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Granger causal representation learning for groups of time series

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science China(Information sciences) 2024年第5期67卷 56-68页

作者： Ruichu CAI Yunjin WU Xiaokai HUANG Wei CHEN Tom Z.J.FU Zhifeng HAO School of computer science Guangdong University of Technology Peng Cheng laboratory College of science Shantou University

Discovering causality from multivariate time series is an important but challenging *** existing methods focus on estimating the Granger causal structures among multivariate time series,while ignoring the prior knowledge of these time series, e.g., the group of the time series. Focusing on discovering the Granger causal structures among groups of time series, we propose a Granger causal representation learning method to solve this problem. First, we use the multiset canonical correlation analysis method to learn the Granger causal representation of each group of time series. Then, we model the Granger causal relationships among the learned Granger causal representations using a recurrent neural network with temporal information. Finally, we formulate the above two stages into one unified optimization problem, which is efficiently solved using the augmented Lagrangian method. We conduct extensive experiments on synthetic and real-world datasets to validate the correctness and effectiveness of the proposed method.

关键词： Granger causal discovery Granger causal representation learning time series data recurrent neural network multiset canonical correlation analysis

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Formal Verification of Data Modifications in Cloud Block Storage Based on Separation Logic

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Chinese Journal of Electronics 2024年第1期33卷 112-127页

作者： Bowen ZHANG Zhao JIN Hanpin WANG Yongzhi CAO Key laboratory of High Confidence Software Technologies (MOE) School of Computer Science Peking University School of computer and Artificial Intelligence Zhengzhou University School of computer science and Cyber Engineering Guangzhou University

Cloud storage is now widely used, but its reliability has always been a major concern. Cloud block storage(CBS) is a famous type of cloud storage. It has the closest architecture to the underlying storage and can provide interfaces for other types. Data modifications in CBS have potential risks such as null reference or data *** verification of these operations can improve the reliability of CBS to some extent. Although separation logic is a mainstream approach to verifying program correctness, the complex architecture of CBS creates some challenges for verifications. This paper develops a proof system based on separation logic for verifying the CBS data modifications. The proof system can represent the CBS architecture, describe the properties of the CBS system state, and specify the behavior of CBS data modifications. Using the interactive verification approach from Coq, the proof system is implemented as a verification tool. With this tool, the paper builds machine-checked proofs for the functional correctness of CBS data modifications. This work can thus analyze the reliability of cloud storage from a formal perspective.

关键词： Cloud computing Behavioral sciences Reliability Formal verification

Retrieval-and-alignment based large-scale indoor point cloud semantic segmentation

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science China(Information sciences) 2024年第4期67卷 164-180页

作者： Zongyi XU Xiaoshui HUANG Bo YUAN Yangfu WANG Qianni ZHANG Weisheng LI Xinbo GAO School of computer science and Technology Chongqing University of Posts and Telecommunications Shanghai Artificial Intelligence laboratory School of Electronic Engineering and computer science Queen Mary University of London

Current methods for point cloud semantic segmentation depend on the extraction of descriptive features. However, unlike images, point clouds are irregular and often lack texture information, making it demanding to extract discriminative features. In addition, noise, outliers, and uneven point distribution are commonly present in point clouds, which further complicates the segmentation task. To address these problems, a novel architecture is proposed for direct and accurate large-scale point cloud segmentation based on point cloud retrieval and alignment. The proposed approach involves using a feature-based point cloud retrieval method for searching for reference point clouds with annotations from a dataset. In the following segmentation stage, an overlap-based point cloud registration method has been developed to align the target and reference point clouds. For accurate and robust alignment, an overlap region estimation module is trained to locate the optimal overlap region between two pieces of point clouds in a coarse-to-fine manner. In the detected overlap region, the global and local features of the points are extracted and combined for featuremetric registration to obtain accurate transformation parameters between the target and reference point clouds. After alignment, the annotated segmentation of the reference is transferred to the target point clouds to obtain accurate segmentation results. Extensive experiments are conducted to show that the developed method outperforms the state-of-the-art approaches in terms of both accuracy and robustness against noise and outliers.

关键词： point cloud semantic segmentation large-scale indoor point clouds point cloud alignment overlap estimation label transfer

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Towards kernelizing the classifier for hyperbolic data

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Frontiers of computer science 2024年第1期18卷 17-31页

作者： Meimei YANG Qiao LIU Xinkai SUN Na SHI Hui XUE School of computer science and Engineering Southeast UniversityNanjing 210096China MOE Key laboratory of computer science and Information Integration(Southeast University) Nanjing 210096China

Data hierarchy,as a hidden property of data structure,exists in a wide range of machine learning applications.A common practice to classify such hierarchical data is first to encode the data in the Euclidean space,and then train a Euclidean ***,such a paradigm leads to a performance drop due to distortion of data embedding in the Euclidean *** relieve this issue,hyperbolic geometry is investigated as an alternative space to encode the hierarchical data for its higher ability to capture the hierarchical *** methods cannot explore the full potential of the hyperbolic geometry,in the sense that such methods define the hyperbolic operations in the tangent plane,causing the distortion of data *** this paper,we develop two novel kernel formulations in the hyperbolic space,with one being positive definite(PD)and another one being indefinite,to solve the classification tasks in hyperbolic *** PD one is defined via mapping the hyperbolic data to the Drury-Arveson(DA)space,which is a special reproducing kernel Hilbert space(RKHS).To further increase the discrimination of the classifier,an indefinite kernel is further defined in the Krein ***,we design a 2-layer nested indefinite kernel which first maps hyperbolic data into the DA spaces,followed by a mapping from the DA spaces to the Krein *** experiments on real-world datasets demonstrate the superiority ofthe proposed kernels.

关键词： data hierarchy hyperbolic cgeometry drury-arveson space krein space

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Journal of computer science & Technology 2024年第1期39卷 63-81页

作者：陈章玉华宇左鹏飞孙园园郭云程 Wuhan National laboratory for Optoelectronics School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China

Image bitmaps,i.e.,data containing pixels and visual perception,have been widely used in emerging applica-tions for pixel operations while consuming lots of memory space and *** with legacy DRAM(dynamic ran-dom access memory),non-volatile memories(NVMs)are suitable for bitmap storage due to the salient features of high density and intrinsic ***,writing NVMs suffers from higher energy consumption and latency compared with read *** precise or approximate compression schemes in NVM controllers show limited performance for bitmaps due to the irregular data patterns and variance in *** observe the pixel-level similarity when writing bitmaps due to the analogous contents in adjacent *** exploiting the pixel-level similarity,we propose SimCom,an approximate similarity-aware compression scheme in the NVM module controller,to efficiently compress data for each write access *** idea behind SimCom is to compress continuous similar words into the pairs of base words with *** storage costs for small runs are further mitigated by reusing the least significant bits of base *** adaptively selects an appropriate compression mode for various bitmap formats,thus achieving an efficient trade-off be-tween quality and memory *** implement SimCom on GEM5/zsim with NVMain and evaluate the perfor-mance with real-world image/video *** results demonstrate the efficacy and efficiency of our SimCom with an efficient quality-performance trade-off.

关键词： approximate computing data compression memory architecture non-volatile memory

Building a domain-specific compiler for emerging processors with a reusable approach

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science China(Information sciences) 2024年第1期67卷 20-38页

作者： Mingzhen LI Yi LIU Bangduo CHEN Hailong YANG Zhongzhi LUAN Depei QIAN State Key laboratory of Software Development Environment School of computer science and Engineering Beihang University

High-performance computing and deep learning domains have been motivating the design of domain-specific *** these processors can provide promising computation capability,they are notorious for exotic programming *** improve programming productivity and fully exploit the performance potential of these processors,domain-specific compilers(DSCs) have been ***,building DSCs for emerging processors requires tremendous engineering efforts because the commonly used compilation stack is difficult to be *** to the advent of multilevel intermediate representation(MLIR),DSC developers can leverage reusable infrastructure to extend their customized functionalities without rebuilding the entire compilation *** this paper,we further demonstrate the effectiveness of MLIR by extending its reusable infrastructure to embrace a heterogeneous many-core processor(Sunway processor).In particular,we design a new Sunway dialect and corresponding backend for the Sunway processor,fully exploiting its architectural advantage and hiding its programming *** show the ease of building a DSC,we leverage the Sunway dialect and existing MLIR dialects to build a stencil compiler for the Sunway *** experimental results show that our stencil compiler,built with a reusable approach,can even perform better than state-of-the-art stencil compilers.

关键词： domain-specific compiler emerging processor reusable dialect performance optimization MLIR

Minimal Context-Switching Data Race Detection with Dataflow Tracking

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Journal of computer science & Technology 2024年第1期39卷 211-226页

作者：郑龙李洋辛杰刘海峰郑然廖小飞金海 National Engineering Research Center for Big Data Technology and System School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Services Computing Technology and System laboratory School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Cluster and Grid Computing laboratory School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China

Data race is one of the most important concurrent anomalies in multi-threaded *** con-straint-based techniques are leveraged into race detection,which is able to find all the races that can be found by any oth-er sound race ***,this constraint-based approach has serious limitations on helping programmers analyze and understand data ***,it may report a large number of false positives due to the unrecognized dataflow propa-gation of the ***,it recommends a wide range of thread context switches to schedule the reported race(in-cluding the false one)whenever this race is exposed during the constraint-solving *** ad hoc recommendation imposes too many context switches,which complicates the data race *** address these two limitations in the state-of-the-art constraint-based race detection,this paper proposes DFTracker,an improved constraint-based race detec-tor to recommend each data race with minimal thread context ***,we reduce the false positives by ana-lyzing and tracking the dataflow in the *** this means,DFTracker thus reduces the unnecessary analysis of false race *** further propose a novel algorithm to recommend an effective race schedule with minimal thread con-text switches for each data *** experimental results on the real applications demonstrate that 1)without removing any true data race,DFTracker effectively prunes false positives by 68%in comparison with the state-of-the-art constraint-based race detector;2)DFTracker recommends as low as 2.6-8.3(4.7 on average)thread context switches per data race in the real world,which is 81.6%fewer context switches per data race than the state-of-the-art constraint based race ***,DFTracker can be used as an effective tool to understand the data race for programmers.

关键词： data race satisfiability modulo theory multi-threaded program dynamic detection

When debugging encounters artificial intelligence: state of the art and open challenges

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science China(Information sciences) 2024年第4期67卷 42-84页

作者： Yi SONG Xiaoyuan XIE Baowen XU School of computer science Wuhan University State Key laboratory of Novel Software Technology Nanjing University

Both software debugging and artificial intelligence techniques are hot topics in the current field of software engineering. Debugging techniques, which comprise fault localization and program repair, are an important part of the software development lifecycle for ensuring the quality of software systems. As the scale and complexity of software systems grow, developers intend to improve the effectiveness and efficiency of software debugging via artificial intelligence(artificial intelligence for software debugging, AI4SD). On the other hand, many artificial intelligence models are being integrated into safety-critical areas such as autonomous driving, image recognition, and audio processing, where software debugging is highly necessary and urgent(software debugging for artificial intelligence, SD4AI). An AI-enhanced debugging technique could assist in debugging AI systems more effectively, and a more robust and reliable AI approach could further guarantee and support debugging techniques. Therefore, it is important to take AI4SD and SD4AI into consideration comprehensively. In this paper, we want to show readers the path, the trend, and the potential that these two directions interact with each other. We select and review a total of 165 papers in AI4SD and SD4AI for answering three research questions, and further analyze opportunities and challenges as well as suggest future directions of this cross-cutting area.

关键词： software debugging fault localization program repair artificial intelligence machine learning

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For Mega-Constellations: Edge Computing and Safety Management Based on Blockchain Technology

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China Communications 2024年第2期21卷 59-73页

作者： Zhen Zhang Bing Guo Chengjie Li College of computer science Sichuan UniversityChengdu 610064China The Key laboratory for computer Systems of State Ethnic Affairs Commission School of Computer Science and TechnologySouthwest Minzu UniversityChengdu 610225China National Key laboratory of science and Technology on Communications University of Electronic Science and Technology of ChinaChengdu 611731China

In mega-constellation Communication Systems, efficient routing algorithms and data transmission technologies are employed to ensure fast and reliable data transfer. However, the limited computational resources of satellites necessitate the use of edge computing to enhance secure *** edge computing reduces the burden on cloud computing, it introduces security and reliability challenges in open satellite communication channels. To address these challenges, we propose a blockchain architecture specifically designed for edge computing in mega-constellation communication systems. This architecture narrows down the consensus scope of the blockchain to meet the requirements of edge computing while ensuring comprehensive log storage across the network. Additionally, we introduce a reputation management mechanism for nodes within the blockchain, evaluating their trustworthiness, workload, and efficiency. Nodes with higher reputation scores are selected to participate in tasks and are appropriately incentivized. Simulation results demonstrate that our approach achieves a task result reliability of 95% while improving computational speed.

关键词： blockchain consensus mechanism edge computing mega-constellation reputation management

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