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3rd International Conference on parallel Architectures and Languages Europe, PARLE 1991

作者： Das, Sajal K. Horng, Wen-Bing Center for Research in Parallel and Distributed Computing Department of Computer Science University of North Texas DentonTX76203-3886 United States

ISBN: (纸本)9783540541516

We design a cost-optimal algorithm for managing a parallel heap on an exclusive-read and exclusive-write (EREW), parallel random access machine (PRAM) model. This is an improvement in space and time over the one recently proposed by Deo and Prasad [4]. Our approach efficiently employs p processors in the range 1 ≤ p ≤ n, where n is the maximum number of items in a parallel heap. It is assumed that a delete-think-insert cycle is repeatedly performed, and each processor requires an arbitrary but the same amount of time (called the think time) for processing an item which in turn generates at most α (a constant) new items. The time required for deleting p items of the highest priority from the parallel heap is O(l), while that for inserting at most αp new items is 0(logn). With or without incorporating the think time, the speedup of our algorithm is proved to be linear, i.e. 0(p). Using a global, working data structure for each level of the heap, it is shown that the additional memory space required for our parallel heap is much less than that for the existing one [4]. Furthermore, the proposed algorithm retains the strict priority ordering of a sequential heap. © Springer-Verlag Berlin Heidelberg 1991.

关键词： Data structures

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A mathematical model for empowerment of Beowulf clusters for exascale computing

A mathematical model for empowerment of Beowulf clusters for...

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2013 11th International Conference on High Performance computing and Simulation, HPCS 2013

作者： Mirtaheri, Seyedeh Leili Khaneghah, Ehsan Mousavi Grandinetti, Lucio Sharifi, Mohsen Center of High Performance Computing for Parallel and Distributed Processing University of Calabria Rende Italy School of Computer Engineering Iran University of Science and Technology Tehran Iran

ISBN: (纸本)9781479908363

High-performance computing (HPC) clusters are currently faced with two major challenges - namely, the dynamic nature of new generation of applications and the heterogeneity of platforms - if they are going to be useful for exascale computing. Processes running these applications may well demand unpredictable requirements and changes to system configuration and capabilities at runtime, thereby requiring fast system response without sacrificing the transparency and integrity of the reconfigured empowered system that is running on a heterogeneous platform. While a challenge in and of itself, platform heterogeneity is both useful and instrumental in the handling of unpredictable requests. The realization of such a dynamically reconfigurable and heterogeneous HPC cluster system for exascale computing requires a model to guide running processes to determine if they need empowerment of the current cluster, and if yes, by how much. To show the feasibility of empowerment of traditional HPC clusters for exascale computing, we have selected Beowulf as a noble candidate cluster and present a mathematical model for the empowerment of Beowulf clusters for exascale computing (EBEC). We have developed the model in line with Beowulf's cluster approach and by using vector space algebra. In contrast to traditional hardware-oriented approaches to improvise the performance of clusters, we use a software approach to the development of the proposed model by emphasizing processes, which act as the creators of the cluster and thus should decide on system (re)configuration, as the principal building blocks of the system. We have also adopted a new approach to heterogeneity by considering heterogeneity at different levels including hardware, system software, application software, and system functionality. In addition to support for heterogeneity and dynamic reconfiguration, the proposed model includes support for scalability that is crucial to exascale computing too. © 2013 IEEE.

关键词： Vector spaces

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Cost-optimal parallel algorithms for finitely inductive sequences 26

Cost-optimal parallel algorithms for finitely inductive sequ...

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26th Hawaii International Conference on System sciences, HICSS 1993

作者： Das, S.K. Fisher, P.S. Zhang, H. Center for Research in Parallel and Distributed Computing Department of Computer Science University of North Texas DentonTX76203-3886 United States

ISBN: (纸本)0818632305

Finitely inductive (FI) sequences are a class of sequences, finite or infinite, which are amenable to a certain mathematical representation which has direct significance to pattern recognition and string matching. Pattern recognition using the FI technique first transforms known patterns into function table(s) by factoring, and then uses the function iable(s) to match an input pattern by following. Factoring is done off line and only once for each pattern. The sequential time for matching two sequences depends only upon the length of the input sequence. In this paper, we propose cost-optimal (i.e., efficient) parallel algorithms for FI sequence processing. These algorithms include parallel factoring and following by bucket packing and by hashing on an exclusive-read and exclusive-write (EREW), parallel random access machine (PRAM) model. © 1993 IEEE.

关键词： Pattern recognition

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Evolving agent-based simulations in the clouds

Evolving agent-based simulations in the clouds

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3rd International Workshop on Advanced Computational Intelligence, IWACI 2010

作者： Decraene, James Cheng, Yong Yong Hean Low, Malcolm Yoke Zhou, Suiping Cai, Wentong Choo, Chwee Seng Parallel and Distributed Computing Center School of Computer Engineering Nanyang Technological University Singapore Singapore DSO National Laboratories 20 Science Park Drive Singapore Singapore

ISBN: (纸本)9781424463343

Evolving agent-based simulations enables one to automate the difficult iterative process of modeling complex adaptive systems to exhibit pre-specified/desired behaviors. Nevertheless this emerging technology, combining research advances in agent-based modeling/simulation and evolutionary computation, requires significant computing resources (i.e., high performance computing facilities) to evaluate simulation models across a large search space. Moreover, such experiments are typically conducted in an infrequent fashion and may occur when the computing facilities are not fully available. The user may thus be confronted with a computing budget limiting the use of these "evolvable simulation" techniques. We propose the use of the cloud computing paradigm to address these budget and flexibility issues. To assist this research, we utilize a modular evolutionary framework coined CASE (for complex adaptive system evolver) which is capable of evolving agent-based models using nature-inspired search algorithms. In this paper, we present an adaptation of this framework which supports the cloud computing paradigm. An example evolutionary experiment, which examines a simplified military scenario modeled with the agent-based simulation platform MANA, is presented. This experiment refers to Automated Red Teaming: a vulnerability assessment tool employed by defense analysts to study combat operations (which are regarded here as complex adaptive systems). The experimental results suggest promising research potential in exploiting the cloud computing paradigm to support computing intensive evolvable simulation experiments. Finally, we discuss an additional extension to our cloud computing compliant CASE in which we propose to incorporate a distributed evolutionary approach, e.g., the island-based model to further optimize the evolutionary search.

关键词： Cloud computing

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Untrusted Hardware Causes Double-Fetch Problems in the I/O Memory

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Journal of computer science & Technology 2018年第3期33卷 587-602页

作者： Kai Lu Peng-Fei Wang Gen Li Xu Zhou College of Computer National University of Defense Technology Changsha 410073 China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha 410073 China Collaborative Innovation Center of High-Performance Computing National University of Defense Technology Changsha 410073 China

The double fetch problem occurs when the data is maliciously changed between two kernel reads of the supposedly same data, which can cause serious security problems in the kernel. Previous research focused on the double fetches between the kernel and user applications. In this paper, we present the first dedicated study of the double fetch problem between the kernel and peripheral devices （aka. the hardware double fetch）. Operating systems communicate with peripheral devices by reading from and writing to the device mapped I/O （input and output） memory. Owing to the lack of effective validation of the attached hardware, compromised hardware could flip the data between two reads of the same I/O memory address, causing a double fetch problem. We propose a static pattern-matching approach to identify the hardware double fetches from the Linux kernel. Our approach can analyze the entire kernel without relying on the corresponding hardware. The results are categorized and each category is analyzed using case studies to discuss the possibility of causing bugs. We also find four previously unknown double-fetch vulnerabilities, which have been confirmed and fixed after reporting them to the maintainers.

关键词： hardware double fetch double-fetch bug I/O memory peripheral device double-fetch vulnerability

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DFTracker: detecting double-fetch bugs by multi-taint parallel tracking

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Frontiers of computer science 2019年第2期13卷 247-263页

作者： Pengfei WANG Kai LU Gen LI Xu ZHOU Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha 410073 China College of Computer National University of Defense Technology Changsha 410073 China Collaborative Innovation Center of High Performance Computing National University of Defense Technology Changsha 410073 China

A race condition is a common trigger for concurrency bugs. As a special case, a race condition can also occur across the kernel and user space causing a doublefetch bug, which is a field that has received little research attention. In our work, we first analyzed real-world doublefetch bug cases and extracted two specific patterns for doublefetch bugs. Based on these patter ns, we proposed an approach of multi-taint parallel tracking to detect double-fetch bugs. We also implemented a prototype called DFTracker (doublefetch bug tracker), and we evaluated it with our test suite. Our experiments demonstrated that it could effectively find all the double-fetch bugs in the test suite including eight realworld cases with no false negatives and minor false positives. In addition, we tested it on Linux kernel and found a new double-fetch bug. The execution overhead is approximately 2x for single-file cases and approximately 9x for the whole kernel test, which is acceptable. To the best of the authors1 knowledge, this work is the first to introduce multi-taint parallel tracking to double-fetch bug detection—an innovative method that is specific to double-fetch bug features—and has better path coverage as well as lower runtime overhead than the widely used dynamic approaches.

关键词： multi-taint parallel tracking double fetch race condition between kernel and user time of check to time of use real-world case analysis Clang Static Analyzer

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Key Message Approach to Optimize Communication of parallel Applications on Clusters

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Cluster computing 2003年第3期6卷 253-265页

作者： Zhu, Ming Cai, Wentong Lee, Bu-Sung Parallel and Distributed Computing Center School of Computer Engineering Nanyang Technological University Singapore

Over the past few years, cluster/distributed computing has been gaining popularity. The proliferation of the cluster/distributed computing is due to the improved performance and increased reliability of these systems. Many parallel programming languages and related parallel programming models have become widely accepted. However, one of the major shortcomings of running parallel applications on cluster/distributed computing environments is the high communication overhead incurred. To reduce the communication overhead, and thus the completion time of a parallel application, this paper describes a simple, efficient and portable Key Message (KM) approach to support parallel computing on cluster/distributed computing environments. To demonstrate the advantage of the KM approach, a prototype runtime system has been implemented and evaluated. Our preliminary experimental results show that the KM approach has better improvement on communication of a parallel application when network background load increases or the computation to communication ratio of the application decreases.

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Geo-distributed Analytical Streaming Architecture for IoT Platforms

Geo-Distributed Analytical Streaming Architecture for IoT Pl...

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2024 IEEE International Conference on Cluster computing, CLUSTER 2024

作者： Hoseiny Farahabady, M. Reza Zomaya, Albert Y. The University of Sydney School of Computer Science Center for Distributed and High Performance Computing SydneyNSW2006 Australia

ISBN: (纸本)9798350358711

The surge in real-time IoT data introduces scalability and computational challenges, necessitating advanced architectural and technological solutions. Streamed data processing is increasingly adopted across industries to enhance operational efficiency by extracting insights from vast, unstructured datasets. However, complex analytical tasks, such as multi-join queries, often require stateful iterative calculations on high-volume, high-velocity data, which challenges conventional programming models like MapReduce. This paper introduces an architectural model enabling application developers to create intricate streaming computational logic within an IoT platform. Our architecture supports scalable applications across distributed edge-tier nodes, particularly for iterative analytical operations on streamed data. We discuss core concepts and a timestamp model (borrowed from the timely data-flow concept) attached to data items circulating between computational blocks, which can execute concurrently on different edge-tier nodes. Additionally, we detail a buffer management mechanism that dynamically adjusts memory size in each computational block on nodes with limited capacity. This mechanism considers application performance requirements and runtime conditions to optimize buffer sizes. Performance evaluation against cloud-tier alternatives confirms the effectiveness of our solution. Experimental results show a significant reduction in p-99 delay compared to cloud-tier deployment with a database engine for analytical applications involving multi-join operations. © 2024 IEEE.

关键词： MapReduce

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Demystifying Ethereum account diversity:observations,models and analysis

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Frontiers of computer science 2022年第4期16卷 119-130页

作者： Chaofan Wang Xiaohai Dai Jiang Xiao Chenchen Li Ming Wen Bingbing Zhou Hai Jin Clusters and Grid Computing Lab National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabWuhan430074China School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan430074China School of Cyber Science and Engineering Huazhong University of Science and TechnologyWuhan430074China Centre for Distributed and High Performance Computing School of Information TechnologiesThe University of SydneyCamperdownNew South Wales2006Australia

Blockchain platform Ethereum has involved millions of accounts due to its strong potential for providing numerous services based on smart *** massive accounts can be divided into diverse categories,such as miners,tokens,and exchanges,which is termed as account diversity in this *** benefit of investigating diversity are multi-fold,including understanding the Ethereum ecosystem deeper and opening the possibility of tracking certain abnormal ***,the exploration of blockchain account diversity remains *** the most relevant studies,which focus on the deanonymization of the accounts on Bitcoin,can hardly be applied on Ethereum since their underlying protocols and user idioms are *** this end,we present the first attempt to demystify the account diversity on *** key observation is that different accounts exhibit diverse behavior patterns,leading us to propose the heuristics for classification as the *** then raise the coverage rate of classification by the statistical learning model Maximum Likelihood Estimation(MLE).We collect real-world data through extensive efforts to evaluate our proposed method and show its ***,we make an in-depth analysis of the dynamic evolution of the Ethereum ecosystem and uncover the abnormal arbitrage *** for the former,we validate two sweeping statements reliably:(1)standalone miners are gradually replaced by the mining pools and cooperative miners;(2)transactions related to the mining pool and exchanges take up a large share of the total *** latter analysis shows that there are a large number of arbitrage transactions transferring the coins from one exchange to another to make a price difference.

关键词： blockchain Ethereum classification account diversity network analysis

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Routing with uncertainty in wireless mesh networks

Routing with uncertainty in wireless mesh networks

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2010 IEEE 18th International Workshop on Quality of Service, IWQoS 2010

作者： Chen, Fajun Liu, Jiangchuan Li, Zongpeng Wang, Yijie Key Laboratory of Science and Technology for National Defence of Parallel and Distributed Processing School of Computer National University of Defense Technology China School of Computing Science Simon Fraser University Canada Department of Computer Science University of Caglary Canada

ISBN: (纸本)9781424459889

Existing routing protocols for Wireless Mesh Networks (WMNs) are generally optimized with statistical link measures, while not addressing on the intrinsic uncertainty of wireless links. We show evidence that, with the transient link uncertainties at PHY and MAC layers, a pseudo-deterministic routing protocol that relies on average or historic statistics can hardly explore the full potentials of a multi-hop wireless mesh. We study optimal WMN routing using probing-based online anypath forwarding, with explicit consideration of transient link uncertainties. We show the underlying connection between WMN routing and the classic Canadian Traveller Problem (CTP) [1]. Inspired by a stochastic recoverable version of CTP (SRCTP), we develop a practical SRCTP-based online routing algorithm under link uncertainties. We study how dynamic next hop selection can be done with low cost, and derive a systematic selection order for minimizing transmission delay. We conduct simulation studies to verify the effectiveness of the SRCTP algorithms under diverse network configurations. In particular, compared to deterministic routing, reduction of end-to-end delay (51:15∼73:02%) and improvement on packet delivery ratio (99:76%) are observed.

关键词： Routing protocols

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