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检索条件"任意字段=2024 International Symposium on Computer Architecture and High Performance Computing Workshops"

共 5235 条记录，以下是621-630 订阅

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Examining the Viability of Row-Scale Disaggregation for Production Applications

Examining the Viability of Row-Scale Disaggregation for Prod...

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high performance computing, Networking, Storage and Analysis, SC-W: workshops of the international Conference for

作者： Curtis Shorts Ryan E. Grant Electrical and Computer Engineering Department Queen’s University Kingston Canada

ISBN: (数字)9798350355543

ISBN: (纸本)9798350355550

Row-scale Composable Disaggregated Infrastructure (CDI) is a heterogeneous high performance computing (HPC) architecture that relocates the GPUs to a single chassis which CPU nodes can then request compute resources from. This is a distinctly different architecture from rack-scaled CDI as the GPUs are accessed over a network rather than existing in the same PCIe domain as the CPUs. Row-scale CDI expands the benefits and flexibility of rack-scaled CDI, while introducing new challenges. For example, with row-scale CDI, one must account for the effects of "slack", a latency in the CPU-to-GPU communication times due to network delays. This work seeks to assess potential challenges with row-scale CDI to determine which factors are most important to consider when deploying a CDI system. Our strong scaling application analyses reveal that there are two types of HPC workloads that may benefit from row-scale CDI; those that are CPU dominant and periodically call on the GPU to do highly parallel tasks and those that are GPU dominant and primarily rely on the CPU to coordinate work. We perform comparisons between the kernel and data transfer characteristics of each application to a slack proxy application which allowed for the development of a mathematical model to predict the performance penalty different applications can face as a result of slack. To illustrate this we profile two applications using our proposed method and find that they pessimistically would see a less than a 1% performance penalty above the effects of crossing the network in an environment which induced 100 µs of slack, or a distance of 20 km at the speed of light in a fibre optic network cable. This demonstrates that both row-scale and cluster-scale CDI are viable technologies from an application performance perspective.

关键词： high performance computing Graphics processing units Optical fiber cables Production computer architecture Software Mathematical models Resource management Kernel Testing

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LogESP: Enhancing Log Semantic Representation With Word Position for Anomaly Detection 22

LogESP: Enhancing Log Semantic Representation With Word Posi...

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22nd IEEE international symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： Ni, Zhengping Di, Xiaoqiang Liu, Xu Chang, Lianjie Li, Jinqing Tang, Qiyue Changchun University of Science and Technology School of Computer Science and Technology Changchun130022 China Changchun University of Science and Technology Jilin Province Key Laboratory of Network and Information Security Changchun130022 China Changchun University of Science and Technology Information Center Changchun130022 China

ISBN: (纸本)9798331509712

Logs are valuable data for detecting anomalous network behavior. Accurate feature extraction from logs is essential for anomaly detection. However, statistical-based feature extraction methods consider the statistical features of logs over a period of time, while ignoring the semantic information in each log. Most semantic-based feature extraction methods only embed the token semantics into high-dimensional vectors for semantic representation, which may lead to the lack of positional information between tokens, so that the uniqueness of the log template semantics cannot be maintained. At the same time, it also causes time-consuming problems due to high-dimensional data. To address the above challenges, we propose a novel log anomaly detection method called LogESP, which enhances the semantic representation of logs with positional information. Lo-gESP aims to effectively capture the semantic differences between normal and abnormal logs, thereby providing a new perspective for accurate detection of abnormal network behavior. First, we select representative words to summarize the semantics of log templates, then use structured tuples to enhance the semantic representation of the templates, and finally, construct LSTM model to extract the temporal features of the log sequences. Experimental results on two public log datasets (BGL and HDFS) show better performance compared to other state-of-the-art methods. © 2024 IEEE.

关键词： Spatio-temporal data

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Deep Neural Network Framework for the Identification of Smoking Events in 6G and Cloud-Enabled Smart Cities

Deep Neural Network Framework for the Identification of Smok...

引用

Cluster, Cloud and Internet computing workshops (CCGridW), IEEE/ACM international symposium on

作者： Brij B. Gupta Kwok Tai Chui Akshat Gaurav Jinsong Wu Department of Computer Science and Information Engineering Asia University Taichung Taiwan Department of Electrical and Computer Engineering Lebanese American University Beirut Lebanon Hong Kong Metropolitan University (HKMU) Hong Kong Ronin Institute Montclair NJ USA Universidad de Chile Chile

ISBN: (数字)9798350377514

ISBN: (纸本)9798350377521

This study introduces a deep neural network framework for the identification of smoking events, designed to integrate seamlessly with the burgeoning infrastructure of 6G and cloud-enabled smart cities. We developed a model that not only learns from high-dimensional data but also adapts to the dynamic urban landscapes. Our model underwent rigorous training and validation phases, achieving a classification accuracy of 71%, with balanced precision and recall across both smoking and nonsmoking classes. The results, encapsulated in a comprehensive confusion matrix, highlight the model’s potential in real-time monitoring and public health policy enforcement. This paper details the model architecture, training process, and evaluation metrics, underscoring the significant role of deep learning in enhancing urban surveillance systems for future smart cities.

关键词： 6G mobile communication Training Measurement Cloud computing Adaptation models Smart cities Surveillance Artificial neural networks Real-time systems Public healthcare

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Breast Cancer Classification Using DDPM and Holographic Guidance Diffusion Framework 22

Breast Cancer Classification Using DDPM and Holographic Guid...

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22nd IEEE international symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： You, Yuxin Gan, Hong-Seng Shimizu, Akinobu Ramlee, Muhammad Hanif Basarudin, Hafiz Vu, Viet-Vu Xi'an Jiaotong - Liverpool University School of Ai and Advanced Computing Suzhou China Tokyo University of Agriculture and Technology Institute of Engineering Tokyo Japan Universiti Teknologi Malaysia Department of Biomedical Engineering and Health Sciences Johor Bahru Malaysia Universiti Tunku Abdul Rahman Lee Kong Chian Faculty of Engineering and Science Kajang Malaysia Cmc University Faculty of Information Technology and Communications Hanoi Viet Nam

ISBN: (纸本)9798331509712

Breast cancer is a serious health threat to women. The early detection of breast cancer is crucial to improving survival rates and reducing the difficulty of treatment. In recent years, denoising diffusion probability models (DDPM) have performed well in image generation, but their application to breast cancer classification remains unknown. Additionally, conditional priors are often the most important source of information for diffusion models to solve problems, and fuzzy lesions or high-noise images pose a significant challenge for the model to extract accurate prior information. To address these issues, we propose a new classification model based on DDPM and combine it with the holographic guided diffusion framework (HGDF) to remove noise from images through specific guidance and make full use of HPC resources to improve the classification performance of breast cancer images. Results from the experiment indicate that the model has excellent accuracy in ultrasound images (BUS dataset) and mammography images (MAMMO dataset), with accuracy of 86.17 % ± 1.74% and 94.32% ± 2.31%, respectively. © 2024 IEEE.

关键词： Lung cancer

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An Open-Source RISC-V Vector Math Library

An Open-Source RISC-V Vector Math Library

引用

computer Arithmetic (ARITH)

作者： Ping Tak Peter Tang Riovs Inc. Santa Clara CA

ISBN: (数字)9798350384321

ISBN: (纸本)9798350384338

RISC-V is an open royalty-free instruction set architecture (ISA) under the governance of RISC-V international. The ISA consists of a base instruction set and many modular extensions among which the vector extension that supports data parallel execution is recently ratified. Supporting the goal of an open ISA to accelerate innovation, we developed an open-source double-precision vector math library as a highly relevant addition to the high-performance computing (HPC) ecosystem. This paper introduces the RISC-V vector ISA, some of those computational instructions we found most useful, and the software structure of, as well as the various numerical techniques employed to make the library accurate and efficient.

关键词： Technological innovation Instruction sets high performance computing Ecosystems computer architecture Digital arithmetic Vectors

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Trace Analysis of Electric Micromobility and its Application for City Sensing 28

Trace Analysis of Electric Micromobility and its Application...

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28th IEEE/ACM international symposium on Distributed Simulation and Real Time Applications, DS-RT 2024

作者： Esposito, Alfonso Ciabattini, Leonardo Sciullo, Luca Montanari, Marco Bononi, Luciano Felice, Marco Di University of Bologna Department of Computer Science and Engineering Italy

ISBN: (纸本)9798331527211

Electric micromobility is increasingly being adopted as a urban transportation means. This emerging class of vehicles, thanks to its onboard hardware and embedded sensors, can be used for gathering IoT data across cities or for producing valuable insights on users' driving behavior. However, the limited availability of public datasets on e-mobility poses a significant challenge for research, restricting the potential for improving the modeling and optimization of city-scale mobility systems. In this paper, we present an in-depth analysis of electric micromobility using GPS traces from three Italian cities. Furthermore, we identify significant spatio-temporal patterns and develop algorithms to reconstruct rental trips and model user demands, enabling the generation of synthetic vehicular traces for various urban scenarios and arbitrary number of vehicles. Our findings reveal distinct temporal patterns influenced by seasons and time of day, and spatial patterns showing varying distances covered by different vehicle types. Notably, our simulations for the city of Bologna demonstrate the potential of using electric micromobility vehicles as mobile sensors for city-sensing applications, providing extensive urban coverage with minimal units. © 2024 IEEE.

关键词： Urban transportation

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Serverless computing for Dynamic HPC Workflows

Serverless Computing for Dynamic HPC Workflows

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high performance computing, Networking, Storage and Analysis, SC-W: workshops of the international Conference for

作者： Vijay Thurimella Philipp Raith Rolando P. Hong Enriquez Anderson Andrei Da Silva Gourav Rattihalli Ada Gavrilovska Dejan Milojicic School of Computer Science Georgia Institute of Technology Atlanta USA Hewlett Packard Enterprise Hewlett Packard Labs Milpitas CA

ISBN: (数字)9798350355543

ISBN: (纸本)9798350355550

Containers have become an important component for scientific workflows, enhancing reproducibility, portability, and isolation when coupled with workflow management systems. However, integrating containers with these systems can be complex, potentially hindering wider adoption. Serverless platforms offer a solution by providing a layer of abstraction over container orchestrators, simplifying management while introducing event-driven capabilities. This paper presents a novel integration of serverless with workflow management systems to optimize scientific workflow execution. Our approach leverages serverless functions to dynamically provision containers for workflow tasks, resulting in up to 30% faster execution. We found that performance can be further improved by reusing containers between multiple different tasks that were provisioned by the serverless platform. These findings demonstrate the utility of combining specialized container orchestration with established workflow management to streamline scientific computing, improve resource utilization, and accelerate time-to-results. Serverless’ event-driven architecture enables efficient resource scaling, aligning with the dynamic nature of scientific workloads.

关键词： Hands Scientific computing high performance computing Serverless computing Manuals Containers Aerodynamics Reproducibility of results Wrapping Workflow management software

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PREFETCHX: Cross-Core Cache-Agnostic Prefetcher-based Side-Channel Attacks

PREFETCHX: Cross-Core Cache-Agnostic Prefetcher-based Side-C...

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IEEE symposium on high-performance computer architecture

作者： Yun Chen Ali Hajiabadi Lingfeng Pei Trevor E. Carlson School of Computing National University of Singapore

In this paper, we reveal the existence of a new class of prefetcher, the XPT prefetcher, in modern Intel processors which has never been officially detailed. It speculatively issues a load, bypassing last-level cache (LLC) lookups, when it predicts that a load request will result in an LLC miss. We demonstrate that XPT prefetcher is shared among different cores, which enables an attacker to build cross-core side-channel and covertchannel attacks. We propose PREFETCHX, a cross-core attack mechanism, to leak users’ sensitive data and activities. We empirically demonstrate that PREFETCHX can be used to extract private keys of real-world RSA applications. Furthermore, we show that PREFETCHX can enable side-channel attacks that can monitor keystrokes and network traffic patterns of users. Our two cross-core covert-channel attacks also see a low error rate and a 122KiB/s maximum channel capacity. Due to the cache-independent feature of PREFETCHX, current cache-based mitigations are not effective against our attacks. Overall, our work uncovers a significant vulnerability in the XPT prefetcher, which can be exploited to compromise the confidentiality of sensitive information in both cryptography and non-cryptography-related applications among processor cores.

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A Microservices architecture Toolkit for Interconnected Science Ecosystems 24

A Microservices Architecture Toolkit for Interconnected Scie...

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Proceedings of the SC '24 workshops of the international Conference on high performance computing, Network, Storage, and Analysis

作者： Michael J. Brim Lance Drane Marshall McDonnell Christian Engelmann Addi Malviya Thakur National Center for Computational Sciences Computer Science and Mathematics Division Oak Ridge National Laboratory Oak Ridge Tennessee U.S.A.

ISBN: (纸本)9798350355543

Microservices architecture is a promising approach for developing reusable scientific workflow capabilities for integrating diverse resources, such as experimental and observational instruments and advanced computational and data management systems, across many distributed organizations and facilities. In this paper, we describe how the INTERSECT Open architecture leverages federated systems of microservices to construct interconnected science ecosystems, review how the INTERSECT software development kit eases microservice capability development, and demonstrate the use of such capabilities for deploying an example multi-facility INTERSECT ecosystem.

关键词： Application programming interfaces

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Peachy Parallel Assignments (EduPar 2022) 36

Peachy Parallel Assignments (EduPar 2022)

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36th IEEE international Parallel and Distributed Processing symposium (IEEE IPDPS)

作者： Buecker, H. Martin Casanova, Henri da Silva, Rafael Ferreira Lasserre, Alice Luyen, Derrick Namyst, Raymond Schoder, Johannes Wacrenier, Pierre-Andre Bunde, David P. Friedrich Schiller Univ Jena Inst Comp Sci Jena Germany Univ Hawaii Informat & Comp Sci Honolulu HI 96822 USA Oak Ridge Natl Lab Natl Ctr Computat Sci Oak Ridge TN USA Univ Bordeaux Comp Sci Dept Inria Bordeaux Sud Ouest Talence France Knox Coll Comp Sci Dept Galesburg IL USA

ISBN: (纸本)9781665497473

The presentation of Peachy Parallel Assignments in several workshops on parallel and distributed computing education aims to promote the reuse of highquality assignments, both saving precious faculty time and improving the quality of course assignments. Presented assignments are selected competitively- they must have been successfully used in a real classroom, be easy for other instructors to adopt, and be "cool and inspirational" to encourage students to spend time on them and talk about them with others. Winning assignments are also archived on the Peachy Parallel Assignments website. In this installment of Peachy Parallel Assignments, we present three new assignments. The first assignment is to simulate an Abelian Sandpile, with grains of sand moving from tall piles to shorter ones. This is a discrete simulation that creates colorful and intricate images. The second assignment is a Big Data problem in which students use the MapReduce paradigm to recreate "Warming Stripes", a visualization of climate data that highlights climate change. The third assignment introduces climate-oriented optimization by asking students to schedule distributed workflows to minimize their carbon footprint.

关键词： Peachy Parallel Assignments Parallel computing education high-performance computing education Parallel programming Curriculum Development Abelian Sandpile Parallel Simulation MapReduce Big Data Warming Stripes Distributed Workflow Scheduling Carbon Footprint

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