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Access Patterns and Performance Behaviors of Multi-layer Supercomputer I/O Subsystems under Production Load 22

Access Patterns and Performance Behaviors of Multi-layer Sup...

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31st International Symposium on High-Performance Parallel and Distributed computing (HPDC)

作者： Bez, Jean Luca Karimi, Ahmad Maroof Paul, Arnab K. Xie, Bing Byna, Suren Carns, Philip Oral, Sarp Wang, Feiyi Hanley, Jesse Lawrence Berkeley Natl Lab Berkeley CA 94720 USA Oak Ridge Natl Lab Oak Ridge TN USA Birla Inst Technol Sci Pilani Rajasthan India Argonne Natl Lab Argonne IL USA BITS Pilani Pilani Goa India

ISBN: (纸本)9781450391993

Scientific computing workloads at HPC facilities have been shifting from traditional numerical simulations to AI/ML applications for training and inference while processing and producing ever-increasing amounts of scientific data. To address the growing need for increased storage capacity, lower access latency, and higher bandwidth, emerging technologies such as non-volatile memory are integrated into supercomputer I/O subsystems. With these emerging trends, we need a better understanding of the multilayer supercomputer I/O systems and ways to use these subsystems efficiently. In this work, we study the I/O access patterns and performance characteristics of two representative supercomputer I/O subsystems. Through an extensive analysis of year-long I/O logs on each system, we report new observations in I/O reads and writes, unbalanced use of storage system layers, and new trends in user behaviors at the HPC I/O middleware stack.

关键词： Access Patterns Parallel File systems In-System Storage High-Performance computing Production System

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proceedings of SC 2022: International Conference for High Performance computing, Networking, Storage and analysis

Proceedings of SC 2022: International Conference for High Pe...

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2022 International Conference for High Performance computing, Networking, Storage and analysis, SC 2022

ISBN: (纸本)9781665454445

The proceedings contain 87 papers. The topics discussed include: reshaping geostatistical modeling and prediction for extreme-scale environmental applications;pushing the frontier in the design of laser-based electron accelerators with groundbreaking mesh-refined particle-in-cell simulations on exascale-class supercomputers;extreme scale earthquake simulation with uncertainty quantification;exaflops biomedical knowledge graph analytics;scaling correlated fragment molecular orbital calculations on summit;image gradient decomposition for parallel and memory-efficient ptychographic reconstruction;building blocks for network-accelerated distributed file systems;combining hard and soft constraints in quantum constraint-satisfaction systems;large-scale simulation of quantum computational chemistry on a new Sunway supercomputer;charter: identifying the most-critical gate operations in quantum circuits via amplified gate reversibility;study of workload interference with intelligent routing on dragonfly;and symmetric block-cyclic distribution: fewer communications leads to faster dense Cholesky factorization.

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IHC 2022 - proceedings of the 21st Brazilian Symposium on Human Factors in computing systems

IHC 2022 - Proceedings of the 21st Brazilian Symposium on Hu...

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21st Brazilian Symposium on Human Factors in computing systems, IHC 2022

ISBN: (纸本)9781450395069

The proceedings contain 45 papers. The topics discussed include: a systematic mapping study on digital game adaptation dimensions;a systematic mapping study on usability and user experience evaluation of multi-touch systems;analysis of transcription tools for Brazilian Portuguese with focus on disfluency detection;analyzing structural similarity of user interface layouts of android apps using deep learning;applying the engagement by design methodology: perceptions and lessons learned;are user reviews useful for identifying accessibility issues that autistic users face? an exploratory study;assessment of visual aesthetics through human judgments: a systematic mapping;automated assessment of visual aesthetics of android user interfaces with deep learning;children’s participation in the design of digital artifacts in rural schools;and contextual exploration of mathematical formulae on the web for people with visual disabilities in Brazil with an open-source screen reader.

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A Multi-Bit Near-RRAM based computing Macro with Highly computing Parallelism for CNN Application

A Multi-Bit Near-RRAM based Computing Macro with Highly Comp...

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2024 Design, Automation and Test in Europe Conference and Exhibition, DATE 2024

作者： Lin, Kuan-Chih Zuo, Hao Wang, Hsiang-Yu Huang, Yuan-Ping Wu, Ci-Hao Guo, Yan-Cheng Jou, Shyh-Jye Hou, Tuo-Hung Chang, Tian-Sheuan Institute Of Electronics National Yang Ming Chiao Tung University Hsinchu Taiwan

ISBN: (纸本)9798350348590

Resistive random-access memory (RRAM) based compute-in-memory (CIM) is an emerging approach to address the demand for practical implementation of artificial intelligence (AI) on resource constrained edge devices by reducing the power-hungry data transfer between memory and processing unit. However, the state-of-the-art RRAM CIM designs fail to strike a balance between precision, energy efficiency, throughput, and latency. This work merges the techniques of CIM and compute-near-memory (CNM) to deliver high precision, high energy efficiency, high throughput, and low latency. In this paper, a 256Kb RRAM based CNM macro fabricated in TSMC 40 nm process is presented featuring: 1) opposite weight mapping with variation-robust SA to mitigate the impact of RRAM device variations on MAC (Multiply-Accumulate) results;2) switched-capacitor-based analog multiplication circuit to achieve highly parallel computing of 128 4-bit by 4-bit MAC result with low power consumption and high operation speed;and 3) joint optimization of hardware and software to compensate for the accuracy loss after considering the non-idealities of circuits. The macro achieves a low latency of 17ns and high energy efficiency of 71 TOPS/W for MAC operations with 4-bit input, 4-bit weight and 4-bit output precision. It is used to accelerate the convolution process in the Light-CSPDenseN et AI model, resulting in a high accuracy of 86.33% on Visual Wake Words dataset. © 2024 EDAA.

关键词： Low power electronics

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Machine learning model cards toward model-based system engineering analysis of resource-limited systems 32

Machine learning model cards toward model-based system engin...

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Conference on Signal Processing, Sensor/Information Fusion, and Target Recognition XXXII

作者： Booth, Thomas M. Ghosh, Sudipto USAF 309th SWEG Hill AFB UT 84056 USA Colorado State Univ Ft Collins CO USA

ISBN: (数字)9781510662117

ISBN: (纸本)9781510662100;9781510662117

Sensor fusion combines data from a suite of sensors into an integrated solution that represents the target environment more accurately than that produced by individual sensors. New developments in Machine Learning (ML) algorithms are leading to increased accuracy, precision, and reliability in sensor fusion performance. However, these increases are accompanied by increases in system costs. Aircraft sensor systems have limited computing, storage, and bandwidth resources, which must balance monetary, computational, and throughput costs, sensor fusion performance, aircraft safety, data security, robustness, and modularity system objectives while meeting strict timing requirements. Performing trade studies of these system objectives should come before incorporating new ML models into the sensor fusion software. A scalable and automated solution is needed to quickly analyze the effects on the system's objectives of providing additional resources to the new inference models. Given that model-based systems engineering (MBSE) is a focus of the majority of the aerospace industry for designing aircraft mission systems, it follows that leveraging these system models can provide scalability to the system analyses needed. This paper proposes adding empirically derived sensor fusion RNN performance and cost measurement data to machine-readable Model Cards. Furthermore, this paper proposes a scalable and automated sensor fusion system analysis process for ingesting SysML system model information and RNN Model Cards for system analyses. The value of this process is the integration of data analysis and system design that enables rapid enhancements of sensor system development.

关键词： MBSE SysML Machine Learning Model Card Sensor Fusion Resource datasheets factsheets

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Communication Isolation For Multi-Robot systems Using ROS2 25

Communication Isolation For Multi-Robot Systems Using ROS2

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40th Annual acm Symposium on Applied computing, SAC 2025

作者： Naury, Lucas Gouguet, Adam Lozenguez, Guillaume Fabresse, Luc IMT Nord-Europe Douai France

ISBN: (纸本)9798400706295

This article examines how to design communication isolation in a fleet of robots using the Robot Operating System (ROS 2). A qualitative analysis and comparison of several communication methods is provided, based on various criteria (isolation granularity, isolation strength, network usage, etc.). A specific scenario is implemented for each communication method to demonstrate their feasibility and highlight some of their limitations. Finally, experimental results both simulations and real robots compare five communication strategies, providing guidelines to help select the best method depending on the project's requirements. Copyright © 2025 held by the owner/author(s).

关键词： Multipurpose robots

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Memory Space Recycling 22

Memory Space Recycling

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2022 acm SIGMETRICS/IFIP PERFORMANCE Joint International Conference on measurement and Modeling of Computer systems, SIGMETRICS/PERFORMANCE 2022

作者： Ryoo, Jihyun Kandemir, Mahmut Taylan Karakoy, Mustafa The Pennsylvania State University State CollegePA United States TUBITAK-BILGEM Gebze Turkey

ISBN: (纸本)9781450391412

Many program codes from different application domains process very large amounts of data, making their data locality/cache memory behavior critical for high performance. Prior work has addressed the data locality optimization problem in the context of both single-core and multi-core systems. Another dimension of optimization, which can be as equally important/beneficial as improving data access pattern is to reduce the data volume (total number of addresses) accessed by the program code. In this work, we explore the idea of rewriting an application program code to reduce its memory space footprint. The main idea behind this approach is to reuse/recycle, for a given data element, a memory location that has originally been assigned to another data element, provided that the lifetimes of these two data elements do not overlap with each other. We present a detailed experimental evaluation of our proposed memory space recycling strategy. The experimental results show that our proposed approach brings, respectively, 33.2%, 48.6%, 46.5%, 31.8%, and 27.9% average improvements in these metrics, in the case of single-threaded applications. With the multi-threaded versions of the same applications, the achieved improvements are 39.5%, 55.5%, 53.4%, 26.2%, and 22.2%, in the same order. © 2022 Owner/Author.

关键词： multi-core processors compilers high performance computing memory systems workload characterization

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A Cross-Country analysis of GDPR Cookie Banners and Flexible Methods For Scraping Them 25

A Cross-Country Analysis of GDPR Cookie Banners and Flexible...

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2025 CHI Conference on Human Factors in computing systems, CHI 2025

作者： Nouwens, Midas Kristensen, Janus Bager Maalt, Kristjan Bagge, Rolf Digital Design and Information Studies Aarhus University Aarhus Denmark Centre for Advanced Visualisation and Interaction Aarhus University Aarhus Denmark Business Development and Technology Aarhus University Aarhus Denmark

ISBN: (纸本)9798400713941

Online tracking remains problematic, with compliance and ethical issues persisting despite regulatory efforts. Consent interfaces, the visible manifestation of this industry, have seen significant attention over the years. We present robust automated methods to study the presence, design, and third-party suppliers of consent interfaces at scale and the web service *** to do it with. We examine the top 10,000 websites across 31 countries under the ePrivacy Directive and GDPR (n=254.148). Our findings show that 67% of websites use consent interfaces, but only 15% are minimally compliant, mostly because they lack a reject option. Consent management platforms (CMPs) are powerful intermediaries in this space: 67% of interfaces are provided by CMPs, and three organisations hold 37% of the market. There is little evidence that regulators' guidance and fines have impacted compliance rates, but 18% of compliance variance is explained by CMPs. Researchers should take an infrastructural perspective on online tracking and study the factual control of intermediaries to identify effective leverage points. © 2025 Copyright held by the owner/author(s).

关键词： Cookie

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An Enterprise-Grade Open-Source Data Reduction Architecture for All-Flash Storage systems 22

An Enterprise-Grade Open-Source Data Reduction Architecture ...

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2022 acm SIGMETRICS/IFIP PERFORMANCE Joint International Conference on measurement and Modeling of Computer systems, SIGMETRICS/PERFORMANCE 2022

作者： Ajdari, Mohammadamin Raaf, Patrick Kishani, Mostafa Salkhordeh, Reza Asadi, Hossein Brinkmann, André Sharif University of Technology Tehran Iran Johannes Gutenberg University Mainz Germany

ISBN: (纸本)9781450391412

Data reduction technologies have proven their effectiveness to decrease the ever-growing demands on storage system capacities, but also introduce new complexity in the system I/O stack that can easily invalidate well-known best practices. In this paper, we conduct an extensive set of experiments on an enterprise all-flash storage (AFS) system equipped with an open-source data reduction module, i.e., RedHat VDO, and reveal novel observations on the performance gap between the state-of-the-art and the optimal AFS stack with integrated data reduction. We then offer cross-layer optimizations to enhance the performance of AFS, which range from deriving new optimal hardware RAID configurations up to modifications of the enterprise storage stack tailored to the major bottlenecks observed. By implementing all proposed optimizations in an enterprise AFS, we show up to 12.5x speedup over the baseline AFS with integrated data reduction, and up to 57x performance/cost improvement over an optimized AFS (with no data reduction) for 100% write, high-reduction workload scenarios. © 2022 Owner/Author.

关键词： solid-state drives deduplication compression raid all-flash storage systems performance evaluation

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The Dual Model for Everyday Stress Technology: Understanding the Lived Experience of Data-Driven Stress 25

The Dual Model for Everyday Stress Technology: Understanding...

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2025 CHI Conference on Human Factors in computing systems, CHI 2025

作者： Hoddø Bakås, Sigrid WoÅ°niak, Mikolaj P. Herstad, Jo WoÅ°niak, Pawel W. Niess, Jasmin University of Oslo Oslo Norway University of Oldenburg Oldenburg Germany TU Wien Vienna Austria

ISBN: (纸本)9798400713941

Technology plays a dual role in our daily lives, both contributing to heightened stress levels and offering potential solutions for stress management. However, the lived experience of stress in everyday contexts remains underexplored, leaving a critical gap in our understanding of how stress manifests and how technology can effectively support stress management. To address this, we conducted user interviews and expert interviews with specialists in psychology, health, and stress research, complemented by an autoethnographic study. Our findings show the complexity of stress as both a subjective experience and a response shaped by socio-technical environments, leading to the construction of the Dual Model for Everyday Stress Technology. This model highlights the paradoxical nature of stress and its management in technology-mediated settings. We identify key directions for future stress-management technology design and research, with implications for creating meaningful, human-centred technologies for managing stress in everyday life. © 2025 Copyright held by the owner/author(s).

关键词： Stress analysis

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