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distributed computing systems and Approaches for Polar Science Research: An Interdisciplinary Systematic Review 24

Distributed Computing Systems and Approaches for Polar Scien...

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24th ieee/ACM international Symposium on Cluster, Cloud, and Internet computing (CCGrid)

作者： Kathiravelu, Pradeeban Birmingham, Ryan Univ Alaska Anchorage Anchorage AK 99508 USA Emory Univ Atlanta GA 30322 USA

ISBN: (纸本)9798350377521;9798350377514

Polar science is an umbrella term for several research disciplines practiced in Earth's polar regions and other planets. Polar science research includes studies performed on land (such as geology and archeology on the circumpolar tundra), air (atmospheric research), sky (planetary observations due to dark, clear, and clean skies during the polar nights), and ocean (marine studies in the Arctic and the Southern Oceans). Many polar science research works look into overlapping complementary studies. distributed computing is a discipline of computer science that involves computations across multiple distinct physically separated computing resources, such as computer clusters, clouds, and the edge. distributed computing has enabled efficient, scalable, and elastic execution of complex computational problems on utility hardware without expecting access to expensive infrastructure or supercomputers. In this paper, we screen 770 for the interdisciplinary research of distributed computing used in or developed for polar science. After systematically removing the irrelevant studies, we assess the full text of 72 papers to understand the distributed systems research landscape for polar science. We then specifically study 22 polar science research works that develop or heavily utilize distributed computing frameworks or principles in detail. Our study finds distributed execution frameworks instrumental for polar science due to the complex and real-time computational needs, coupled with the remote location requiring efficient network bandwidth availability and usage to access remote resources.

关键词： Computer Networks distributed computing distributed systems Environmental systems Polar Science

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Virtual Try-On Application leveraging RoCE in Low-latency Edge computing Networks 24

Virtual Try-On Application leveraging RoCE in Low-latency Ed...

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24th international conference on Transparent Optical Networks (ICTON)

作者： Guaitolini, Michelangelo Khan, Abdul H. Le Rouzic, Emilie Paolucci, Francesco Cugini, Filippo Consorzio Nazl Interuniv Telecomunicaz CNIT Pisa Italy

ISBN: (纸本)9798350377330;9798350377323

Direct memory access (RDMA) over Converged Ethernet (RoCE) allows for direct memory transfers between systems, granting minimal latency and CPU overhead. this allows low-latency applications where data collection, analytics and feedback to the user are distributed between different nodes, optimizing resource management. RoCE, originally designed for data center operations, has the potential to effectively support applications deployed on edge nodes, where limited resources are available and low latency is required. this demo shows the use of RoCE in support to an AI-based application for smart shopping, deployed at the edge.

关键词： Edge computing RDMA over Converged Ethernet Low-latency networking virtual-try on application smart shopping

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IDIOMS: Index-powered distributed Object-centric Metadata Search for Scientific Data Management 24

IDIOMS: Index-powered Distributed Object-centric Metadata Se...

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24th ieee/ACM international Symposium on Cluster, Cloud, and Internet computing (CCGrid)

作者： Zhang, Wei Tang, Houjun Byna, Suren Lawrence Berkeley Natl Lab Berkeley CA 94720 USA Ohio State Univ Columbus OH USA

ISBN: (纸本)9798350395679;9798350395662

Affix-oriented metadata search is one of the essential fuzzy search capabilities that allow users to find data of interest in their voluminous data set with incomplete query conditions. With the recent transition towards object-centric data management systems in the science community, there is a paramount need for the support of such features in distributed settings. However, existing metadata search solutions either do not support efficient affix-oriented metadata search or do not suit well in a distributed setting of object-centric data management systems. To bridge this gap, we introduce IDIOMS, a metadata search solution underpinned by a distributed metadata index, meticulously designed to enable high-performance affix-oriented metadata search for parallel object-centric storage. One of the standout features of IDIOMS is its efficiency in supporting four distinct types of highly demanded metadata queries. Furthermore, IDIOMS is flexibly catering to both independent and collective metadata search operations. Our experimental comparisons with SoMeta, a state-of-the-art metadata query method, demonstrate more than 400x performance boost for independent queries and up to 300x performance improvements for collective queries, while keeping a small index management overhead.

关键词： Metadata Search Metadata Management Parallel Data Processing distributed Data Management Scientific Data Management

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In-Memory computing: Global Energy Consumption, Carbon Footprint, Technology, and Products Status Quo 24

In-Memory Computing: Global Energy Consumption, Carbon Footp...

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ieee 24th international conference on Nanotechnology (NANO)

作者： TaheriNejad, Nima TU Wien EclectX Team Vienna Austria Heidelberg Univ Heidelberg Germany

ISBN: (纸本)9798350386257;9798350386240

In this paper, we highlight and quantify the importance and potential role of In-Memory Computation (IMC) and memory technologies in the future of humans' global footprint. To this end, we calculate the estimated energy consumption and carbon emission associated with the data movement inside computing systems and put them in perspective using tangible examples. Next, we review various memory technologies as well as their advantages and disadvantages (especially regarding their energy consumption), for usage in computing systems as memory and computing elements. We calculate what their impact is and what would be the potential savings of migrating towards emerging memory technologies. We discuss some of the challenges these emerging memory technologies face, before presenting the highlights of the IMC products on or near the market. this paper aims at providing an insight on the impact of IMC and memory technology on the society at large and clarify the importance of working on IMC and emerging memory technologies to lower the power consumption and overall footprint of computing systems. the status of IMC products show that while moving in the right direction, there is a substantial body of work to be done. We hope this will help engineers to better grasp the extent of the impact they can produce and motivate them further in the pursuit of better computing systems.

关键词： In-Memory computing Memory Technology Global Impact Energy Consumption Carbon Emission Industrial Products

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Research on Concurrent Destruction of Embedded High-Availability distributed computing Platform 24

Research on Concurrent Destruction of Embedded High-Availabi...

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24th ieee/ACIS international conference on Computer and Information Science, ICIS 2024

作者： He, Qinhan Liu, Jinhui He, Lijun Zhou, Guangfei School of Artificial Intelligence Xidian University Xi'an China School of Computer Science and Technology Xidian University Xi'an China Aeronautics Computing Technique Research Institute Xi'an China

ISBN: (纸本)9798350376647

the embedded distributed computing platform runs large-scale tasks with high complexity and high computing capacity requirements, and divides the embedded tasks required by super computing capacity into multiple independent sub-tasks, which can be simultaneously allocated to multiple computing nodes for paralleled execution. this paper researches that the embedded high-availability distributed computing platform ensures the real-time and deterministic requirements of embedded system function execution through the distribution of computing resources, network communication resources and storage resources, and implements the allocation and execution of distributed tasks under static partition configuration based on the distributed computing framework of the Actor model. In the paper, the destruction technology of large-scale storage resources in embedded high-availability distributed computing platform is also studied, the concurrent destruction is proposed, which improves the efficiency of destructive power input, solves the problems of large amount of computing nodes destruction, large destructive current and long destructive duration of large-scale storage resources in embedded system, and effectively solves the leakage of key information. © 2024 ieee.

关键词： Concurrent destruction distributed computing High availability

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Preserving Near-Optimal Gradient Sparsification Cost for Scalable distributed Deep Learning 24

Preserving Near-Optimal Gradient Sparsification Cost for Sca...

引用

24th ieee/ACM international Symposium on Cluster, Cloud, and Internet computing (CCGrid)

作者： Yoon, Daegun Oh, Sangyoon ETRI Daejeon South Korea Ajou Univ Suwon South Korea

ISBN: (纸本)9798350395679;9798350395662

Communication overhead is a major obstacle to scaling distributed training systems. Gradient sparsification is a potential optimization approach to reduce the communication volume without significant loss of model fidelity. However, existing gradient sparsification methods have low scalability owing to inefficient design of their algorithms, which raises the communication overhead significantly. In particular, gradient build-up and inadequate sparsity control methods degrade the sparsification performance considerably. Moreover, communication traffic increases drastically owing to workload imbalance of gradient selection between workers. To address these challenges, we propose a novel gradient sparsification scheme called ExDyna. In ExDyna, the gradient tensor of the model comprises fined-grained blocks, and contiguous blocks are grouped into non-overlapping partitions. Each worker selects gradients in its exclusively allocated partition so that gradient build-up never occurs. To balance the workload of gradient selection between workers, ExDyna adjusts the topology of partitions by comparing the workloads of adjacent partitions. In addition, ExDyna supports online threshold scaling, which estimates the accurate threshold of gradient selection on-the-fly. Accordingly, ExDyna can satisfy the user-required sparsity level during a training period regardless of models and datasets. therefore, ExDyna can enhance the scalability of distributed training systems by preserving near-optimal gradient sparsification cost. In experiments, ExDyna outperformed state-of-the-art sparsifiers in terms of training speed and sparsification performance while achieving high accuracy.

关键词： distributed deep learning gradient sparsification scalability

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A distributed, Asynchronous Algorithm for Large-Scale Internet Network Topology Analysis 24

A Distributed, Asynchronous Algorithm for Large-Scale Intern...

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24th ieee/ACM international Symposium on Cluster, Cloud, and Internet computing (CCGrid)

作者： Elmougy, Youssef Hayashi, Akihiro Sarkar, Vivek Georgia Inst Technol Atlanta GA 30332 USA

ISBN: (纸本)9798350395679;9798350395662

With the growing complexity of modern internet networks, we introduce a distributed, asynchronous, and scalable algorithm tailored for determining the centrality and importance of various levels of the global internet network topology at a massive scale. By utilizing triangle formations and neighborhood densities in these complex networks, our algorithm provides valuable insights into the structural importance of individual nodes and the intricate relationships among interconnected entities. Focusing on the global internet's prime components routers, IP addresses, and Autonomous systems - the algorithm provides a scalable solution extending to the global internet infrastructure, datacenters, cloud networks, and private networks. By taking advantage of the parallelism, distributed processing, efficient communication, and fine-grained asynchronous execution through an Actor-based programming system, our algorithm is capable of efficiently processing and performing rapid computations on large-scale internet networks. We perform scalability studies on the NERSC Perlmutter supercomputer and the Georgia Tech HPC PACE cluster using three large-scale real-world network datasets and one large-scale synthetic network dataset, achieving up to 91.7% parallel efficiency scaling out to 2K cores and reducing execution time from 5.7 hours to 18.3 seconds, while performing 105.4x better on average compared to related approaches. Our research contributes significantly to facilitating enhanced network management, fault tolerance and resilience, and security, but as well to improving overall network stability, reducing latency, and optimizing energy consumption across the vast internet network devices environment.

关键词： Network Topology Internet Analysis Actors Selectors distributed systems Scalable computing Centrality Shared Memory PGAS OpenSHMEM

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2024 ieee/ACIS 24th international conference on Computer and Information Science, ICIS 2024 - Proceedings

2024 IEEE/ACIS 24th International Conference on Computer and...

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24th ieee/ACIS international conference on Computer and Information Science, ICIS 2024

ISBN: (纸本)9798350376647

the proceedings contain 35 papers. the topics discussed include: research on concurrent destruction of embedded high-availability distributed computing platform;unsupervised community detection framework for social network forensics;intrusion detection system based on machine learning algorithm to detect the DDoS attack in the IoT network;diagnosability of the strong product of paths and cycles under PMC model;deep learning based satellite communication anti-jamming systems;deep deterministic strategy gradient method using plot experience playback;application scenario analysis of large language models education based on activity theory;and asynchronous federated learning for personal credit assessment based on copula reputation.

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Building Trust in Data for IoT systems 24

Building Trust in Data for IoT Systems

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24th ieee/ACM international Symposium on Cluster, Cloud, and Internet computing (CCGrid)

作者： Margaria, Davide Carelli, Alberto Vesco, Andrea LINKS Fdn Cvbersecur Res Grp I-10138 Turin Italy

ISBN: (纸本)9798350377521;9798350377514

Nowadays, Internet of things platforms are being deployed in a wide range of application domains. Some of these include use cases with security requirements, where the data generated by an IoT node is the basis for making safety-critical or liability-critical decisions at system level. the challenge is to develop a solution for data exchange while proving and verifying the authenticity of the data from end-to-end. In line with this objective, this paper proposes a novel solution with the proper protocols to provide Trust in Data, making use of two Roots of Trust that are the IOTA distributed Ledger Technology and the Trusted Platform Module. the paper presents the design of the proposed solution and discusses the key design aspects and relevant trade-offs. the paper concludes with a Proof-of-Concept implementation and an experimental evaluation to confirm its feasibility and to assess the achievable performance.

关键词： Internet of things distributed Ledger Technology IOTA Tangle Trusted computing Remote Attestation

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Deployment of Multi-Agent System Pipelines for Near-Real-Time Operation of 6G Network Services 24

Deployment of Multi-Agent System Pipelines for Near-Real-Tim...

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24th international conference on Transparent Optical Networks (ICTON)

作者： Gonzalez, Pol Barzegar, Sima Ruiz, Marc Velasco, Luis Univ Politecn Catalunya UPC Opt Commun Grp GCO Barcelona Spain

ISBN: (纸本)9798350377330;9798350377323

A Machine Learning Function Orchestrator deploying and reconfiguring Multi-Agent systems (MAS) pipelines to support near-real-time control of network services is showcased. An architecture to orchestrate the dynamic deployment of agents has been defined by integrating different components. Near-real-time operation of an optical system controlled by a distributed MAS fed with telemetry is presented as use case.

关键词： distributed intelligence Multi-agent systems Telemetry Orchestration

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