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arXiv 2024年

作者： Li, Heng Li, Haojin Chen, Jianyu Fu, Huazhu Liu, Jiang The Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China The Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China The Institute of High Performance Computing Agency for Science Technology and Research Singapore

Deep learning models often encounter challenges in making accurate inferences when there are domain shifts between the source and target data. This issue is particularly pronounced in clinical settings due to the scarcity of annotated data resulting from the professional and private nature of medical data. Despite the existence of decent solutions, many of them are hindered in clinical settings due to limitations in data collection and computational complexity. To tackle domain shifts in data-scarce medical scenarios, we propose a Random frequency filtering enabled Single-source Domain Generalization algorithm (RaffeSDG), which promises robust out-of-domain inference with segmentation models trained on a single-source domain. A frequency filter-based data augmentation strategy is first proposed to promote domain variability within a single-source domain by introducing variations in frequency space and blending homologous samples. Then Gaussian filter-based structural saliency is also leveraged to learn robust representations across augmented samples, further facilitating the training of generalizable segmentation models. To validate the effectiveness of RaffeSDG, we conducted extensive experiments involving out-of-domain inference on segmentation tasks for three human tissues imaged by four diverse modalities. Through thorough investigations and comparisons, compelling evidence was observed in these experiments, demonstrating the potential and generalizability of RaffeSDG. The code is available at https://***/liamheng/NonIID_Medical_Image_Segmentation. Copyright © 2024, The Authors. All rights reserved.

关键词： Inference engines

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Improving Software Defined Network Controllers in a Multi-Vendor Environment

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SSRN 2023年

作者： Deneke, Bereketeab Berhanu Beyene, Asrat Mulatu Haile, Endalew Ayenew Department of Computer Science School of Graduate Studies St. Mary’s University Addis Ababa Ethiopia High Performance Computing & Big Data Analytics CoE Department of Electrical and Computer Engineering Addis Ababa Science and Technology University Addis Ababa Ethiopia Adama Science and Technology University School of Electrical Engineering and Computing Electrical Power and Control Engineering Adama Ethiopia

Software Defined Networking (SDN) is an emerging networking paradigm with the potential to foster innovation through programmable networks. SDNs are characterized by the separation of control and data planes where, in a logically centralized controller, it’s possible to make routing decisions on behalf of forwarding elements. For this, there are different protocols used like Open Flow, Forward and Control Element Separation (FORCES), Path Computation Element Protocol (PCEP), Network Configuration Protocol (NETCONF), and Interface to Routing System (IRS). Border Gateway Protocol (BGP) is one such protocol that can enable the network programmability promised by SDNs. The controllers used in BGP as control plane protocol leverages RESTCONF (RFC 8040) as management plane protocol to interact with physical routers, switches, and network service firewalls. Therefore, the aim of this work is to improve the performance of SDN controllers using BGP enabling a multi-vendor environment without requiring infrastructure upgrade showcasing how interoperability can be achieved. The proposed system is implemented using OpenDaylight controllers. The performance of the prototype is evaluated using Latency, Throughput, CPU consumption, and TTL (Time to Live). Based on the simulation results it is observed that the SDN controllers that use BGP show improvements in terms of Latency and Throughput. © 2023, The Authors. All rights reserved.

关键词： Controllers

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An environment for importance sampling based on stochastic activity networks

An environment for importance sampling based on stochastic a...

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Reliable Distributed Systems

作者： W.D. Obal W.H. Sanders Department of Electrical and Computer Engineering University of Arizona Tucson Tucson AZ USA Center for Reliable and High-Performance Computing Coordinated Science Laboratory University of Illinois Urbana-Champaign Urbana IL USA

Model-based evaluation of reliable distributed and parallel systems is difficult due to the complexity of these systems and the nature of the dependability measures of interest. The complexity creates problems for analytical model solution techniques, and the fact that reliability and availability measures are based on rare events makes traditional simulation methods inefficient. Importance sampling is a well-known technique for improving the efficiency of rare event simulations. However, finding an importance sampling strategy that works well in general is a difficult problem. The best strategy for importance sampling depends on the characteristics of the system and the dependability measure of interest. This fact motivated the development of an environment for importance sampling that would support the wide variety of model characteristics and interesting measures. The environment is based on stochastic activity networks, and importance sampling strategies are specified using the new concept of the importance sampling governor. The governor supports dynamic importance sampling strategies by allowing the stochastic elements of the model to be redefined based on the evolution of the simulation. The utility of the new environment is demonstrated by evaluating the unreliability of a highly dependable fault-tolerant unit used in the well-known MARS architecture. The model is non-Markovian, with Weibull distributed failure times and uniformly distributed repair times.< >

关键词： Monte Carlo methods Stochastic processes Analytical models Discrete event simulation Availability Sampling methods Stochastic systems computer network reliability computer networks Concurrent computing

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Automatic classification of node types in switch-level descriptions

Automatic classification of node types in switch-level descr...

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IEEE International Conference on computer Design: VLSI in computers and Processors, (ICCD)

作者： D.T. Blaauw P. Banerjee J.A. Abraham Center for Reliable an High Performance Computing Coordinated Science Laboratory University of Illinois Urbana-Champaign Urbana IL USA Department of Electrical & Computer Engineering University of Texas Austin Austin TX USA

In switch-level simulation, nodes carry a charge on their parasitic capacitance from one evaluation to the next, which gives them a memory quality. A node is classified as temporary if its memory aspect is lost and cannot affect the circuit operation, whereas a node is classified as a memory node if the memory of the node is maintained and can affect the circuit operation. Accurate classification of nodes into temporary and memory nodes increases the performance of compiled simulators and high-level model generators. An approach for reliable automatic classification of nodes in a switch-level description is introduced. Both an exhaustive, exponential-time algorithm and a polynomial-time heuristic are presented. The heuristic was implemented and tested for several large circuits, including a commercial microprocessor. For this processor, the proposed heuristics identified an average of 92% of all nodes as temporary nodes. The heuristic was applied in a high-level model generator and significantly increased its performance.< >

关键词： Circuit simulation Parasitic capacitance Circuit testing Maintenance Polynomials Switching circuits Switched capacitor circuits Joining processes Capacitance measurement Size measurement

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UltraSAN version 3 overview

UltraSAN version 3 overview

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International Workshop on Petri Nets and performance Models (PNPM)

作者： D.D. Deavours W.D. Obal M.A. Qureshi W.H. Sanders A.P.A. van Moorsel Center for Reliable and High-Performance Computing Coordinated Science Laboratory University of Illinois Urbana-Champaign Urbana IL USA Department of Electrical and Computer Engineering University of Arizona Tucson Tucson AZ USA

UltraSAN is a software package for model-based evaluation of systems represented as stochastic activity networks. The software has been implemented in a modular fashion, with clearly delineated interfaces between model specification, construction, and solution. UltraSAN offers an X Windows-based user interface and both analytical and simulation solution modules for transient and steady-state performance, dependability, and performability measures. Furthermore, the tool facilitates graphical representation of the obtained results by its report generator. This paper gives a very brief overview and pointers to more detailed descriptions of the software.

关键词： Steady-state Storage area networks Modular construction User interfaces Automatic control Joining processes Libraries Markov processes Probability density function Web sites

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A Combined Dual-stage Framework for Robust Scheduling of Scientific Applications in Heterogeneous Environments with Uncertain Availability

A Combined Dual-stage Framework for Robust Scheduling of Sci...

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IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Florina M. Ciorba Timothy Hansen Srishti Srivastava Ioana Banicescu Anthony A. Maciejewski Howard Jay Siegel Center for Information Services and High Performance Computing Technische Universität Dresden Dresden Germany Department of Electrical and Computer Engineering Colorado State University Fort Collins CO USA Department of Computer Science and Engineering Mississippi State University Mississippi MS USA Department of Electrical and Computer Engineering Department of Computer Science Colorado State University Fort Collins CO USA

Scheduling parallel applications on existing or emerging computing platforms is challenging, and, among other attributes, must be efficient and robust. A dual-stage framework is proposed in this paper to evaluate the robustness of efficient resource allocation and dynamic load balancing of scientific applications in heterogeneous computing environments with uncertain availability. The first stage employs robust resource allocation heuristics, while the second stage incorporates robust dynamic loop scheduling techniques. The combined dual-stage framework constitutes a comprehensive framework that enables and provides guarantees for the robust execution of scientific applications in computing systems where uncertainty is caused by various unpredictable perturbations. The paper reports on studies for determining the best techniques to be used for each stage that: (a) maximize the probability that the system make span satisfies a deadline, and (b) minimize the system make span for every given availability level in the system. The usefulness and benefits of the proposed framework are demonstrated via a small scale example.

关键词： Availability Robustness Resource management Uncertainty Runtime Dynamic scheduling Program processors

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Online Demand Peak Shaving with Machine-Learned Advice in Cyber-Physical Energy Systems

Online Demand Peak Shaving with Machine-Learned Advice in Cy...

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IEEE International Symposium on Dependable, Autonomic and Secure computing (DASC)

作者： Minxi Fengl Wei Li Boyu Qin Albert Y. Zomaya Centre for Distributed and High Performance Computing School of Computer Science The University of Sydney Australia Department of Electrical Engineering State Key Laboratory of Electrical Insulation and Power Equipment Xi'an Jiaotong University China

With the deep integration of cyber tools, control algorithms are increasingly employed in cyber-physical energy systems to enhance management, cost efficiency, and robustness. Effective demand load management is crucial in cyber-physical energy systems as it directly impacts operational costs. Failure to adequately manage spiky or seasonal demand loads can lead to significant expenses on monthly utility bills. In this study, we propose AMPAMOD, a randomized online algorithm with machine-learned advice, to optimize battery operations and mitigate highly dynamic peak loads. AMPAMOD utilizes limited advice from machine learning algorithms to guide our online algorithm and ensure cost-effective peak load management. The theoretical analysis shows that our solution has minimal advice complexity, a linear computational cost, and an improved competitive ratio. Finally, we conduct extensive trace-driven experiments on real-world datasets. AMPAMOD achieves a peak shaving success rate of over 90%, outperforming baselines by at least 50%. These experimental results confirm theoretical findings and demonstrate the potential of AMPAMOD.

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Global and localized parallel preconditioning techniques for large scale solid Earth simulations

Global and localized parallel preconditioning techniques for...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Kai Wang Sangbae Kim Jun Zhang K. Nakajima H. Okuda Laboratory for High Performance Scientific Computing and Computer Simulation Department of Computer Science University of Kentucky Lexington KY USA Research Organization for Information Science and Technology Meguro Tokyo Japan Department of Quantum Engineering and System Sciences University of Tokyo Bunkyo Tokyo Japan

We investigate and compare a few parallel preconditioning techniques in the iterative solution of large sparse linear systems arising from solid Earth simulation with and without using contact information in the domain partitioning process. Previous studies are focused on using static or matrix pattern based incomplete LU (ILU) preconditioners in a localized preconditioner implementation. Our current studies are concerned with preconditioner performance for solving two different cases with and without known contact information. For the cases with contact information, we use localized threshold value based incomplete LU (ILUT) preconditioner to improve efficiency. For the cases without contact information, we use a global sparse approximate inverse preconditioner with a static sparsity pattern to achieve robustness. Numerical results from simulating ground motion on a parallel supercomputer are given to compare the effectiveness of these parallel preconditioning techniques.

关键词： Large-scale systems Earth Solid modeling Linear systems Sparse matrices Computational modeling computer simulation Uniform resource locators Geoscience Information science

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A Static Binary Instrumentation Threading Model for Fast Memory Trace Collection

A Static Binary Instrumentation Threading Model for Fast Mem...

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high performance computing, Networking, Storage and Analysis (SCC), SC Companion:

作者： Michael A. Laurenzano Joshua Peraza Laura Carrington Ananta Tiwari William A. Ward Roy Campbell Performance Modeling and Characterization Laboratory San Diego Supercomputer Center University of California San Diego USA Department of Computer Science and Engineering University of California San Diego USA High Performance Computing Modernization Program United States Department of Defense USA

In order to achieve a high level of performance, data intensive applications such as the real-time processing of surveillance feeds from unmanned aerial vehicles will require the strategic application of multi/many-core processors and coprocessors using a hybrid of inter-process message passing (e.g. MPI and SHMEM) and intra-process threading (e.g. pthreads and OpenMP). To facilitate program design decisions, memory traces gathered through binary instrumentation can be used to understand the low-level interactions between a data intensive code and the memory subsystem of a multi-core processor or many-core co-processor. Toward this end, this paper introduces the addition of threading support for PMaCs Efficient Binary Instrumentation Toolkit for Linux/x86 (PEBIL) and compares PEBILs threading model to the threading models of two other popular Linux/x86 binary instrumentation platforms - Pin and Dyninst - on both theoretical and empirical grounds. The empirical comparisons are based on experiments which collect memory address traces for the OpenMP-threaded implementations of the NASA Advanced Supercomputing Parallel Benchmarks (NPBs). This work shows that the overhead of collecting full memory address traces for multithreaded programs is higher in PEBIL (7.7x) than in Pin (4.7x), both of which are significantly lower than Dyninst (897x). This work also shows that PEBIL, uniquely, is able to take advantage of interval-based sampling of a memory address trace by rapidly disabling and re-enabling instrumentation at the transitions into and out of sampling periods in order to achieve significant decreases in the overhead of memory address trace collection. For collecting the memory address streams of each of the NPBs at a 10% sampling rate, PEBIL incurs an average slowdown of 2.9x compared to 4.4x with Pin and 897x with Dyninst.

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Realistic workload scheduling policies for taming the memory bandwidth bottleneck of SMPs

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2004年 3296卷 286-296页

作者： Antonopoulos, Christos D. Nikolopoulos, Dimitrios S. Papatheodorou, Theodore S. Department of Computer Science College of William and Mary 118 McGlothlin-Street Hall Williamsburg VA 23187-8795 United States High Performance Information Systems Lab. Computer Engineering and Informatics Department University of Patras 26500 Patras Greece

In this paper we reformulate the thread scheduling problem on multiprogrammed SMPs. Scheduling algorithms usually attempt to maximize performance of memory intensive applications by optimally exploiting the cache hierarchy. We present experimental results indicating that - contrary to the common belief - the extent of performance loss of memory-intensive, multiprogrammed workloads is disproportionate to the deterioration of cache performance caused by interference between threads. In previous work [1] we found that memory bandwidth saturation is often the actual bottleneck that determines the performance of multiprogrammed workloads. Therefore, we present and evaluate two realistic scheduling policies which treat memory bandwidth as a first-class resource. Their design methodology is general enough and can be applied to introduce bus bandwidth-awareness to conventional scheduling policies. Experimental results substantiate the advantages of our approach. © Springer-Verlag 2004.

关键词： Scheduling algorithms

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