information inherent in hypergraphs. While avoiding traditional graph augmentation methods that corrupt the hypergraph topology, the proposed method provides a simple and efficient learning augmentation function by adding noise to node features. Furthermore, we expands beyond the traditional dichotomous relationship between positive and negative samples in contrastive learning by introducing a new relationship of weak positives. It demonstrates the importance of fine-graining positive samples in contrastive learning. Therefore, HyFi is able to produce high-quality embeddings, and outperforms both supervised and unsupervised baselines in average rank on node classification across 10 datasets. Our approach effectively exploits high-dimensional hypergraph information, shows significant improvement over existing graph-based contrastive learning methods, and is efficient in terms of training speed and GPU memory cost. The source code is available at https://***/Noverse0/***.

关键词： Training Costs Correlation source coding Noise Memory management Graphics processing units Contrastive learning Data models Topology

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DocRes: A Generalist Model Toward Unifying Document Image Restoration Tasks

DocRes: A Generalist Model Toward Unifying Document Image Re...

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Jiaxin Zhang Dezhi Peng Chongyu Liu Peirong Zhang Lianwen Jin South China University of Technology INTSIG-SCUT Joint Lab on Document Analysis and Recognition

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Document image restoration is a crucial aspect of Document AI systems, as the quality of document images significantly influences the overall performance. Prevailing methods address distinct restoration tasks independently, leading to intricate systems and the incapability to harness the potential synergies of multi-task learning. To overcome this challenge, we propose DocRes, a generalist model that unifies five document image restoration tasks including dewarping, deshadowing, appearance enhancement, deblurring, and binarization. To instruct DocRes to perform various restoration tasks, we propose a novel visual prompt approach called Dynamic Task-Specific Prompt (DTSPrompt). The DTSPrompt for different tasks comprises distinct prior features, which are additional characteristics extracted from the input image. Beyond its role as a cue for task-specific execution, DTSPrompt can also serve as supplementary information to enhance the model's performance. Moreover, DTSPrompt is more flexible than prior visual prompt approaches as it can be seamlessly applied and adapted to inputs with high and variable resolutions. Experimental results demonstrate that DocRes achieves competitive or superior performance compared to existing state-of-the-art task-specific models. This under-scores the potential of DocRes across a broader spectrum of document image restoration tasks. The source code is publicly available at https://***/ZZZHANGjx/DocRes.

关键词： Adaptation models Visualization Computer vision Image resolution Computational modeling source coding Feature extraction

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Is it a Bug? Understanding Physical Unit Mismatches in Robot Software

Is it a Bug? Understanding Physical Unit Mismatches in Robot...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Paulo Canelas Trenton Tabor John-Paul Ore Alcides Fonseca Claire Le Goues Christopher S. Timperley School of Computer Science Carnegie Mellon University LASIGE Faculdade de Ciências da Universidade de Lisboa North Carolina State University

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Robot software is abundant with variables that represent real-world physical units (e.g., meters, seconds). Operations over different units (e.g., adding meters and seconds) may be incorrect and can lead to dangerous system misbehaviors; manually detecting such mistakes is challenging. Current software analysis techniques identify such mismatches using dimensional analysis rules and ROS-specific assumptions to analyze the source code. However, these are ignorant of the fact that physical unit mismatches in robotics code are often intentional (e.g., when operating a differential drive robot), resulting in false positive bug reports that can impede robotics developer trust and productivity. In this work, we study how developers introduce physical unit mismatches by manually inspecting 180 errors detected by the software analysis technique, Phys. We identify three types of physical unit mismatches and present a taxonomy of eight high-level categories of how these errors manifest. We find that developers often make unforced and paradigmatic physical unit mismatches through differential drives, small angle approximations, and controls. We draw insights on current development to inform future research to better detect, categorize, and address meaningful physical unit mismatches.

关键词： Meters Productivity Codes source coding Computer bugs Taxonomy Programming

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Use of pre-interleaving for video streaming over wireless access networks

Use of pre-interleaving for video streaming over wireless ac...

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IEEE International Conference on Image Processing

作者： Jianfei Cai Chang Wen Chen Department of Electrical Engineering University of Missouri Columbia Columbia MO USA Sarnoff Corporation Princeton NJ USA

We present an FEC-based end-to-end error control scheme for video streaming over wireless access networks, considering both bit errors and packet-loss. We propose a novel robust video streaming system in which an interleaving is applied to the compressed bitstream before channel coding. The application of such pre-interleaving is able to significantly improve the error-combating performance of video streaming because the adoption of this pre-interleaving can simultaneously satisfy different requirements arising from both channel coding and source coding. Experimental results demonstrate the improved performance of the proposed pre-interleaving scheme, especially in the case of highly bursty and regular channel errors.

关键词： Streaming media Wireless networks Channel coding Interleaved codes Video compression Error correction source coding Forward error correction Robustness Network servers

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Research and Implement of DRM Baseband Encoder and Modulator Based on Embedded System

Research and Implement of DRM Baseband Encoder and Modulator...

引用

International Conference on Networks Security, Wireless Communications and Trusted Computing, NSWCTC

作者： Nanhao Zhu Zhengxiang Li Qinbin Lu Engineering Research Center of Digital Audio and Video Ministry of Education Communication University of China Beijing China

ISBN: (纸本)9781424465972;9780769540115

DRM technology has been widely used in modern Digital AM Broadcasting. The design of DRM base band encoder and modulator based on embedded system is presented in order to realize less cost, smaller power loss and more portability for the DRM transmission system. The function of software modules are described in details combined with DRM standard, and relevant solutions are also presented for reference. Finally, the application of this base band encoder and modulator is analyzed.

关键词： Baseband Embedded system Channel coding Signal mapping Modulation coding Digital audio broadcasting Signal processing source coding Radio broadcasting Digital signal processing

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Third-order coding rate for universal compression of Markov sources

Third-order coding rate for universal compression of Markov ...

引用

IEEE International Symposium on Information Theory

作者： Nematollah Iri Oliver Kosut Arizona State University Tempe AZ US

ISBN: (纸本)9781467377058

We consider the universal source coding problem for first-order stationary, irreducible and aperiodic Markov sources for short blocklengths. Achievability is derived based on the previously introduced algorithm for universal compression of memoryless sources in the finite blocklengths, the Type Size Code, which encodes strings based on type class size. We derive the third-order asymptotic coding rate of the Type Size code for this model class. We also present a converse on the third-order coding rate for the general class of fixed-to-variable codes and show the optimality of Type Size codes for such Markov sources.

关键词： Markov processes source coding Entropy Reactive power Upper bound

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Soft decoding of multiple descriptions

Soft decoding of multiple descriptions

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： T. Guionnet C. Guillemot E. Fabre INRIA IRISA Rennes France

A multiple description scalar quantization (MDSQ) based coding system can be regarded as a source coder (quantizer) followed by a channel coder, i.e. the combination of index and codeword assignment. The redundancy, or the correlation between the descriptions, is controlled by the number of diagonals covered by the index assignment. In this paper, we analyse dependencies between the variables involved in the MDSQ coding chain and design an estimation strategy making use of part of the global model of dependencies at each time. Inference of the hidden states of the connected models is done by applying belief propagation principles on the resulting Bayesian network. We try to evidence the most appropriate form of redundancy one should introduce in the context of variable length code compressed streams in order to fight against de-synchronizations when impaired by channel noise.

关键词： Decoding Bayesian methods Redundancy Delay Stochastic processes Quantization Belief propagation Context source coding Communication systems

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