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2022 Platform for Advanced Scientific computing Conference, PASC 2022

作者： Satheesan, Sandeep Puthanveetil Bhavya Davies, Adam Craig, Alan B. Zhang, Yu Zhai, ChengXiang University of Illinois at Urbana-Champaign UrbanaIL United States Extreme Science and Engineering Discovery Environment Discovery Environment United States California State University Fresno FresnoCA United States

ISBN: (纸本)9781450394109

The availability and generation of digitized newspaper collections have provided researchers in several domains with a powerful tool to advance their research. More specifically, digitized historical newspapers give us a magnifying glass into the past. In this paper, we propose a scalable and customizable big data analysis system that enables researchers to study complex questions about our society as depicted in news media for the past few centuries by applying cutting-edge text analysis tools to large historical newspaper collections. We discuss our experience with building a preliminary version of such a system, including how we have addressed the following challenges: processing millions of digitized newspaper pages from various publications worldwide, which amount to hundreds of terabytes of data;applying article segmentation and Optical Character Recognition (OCR) to historical newspapers, which vary between and within publications over time;retrieving relevant information to answer research questions from such data collections by applying human-in-the-loop machine learning;and enabling users to analyze topic evolution and semantic dynamics with multiple compatible analysis operators. We also present some preliminary results of using the proposed system to study the social construction of juvenile delinquency in the United States and discuss important remaining challenges to be tackled in the future. © 2022 acm.

关键词： Big data

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BottleMod: Modeling Data Flows and Tasks for Fast Bottleneck analysis 25

BottleMod: Modeling Data Flows and Tasks for Fast Bottleneck...

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2025 International Conference on Performance Engineering-ICPE-Annual

作者： Loesser, Ansgar Witzke, Joel Schintke, Florian Scheuermann, Bjorn Tech Univ Darmstadt Darmstadt Germany Zuse Inst Berlin Berlin Germany

ISBN: (纸本)9798400710735

In recent years, scientific workflows have become increasingly popular. However, their tasks are often seen as black boxes, making it difficult to optimize them or identify bottlenecks due to the complex relationships between tasks. Several factors impact task progress, including input data availability, computing power, data transfer speed and network connectivity. During task execution, resource requirements may change significantly. We propose a new method to model task requirements over their lifetime. Using these models, we predict resource consumption over time and execution duration based on a given allocation strategy with low overhead. This method enables computationally simple and fast performance predictions, including bottleneck analysis during workflow runtime. We derive a piecewise-defined bottleneck function from the discrete intersections of the task models' limiting functions. This allows us to predict potential performance gains when mitigating bottlenecks and aids in better resource allocation and workflow execution.

关键词： model scientific workflows data analysis workflows bottleneck analysis

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Scaling Superconducting Quantum Computers with Chiplet Architectures 55

Scaling Superconducting Quantum Computers with Chiplet Archi...

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55th Annual IEEE/acm International Symposium on Microarchitecture (MICRO)

作者： Smith, Kaitlin N. Ravi, Gokul Subramanian Baker, Jonathan M. Chong, Frederic T. Univ Chicago Chicago IL 60637 USA

ISBN: (数字)9781665462723

ISBN: (纸本)9781665462723

Fixed-frequency transmon quantum computers (QCs) have advanced in coherence times, addressability, and gate fidelities. Unfortunately, these devices are restricted by the number of on-chip qubits, capping processing power and slowing progress toward fault-tolerance. Although emerging transmon devices feature over 100 qubits, building QCs large enough for meaningful demonstrations of quantum advantage requires overcoming many design challenges. For example, today's transmon qubits suffer from significant variation due to limited precision in fabrication. As a result, barring significant improvements in current fabrication techniques, scaling QCs by building ever larger individual chips with more qubits is hampered by device variation. Severe device variation that degrades QC performance is referred to as a defect. Here, we focus on a specific defect known as a frequency collision. When transmon frequencies collide, their difference falls within a range that limits two-qubit gate fidelity. Frequency collisions occur with greater probability on larger QCs, causing collision-free yields to decline as the number of on-chip qubits increases. As a solution, we propose exploiting the higher yields associated with smaller QCs by integrating quantum chiplets within quantum multi-chip modules (MCMs). Yield, gate performance, and application-based analysis show the feasibility of QC scaling through modularity. Our results demonstrate that chiplet architectures, relative to monolithic designs, benefit from average yield improvements ranging from 9.6 - 92.6 x for less than or similar to 500 qubit machines. In addition, our simulations explore the design space of chiplet systems and discover configurations that demonstrate average two-qubit gate infidelity reductions that are at best 0.815 x their monolithic counterpart. Finally, we observe that carefully-selected modular systems achieve fidelity improvements on a range of benchmark circuits.

关键词： Quantum computing quantum architecture superconducting quantum computers

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Understanding Data Movement in AMD Multi-GPU systems with Infinity Fabric 24

Understanding Data Movement in AMD Multi-GPU Systems with In...

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proceedings of the SC '24 Workshops of the International Conference on High Performance computing, Network, Storage, and analysis

作者： Gabin Schieffer Ruimin Shi Stefano Markidis Andreas Herten Jennifer Faj Ivy Peng KTH Royal Institute of Technology Stockholm Sweden Jülich Supercomputing Centre Jülich Germany

ISBN: (纸本)9798350355543

Modern GPU systems are constantly evolving to meet the needs of computing-intensive applications in scientific and machine learning domains. However, there is typically a gap between the hardware capacity and the achievable application performance. This work aims to provide a better understanding of the Infinity Fabric interconnects on AMD GPUs and CPUs. We propose a test and evaluation methodology for characterizing the performance of data movements on multi-GPU systems, stressing different communication options on AMD MI250X GPUs, including point-to-point and collective communication, and memory allocation strategies between GPUs, as well as the host CPU. In a single-node setup with four GPUs, we show that direct peer-to-peer memory accesses between GPUs and utilization of the RCCL library outperform MPI-based solutions in terms of memory/communication latency and bandwidth. Our test and evaluation method serves as a base for validating memory and communication strategies on a system and improving applications on AMD multi-GPU computing systems.

关键词： AMD MI250X GPU

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Investigating Human Scale Spatial Experience

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proceedings of the acm on Human-Computer Interaction 2021年第ISS期5卷 1–18页

作者： Paananen, Ville Oppenlaender, Jonas Goncalves, Jorge Hettiachchi, Danula Hosio, Simo Center for Ubiquitous Computing University of Oulu Oulu Finland School of Computing and Information Systems University of Melbourne Melbourne Australia

Spatial experience, or how humans experience a given space, has been a pivotal topic especially in urban-scale environments. On the human scale, HCI researchers have mostly investigated personal meanings or aesthetic and embodied experiences. In this paper, we investigate the human scale as an ensemble of individual spatial features. Through large-scale online questionnaires we first collected a rich set of spatial features that people generally use to characterize their surroundings. Second, we conducted a set of field interviews to develop a more nuanced understanding of the feature identified as most important: perceived safety. Our combined quantitative and qualitative analysis contributes to spatial understanding as a form of context information and presents a timely investigation into the perceived safety of human scale spaces. By connecting our results to the broader scientific literature, we contribute to the field of HCI spatial understanding. © 2021 acm.

关键词： Surveys

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Performance Evaluation of Blockchain systems: Parameters, Criteria and Modeling Techniques 17

Performance Evaluation of Blockchain Systems: Parameters, Cr...

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17th IEEE/acm International Conference on Utility and Cloud computing, UCC 2024

作者： Ajwalia, Madhav Shah, Parth Gujarat Changa India

ISBN: (纸本)9798350367201

Blockchain technology has emerged as a transformative solution for decentralized applications, significantly affecting various sectors. Despite its potential, evaluating blockchain performance remains a complex challenge due to its multifaceted nature. This paper overviews important performance parameters like throughput, latency, energy efficiency or resource consumption, scalability and security. After studying different performance parameters and base in weighted importance, these evaluation parameters are grouped by category. This study explores evaluation criteria, and various modelling techniques (Benchmarking, Simulation, Empirical analysis, and Analytical Modeling) used to analyses blockchain performance to discuss their effectiveness in capturing the intricacies of blockchain operations. The goal is to provide a comprehensive study for evaluating blockchain systems, suggest a comprehensive framework and future research in this domain. © 2024 IEEE.

关键词： Blockchain Energy Efficiency Latency Modeling Techniques Performance Evaluation Scalability Security Throughput

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Understanding "Dark" Design Roles in computing Education 2021

Understanding "Dark" Design Roles in Computing Education

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17th Annual acm Conference on International computing Education Research (ICER)

作者： Gray, Colin M. Chivukula, Shruthi Sai Melkey, Kassandra Manocha, Rhea Purdue Univ W Lafayette IN 47907 USA

ISBN: (纸本)9781450383264

In conjunction with the increasing ubiquity of technology, computing educators have identified the need for pedagogical engagement with ethical awareness and moral reasoning. Typical approaches to incorporating ethics in computing curricula have focused primarily on abstract methods, principles, or paradigms of ethical reasoning, with relatively little focus on examining and developing students' pragmatic awareness of ethics as grounded in their everyday work practices. In this paper, we identify and describe computing students' negotiation of values as they engage in authentic design problems through a lab protocol study. We collected data from four groups of three students each, with each group including participants from either undergraduate User Experience Design students, Industrial Engineering students, or a mix of both. We used a thematic analysis approach to identify the roles that students took on to address the design prompt. Through our analysis, we found that the students took on a variety of "dark" roles that resulted in manipulation of the user and prioritization of stakeholder needs over user needs, with a focus either on building solutions or building rationale for design decisions. We found these roles to actively propagate through design discourses, impacting other designers in ways that frequently reinforced unethical decision making. Even when students were aware of ethical concerns based on their educational training, this awareness did not consistently result in ethicallysound decisions. These findings indicate the need for additional ethical supports to inform everyday computing practice, including means of actively identifying and balancing negative societal impacts of design decisions. The roles we have identified may productively support the development of pragmatically-focused ethical training in computing education, while adding more precision to future analysis of computing student discourses and outputs.

关键词： Ethics values dark patterns ethics education lab protocol

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Computer systems and Technologies - 23rd International Conference, CompSysTech 2022 - proceedings

Computer Systems and Technologies - 23rd International Confe...

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23rd International Conference on Computer systems and Technologies, CompSysTech 2022

ISBN: (纸本)9781450396448

The proceedings contain 31 papers. The topics discussed include: modelling and testing multi-qubit universal control gate developed for quantum computing systems;device model and communication protocol with low overhead for sensors and actuators in smart buildings;real-time trajectory replanning for dynamic obstacles avoidance for robotics manipulators;security aspects of behavioral biometrics for strong user authentication;fractal time series analysis by using entropy and hurst exponent;linear images coprocessing in environmental monitoring;a novel photoplethysmographic noise removal method via wavelet transform to effective preprocessing;how university students in ‘informatics and computer sciences’ would like to use video games for learning;extrapolating the digital readiness – are Turkmen undergraduate students competent for online learning?;and troubleshooting combinational logic circuits web-based learning system for improving students engagement.

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Invited: Algorithms and Architectures for Accelerating Long Read Sequence analysis 23

Invited: Algorithms and Architectures for Accelerating Long ...

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proceedings of the 60th Annual acm/IEEE Design Automation Conference

作者： Hasindu Gamaarachchi Kisaru Liyanage Sri Parameswaran School of Computer Science & Engineering UNSW Sydney and Kinghorn Centre for Clinical Genomics Garvan Institute of Medical Research School of Electrical and Information Engineering University of Sydney.

ISBN: (纸本)9798350323481

Genome sequencing is continuing to revolutionize the medical, forensics, agricultural, and biosecurity fields. The enormous amounts of data from modern sequencing technology, require significant time and cost to obtain accurate results using general-purpose computing resources. The emergence of third-generation sequencers called nanopore sequencers offers small, cheap, and portable genome sequencing capabilities. However, the bottleneck during computational analysis limits scalability and portability. This paper introduces the necessity for one, optimization of existing algorithms; two, efficient utilization of existing heterogeneous systems; and three, novel algorithms and domain-specific architectures for rapid in situ analysis of third-generation sequencing data. State-of-the-art examples are described and future challenges are outlined.

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Machine Learning Techniques for Diabetes Prediction: A Comparative analysis

Machine Learning Techniques for Diabetes Prediction: A Compa...

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2023 International Conference on Sustainable computing and Smart systems, ICSCSS 2023

作者： Mythili, J. Surendhar, T. Suryaprakash, P. Suresh Kumar, K. Faculty of Computer Science and Engineering K S Rangasamy College of Technology Department of Computer Science and Engineering Tiruchengode India Computer Science and Engineering K S Rangasamy College of Technology Department of Computer Science and Engineering Tiruchengode India

ISBN: (纸本)9798350333602

As the prevalence of diabetes mellitus rises, more families are being impacted. Most diabetics don't know much about their health situation or the risks they face before getting a diagnosis. A unique data mining-based method was suggested for the prediction of type 2 diabetes mellitus (T2DM) in this study. The accuracy and robustness of the prediction model are the primary priorities, ensuring flexibility so that it may be used to other datasets. The model is made up of two parts: the enhanced Logistic Regression with Multilayer Perception (LRMLP) and Naïve Bayes (NB) method with a set of preprocessing techniques. To compare the findings with those of other studies, the Diabetes Dataset for Pima Indians was used with the Environment for Knowledge analysis toolkit. According to the findings, the model's prediction accuracy is higher than that of earlier research. Additionally, this approach guarantees that the dataset quality is enough. The system was applied to two more diabetes datasets in order to assess its effectiveness further. Both research findings show strong performance. The model is shown to be helpful for managing diabetic health in a realistic manner as a result. For experimental analysis, data from the University of California, Irvine's (UCI) machine learning repository's Pima Indian Diabetes Database (PIDD) is used. These classification algorithms' performance is evaluated using a variety of statistical metrics, including sensitivity (recall), precision, F-score, and accuracy. The measurement of correctly and erroneously classified cases is called accuracy. According to the testing findings, LR-MLP outscored other classification algorithms and provides the maximum accuracy of 96.3%. © 2023 IEEE.

关键词： Forecasting

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