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检索条件"主题词=Source coding"

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Investigating Resilience of Loops in HPC Programs: A Semantic Approach with LLMs

Investigating Resilience of Loops in HPC Programs: A Semanti...

引用

IEEE Conference on High Performance Extreme Computing (HPEC)

作者： Hailong Jiang Jianfeng Zhu Bo Fang Chao Chen Qiang Guan Department of Computer Science Kent State University Kent OH USA Pacific Northwest National Laboratory Richland WA USA Intel Corporation Santa Clara CA USA

ISBN: (数字)9798350387131

ISBN: (纸本)9798350387148

Transient hardware faults, resulting from particle strikes, are significant concerns in HighPerformance Computing (HPC) systems. As these systems scale, the likelihood of soft errors rises. Traditional methods like Error-Correcting Codes (ECCs) and checkpointing address many of these errors, but some evade detection, leading to silent data corruptions (SDCs). This paper evaluates the resilience of HPC program loops, which are crucial for performance and error handling, by analyzing their computational patterns, known as the thirteen dwarfs of parallelism. We employ fault injection techniques to quantify SDC rates and utilize Large Language Models (LLMs) with prompt engineering to identify the loop semantics of the dwarfs in real source code. Our contributions include defining and summarizing loop patterns for each dwarf, quantifying their resilience, and leveraging LLMs for precise identification of these patterns. These insights enhance the understanding of loop resilience, aiding in the development of more resilient HPC applications.

关键词： Large language models source coding High performance computing Semantics Parallel processing Hardware Prompt engineering Transient analysis Optimization Resilience

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Short-block variable-rate trellis quantization

Short-block variable-rate trellis quantization

引用

Data Compression Conference (DCC)

作者： T. Eriksson M. Novak J.B. Anderson Department of Information Technology Lund University Lund Sweden

We present two methods for variable-rate trellis quantization. Both methods utilize trellis codes based on linear congruential (LC) recursions. LC code trellises have good pseudo-random properties and are easily adapted to serve reconstruction alphabets of different sizes. The first method finds an entropy-constrained code only by optimizing over a scale factor. The scale factor modifies an initial reproducer alphabet in order to skew the associated set of codeword lengths. Using a Lagrangian formulation and the maximum a posteriori (MAP) heuristic, we also develop an entropy-constrained trellis quantizer suitable for short blocks of data. Here the tailbiting BCJR algorithm is used to find the MAP path in the trellis. Simulation results for the Gaussian and Laplacian distributions show that the proposed method is competitive with the best in the literature.

关键词： Image reconstruction Convolutional codes source coding Vector quantization Speech coding Data compression Shift registers Entropy Information technology Optimization methods

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Real-Time and Resource-Efficient Multi-Scale Adaptive Robotics Vision for Underwater Object Detection and Domain Generalization

Real-Time and Resource-Efficient Multi-Scale Adaptive Roboti...

引用

IEEE International Conference on Image Processing

作者： Lyes Saad Saoud Zhenwei Niu Lakmal Seneviratne Irfan Hussain Department of Mechanical Engineering Khalifa University Abu Dhabi United Arab Emirates Khalifa University Center for Autonomous and Robotic Systems Khalifa University Abu Dhabi United Arab Emirates Abu Dhabi

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

Underwater robotic vision encounters numerous challenges posed by complex environments and varying lighting conditions. Meeting these challenges requires solutions that not only deliver accuracy but also demonstrate adaptability. In this paper, we present MARS (Multi-Scale Adaptive Robotics Vision), a pioneering approach to underwater object detection that prioritizes real-time performance and resource efficiency-essential attributes for underwater robotic systems. Leveraging a well-established object detection architecture, MARS integrates Domain-Adaptive Multi-Scale Attention (DAMSA), enhancing both detection accuracy and adaptability to diverse underwater domains. During training, DAMSA employs domain class-based attention, allowing the model to learn and prioritize features specific to different underwater environments. Extensive evaluation across diverse underwater datasets underscores the effectiveness of MARS. On the original dataset, MARS achieves an impressive mean Average Precision (mAP) of58.57%, demonstrating its proficiency in detecting critical underwater objects such as echinus, starfish, holothurian, scallop, and waterweeds. This capability positions MARS as a promising solution for applications in marine robotics, marine biology research, and environmental monitoring. Moreover, MARS exhibits exceptional resilience to domain shifts. When evaluated on an augmented dataset incorporating various enhancements, MARS delivers a commendable mAP of 36.16%, showcasing its robustness and adaptability in recognizing objects across diverse underwater conditions. The source code for MARS is publicly available on GitHub at https://***/LyesSaadSaoud/MARS-Object-Detection/.

关键词： YOLO Training Technological innovation Accuracy source coding Robustness Real-time systems

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Identification via compressed data

Identification via compressed data

引用

IEEE International Symposium on Information Theory

作者： R. Ahlswede En-hui Yang Zhen Zhang Fakultat fur Math. Bielefeld Univ. Germany Department of Mathematics Naukai University Tianjin China Department of EE-Systems University of Southern California Los Angeles CA USA

The combined problem of source coding and identification is considered. To put our problem in perspective, we first review the traditional problem in source coding theory.

关键词： Decoding source coding Error probability Binary sequences Distortion measurement Rate distortion theory Rate-distortion Random variables Length measurement

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Transmission of multimode and variable-rate encoded speech samples on packet switched radio networks handling wide band voice information

Transmission of multimode and variable-rate encoded speech s...

引用

IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： F. Babich E. Valentinuzzi F. Vatta DEEI-Università di Trieste Trieste Italy

Packet switching allows one to exploit the intrinsic variable-rate behaviour of real-time information, such as voice and video. Indeed, packet switching permits one to handle in a more flexible way the information bits and to obtain, therefore, a significant increment in system capacity. A relative measure of the capacity increment we obtain over circuit switched systems is the multiplexing gain. This paper presents preliminary results of the multiplexing gain we can achieve when we transmit multi-mode and variable-rate speech on a slotted and framed radio channel. For our evaluation we use an embedded, variable bit-rate speech coding scheme, namely the Mobile Audio Visual Terminal (MAVT) coder, candidate to the new standard MPEG-4. The peculiar characteristics of this coding scheme can be exploited for obtaining a significant multiplexing gain. Moreover, at high loads, a smooth and graceful degradation of speech quality can be obtained by exploiting the embedded property of the encoder. In fact, being that the information bits are classified by priority, we observe a graceful quality reduction during network congestion, if the transmission algorithm is designed to discard first the bits with the minimum impact on the output quality.

关键词： Packet switching Radio networks Speech coding Wideband MPEG 4 Standard Degradation Quality of service Entropy source coding Bandwidth

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MUT: Human-in-the-Loop Unit Test Migration

MUT: Human-in-the-Loop Unit Test Migration

引用

International Conference on Software Engineering (ICSE)

作者： Yi Gao Xing Hu Tongtong Xu Xin Xia David Lo Xiaohu Yang The State Key Laboratory of Blockchain and Data Security Zhejiang University Hangzhou China Huawei Hangzhou China School of Computing and Information Systems Singapore Management University Hangzhou China

ISBN: (数字)9798400702174

ISBN: (纸本)9798350382143

Test migration, which enables the reuse of test cases crafted with knowledge and creativity by testers across various platforms and programming languages, has exhibited effectiveness in mobile app testing. However, unit test migration at the source code level has not garnered adequate attention and exploration. In this paper, we propose a novel cross-language and cross-platform test migration methodology, named MUT, which consists of four modules: code mapping, test case filtering, test case translation, and test case adaptation. MUT initially calculates code mappings to establish associations between source and target projects, and identifies suitable unit tests for migration from the source project. Then, MUT's code translation component generates a syntax tree by parsing the code to be migrated and progressively converts each node in the tree, ultima tely generating the target tests, which are compiled and executed in the target project. Moreover, we develop a web tool to assist developers in test migration. The effectiveness of our approach has been validated on five prevalent functional domain projects within the open-source community. We migrate a total of 550 unit tests and submitted pull requests to augment test code in the target projects on GitHub. By the time of this paper submission, 253 of these tests have already been merged into the projects (including 197 unit tests in the Luliyucoordinate-LeetCode project and 56 unit tests in the Rangerlee-HtmlParser project). Through running these tests, we identify 5 bugs, and 2 functional defects, and submitted corresponding issues to the project. The evaluation substantiates that MUT's test migration is both viable and beneficial across programming languages and different projects.

关键词： Computer languages Codes Filtering source coding Syntactics Human in the loop Mobile applications

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Predicting Code Smells: A Comparative Study of Machine Learning Classifiers for God Class and Data Class

Predicting Code Smells: A Comparative Study of Machine Learn...

引用

International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES)

作者： Kiran Kumar Sahu Rasmita Panigrahi Vishal Kumar Swain Neelamadhab Padhy Department of CSE GIET UNIVERSITY Gunupur Odisha India

ISBN: (数字)9798331506452

ISBN: (纸本)9798331506469

Code Smells often indicate underlying problems that can degrade various aspects of software quality. It refers to the area in the source code which needs improvement. Software with Code Smell may lead to high maintenance costs. Code Smells are not errors or bugs; rather addressing them can enhance the code quality. Code with Smells may lead to software defects in the future. Objective- This paper aims to predict specific Code Smells, namely God Class and Data Class, present in the source code and compare the performances of various machine learning models. Methodology- We compared the performance of four traditional machine learning classifiers (Decision Tree, Naive Bayes, Logistic Regression, and K-Nearest Neighbor) with five ensemble classifiers (Random Forest, Bagging with Decision Tree, Gradient Boosting, AdaBoost, and XGBoost). Result & Conclusion- Our analysis indicates that the existence of God Class is more prevalent than Data Class in the examined code, with accuracy as the primary performance metric. Our experimental observation reveals that XGBoost outperforms predicting the Code Smells in terms of all performance measures i.e. 100%.

关键词： Codes Power measurement source coding Software quality Signal processing Predictive models Decision trees Software measurement Random forests Software engineering

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Hierarchical Spatio-temporal Decoupling for Text-to- Video Generation

Hierarchical Spatio-temporal Decoupling for Text-to- Video G...

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Zhiwu Qing Shiwei Zhang Jiayu Wang Xiang Wang Yujie Wei Yingya Zhang Changxin Gao Nong Sang Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Alibaba Group Fudan University

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Despite diffusion models having shown powerful abilities to generate photorealistic images, generating videos that are realistic and diverse still remains in its infancy. One of the key reasons is that current methods intertwine spatial content and temporal dynamics together, leading to a notably increased complexity of text-to-video generation (T2V). In this work, we propose HiGen, a diffusion model-based method that improves performance by decoupling the spatial and temporal factors of videos from two perspectives, i.e., structure level and content level. At the structure level, we decompose the T2V task into two steps, including spatial reasoning and temporal reasoning, using a unified denoiser. Specifically, we generate spatially coherent priors using text during spatial reasoning and then generate temporally coherent motions from these priors during temporal reasoning. At the content level, we extract two subtle cues from the content of the input video that can express motion and appearance changes, respectively. These two cues then guide the model's training for generating videos, enabling flexible content variations and enhancing temporal stability. Through the decoupled paradigm, HiGen can effectively reduce the complexity of this task and generate realistic videos with semantics accuracy and motion stability. Extensive experiments demonstrate the superior performance of HiGen over the state-of-the-art T2V methods. We have released our source code and models.

关键词： Training source coding Semantics Spatial coherence Cognition Stability analysis Complexity theory

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A scalable communication architecture for the sensor broadcast problem

A scalable communication architecture for the sensor broadca...

引用

IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

作者： Y.-W. Hong A. Scaglione School of Electrical and Computer Engineering Cornell University USA

In our previous work, a time efficient data retrieval method was proposed for distributed data sources using the generalized group testing approach. In this work, we provide the physical-layer transmission and reception strategy that supports the implementation of the group testing method. The integration of the two protocols leads to a modified strategy that incorporates the errors occurring within the feedback channel. We propose a signal modulation scheme combined with the source and channel coding that was proposed using the concept of group testing. The numerical simulations show an improved performance with the proposed cooperative broadcasting scheme. Our methodology does not separate channel and source coding and can be implemented with a two layer architecture with low complexity.

关键词： Broadcasting Testing Physical layer Feedback source coding Data compression Decoding Computer architecture Distributed computing Data engineering

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Bounding the Rate Region of the Two-Terminal Vector Gaussian CEO Problem

Bounding the Rate Region of the Two-Terminal Vector Gaussian...

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Data Compression Conference (DCC)

作者： Guoqiang Zhang W. Bastiaan Kleijn ACCESS Linnaeus Center Electrical Engineering KTH-Royal Institute of Technology Sweden

The rate region of the two-terminal vector Gaussian CEO problem is studied. A lower bound on the rate region is derived. It is obtained by lower-bounding a weighted sum rate for each supporting hyper plane of the rate... 详细信息

关键词： Noise measurement Covariance matrix Closed-form solution source coding Electrical engineering Optimization

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