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2024 IEEE High Performance Extreme computing Conference, HPEC 2024

作者： Valero-Lara, Pedro Godoy, William F. Teranishi, Keita Vetter, Jeffrey S. Advanced Computing Systems Research Section Oak Ridge National Laboratory Oak RidgeTN United States

ISBN: (纸本)9798350387131

In this work, we present ***, a new feature of Julia for ACCelerators (JACC), which is the performanceportable and metaprogramming model of the just-in-time and LLVM-based Julia language. This new feature allows JACC applications to leverage the high-performance computing (HPC) capabilities of high-bandwidth, on-chip GPU memory. Historically, exploiting high-bandwidth, shared-memory GPUs has not been a priority for high-level programming solutions. *** covers that gap for the first time, thereby providing a highlevel, portable, and easy-to-use solution for programmers to exploit this memory and supporting all current major accelerator architectures. Well-known HPC and AI workloads, such as multi/hyperspectral imaging and AI convolutions, have been used to evaluate *** on two exascale GPU architectures hosted by some of the most powerful US Department of Energy supercomputers: Perlmutter (NVIDIA A100) and Frontier (AMD MI250X). The performance evaluation reports speedup of up to 3.5 × by adding only one line of code to the base codes, thus providing important accelerators in a simple, portable, and transparent way and elevating the programming productivity and performance-portability capabilities for Julia/JACC HPC, AI, and scientific applications. © 2024 IEEE.

关键词： Memory architecture

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***: Leveraging HPC Metaprogramming and Performance Portability for Computations That Use Shared Memory GPUs

***: Leveraging HPC Metaprogramming and Performance Portabil...

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IEEE Conference on High Performance Extreme computing (HPEC)

作者： Pedro Valero-Lara William F. Godoy Keita Teranishi Jeffrey S. Vetter Advanced Computing Systems Research Section Oak Ridge National Laboratory Oak Ridge Tennessee USA

ISBN: (数字)9798350387131

ISBN: (纸本)9798350387148

In this work, we present ***, a new feature of Julia for ACCelerators (JACC), which is the performanceportable and metaprogramming model of the just-in-time and LLVM-based Julia language. This new feature allows JACC applications to leverage the high-performance computing (HPC) capabilities of high-bandwidth, on-chip GPU memory. Historically, exploiting high-bandwidth, shared-memory GPUs has not been a priority for high-level programming solutions. *** covers that gap for the first time, thereby providing a highlevel, portable, and easy-to-use solution for programmers to exploit this memory and supporting all current major accelerator architectures. Well-known HPC and AI workloads, such as multi/hyperspectral imaging and AI convolutions, have been used to evaluate *** on two exascale GPU architectures hosted by some of the most powerful US Department of Energy supercomputers: Perlmutter (NVIDIA A100) and Frontier (AMD MI250X). The performance evaluation reports speedup of up to $3.5 \times$ by adding only one line of code to the base codes, thus providing important accelerators in a simple, portable, and transparent way and elevating the programming productivity and performance-portability capabilities for Julia/JACC HPC, AI, and scientific applications.

关键词： Productivity Convolutional codes Performance evaluation US Department of Energy Computational modeling Graphics processing units Programming Supercomputers System-on-chip Artificial intelligence

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Coexistent quantum channel characterization using quantum process tomography with spectrally resolved detection 3

Coexistent quantum channel characterization using quantum pr...

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Quantum computing, Communication, and Simulation III 2023

作者： Chapman, Joseph C. Lukens, Joseph M. Alshowkan, Muneer Rao, Nageswara S.V. Kirby, Brian T. Peters, Nicholas A. Quantum Information Science Section Oak Ridge National Laboratory Oak RidgeTN37831 United States Research Technology Office Arizona State University TempeAZ85287 United States Advanced Computing Methods for Engineered Systems Section Oak Ridge National Laboratory Oak RidgeTN37831 United States Tulane University New OrleansLA70118 United States DEVCOM Army Research Laboratory AdelphiMD20783 United States

ISBN: (纸本)9781510659971

The coexistence of classical and quantum signals over the same optical fiber is critical for quantum networks operating within the existing communications infrastructure. Here, we characterize the quantum channel that results from distributing approximate single-photon polarization-encoded qubits simultaneously with classical light of varying intensities through a 25 km fiber-optic channel. We use spectrally resolved quantum process tomography with a newly developed Bayesian reconstruction method to estimate the quantum channel from experimental data, both with and without classical noise. Furthermore, we show that the coexistent fiber-based quantum channel has high process fidelity with an ideal depolarizing channel if the noise is dominated by Raman scattering. These results aid future development of quantum repeater designs and quantum error-correcting codes which benefit from realistic channel error models. © 2023 SPIE.

关键词： Tomography

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A Hierarchical Task Scheduler for Heterogeneous computing 36th

A Hierarchical Task Scheduler for Heterogeneous Computing

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36th International Conference on High Performance computing, ISC High Performance 2021

作者： Miniskar, Narasinga Rao Liu, Frank Young, Aaron R. Chakraborty, Dwaipayan Vetter, Jeffrey S. Advanced Computing Systems Research Section Oak Ridge National Laboratory Oak RidgeTN37831 United States Rowan University 201 Mullica Hill Road GlassboroNJ08028 United States

ISBN: (纸本)9783030787127

Heterogeneous computing is one of the future directions of HPC. Task scheduling in heterogeneous computing must balance the challenge of optimizing the application performance and the need for an intuitive interface with the programming run-time to maintain programming portability. The challenge is further compounded by the varying data communication time between tasks. This paper proposes RANGER, a hardware-assisted task-scheduling framework. By integrating RISC-V cores with accelerators, the RANGER scheduling framework divides scheduling into global and local levels. At the local level, RANGER further partitions each task into fine-grained subtasks to reduce the overall makespan. At the global level, RANGER maintains the coarse granularity of the task specification, thereby maintaining programming portability. The extensive experimental results demonstrate that RANGER achieves a 12.7 × performance improvement on average, while only requires 2.7 % of area overhead. © 2021, UT-Battelle, LLC.

关键词： Scheduling

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Coexistent Quantum Channel Characterization Using Spectrally Resolved Bayesian Quantum Process Tomography

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Physical Review Applied 2023年第4期19卷 044026-044026页

作者： Joseph C. Chapman Joseph M. Lukens Muneer Alshowkan Nageswara Rao Brian T. Kirby Nicholas A. Peters Quantum Information Science Section Oak Ridge National Laboratory Oak Ridge Tennessee 37831 USA Research Technology Office Arizona State University Tempe Arizona 85287 USA Advanced Computing Methods for Engineered Systems Section Oak Ridge National Laboratory Oak Ridge Tennessee 37831 USA Tulane University New Orleans Louisiana 70118 USA DEVCOM Army Research Laboratory Adelphi Maryland 20783 USA

The coexistence of quantum and classical signals over the same optical fiber with minimal degradation of the transmitted quantum information is critical for operating large-scale quantum networks over the existing communications infrastructure. Here, we systematically characterize the quantum channel that results from simultaneously distributing approximate single-photon polarization-encoded qubits and classical light of varying intensities through fiber-optic channels of up to 15 km. Using spectrally resolved quantum process tomography with a Bayesian reconstruction method that we develop, we estimate the full quantum channel from experimental photon counting data, both with and without classical background. Furthermore, although we find the exact channel description to be a weak function of the pump polarization, we nevertheless show that the coexistent fiber-based quantum channel has high process fidelity with an ideal depolarizing channel when the noise is dominated by Raman scattering. These results provide a basis for the future development of quantum repeater designs and quantum error-correcting codes for real-world channels and inform models used in the analysis and simulation of quantum networks.

关键词： Engineering Quantum channels Quantum communication Quantum error correction Quantum networks Quantum repeaters Quantum tomography Communication networks

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Coexistent quantum channel characterization using spectrally resolved Bayesian quantum process tomography

arXiv

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arXiv 2022年

作者： Chapman, Joseph C. Lukens, Joseph M. Alshowkan, Muneer Rao, Nageswara Kirby, Brian T. Peters, Nicholas A. Quantum Information Science Section Oak Ridge National Laboratory Oak RidgeTN37831 United States Research Technology Office Arizona State University TempeAZ85287 United States Advanced Computing Methods for Engineered Systems Section Oak Ridge National Laboratory Oak RidgeTN37831 United States Tulane University New OrleansLA70118 United States DEVCOM Army Research Laboratory AdelphiMD20783 United States

The coexistence of quantum and classical signals over the same optical fiber with minimal degradation of the transmitted quantum information is critical for operating large-scale quantum networks over the existing communications infrastructure. Here, we systematically characterize the quantum channel that results from simultaneously distributing approximate single-photon polarization-encoded qubits and classical light of varying intensities through fiber-optic channels of up to 15 km. Using spectrally resolved quantum process tomography with a Bayesian reconstruction method we developed, we estimate the full quantum channel from experimental photon counting data, both with and without classical background. Furthermore, although we find the exact channel description to be a weak function of the pump polarization, we nevertheless show that the coexistent fiber-based quantum channel has high process fidelity with an ideal depolarizing channel when the noise is dominated by Raman scattering. These results provide a basis for the future development of quantum repeater designs and quantum error correcting codes for real-world channels and inform models used in the analysis and simulation of quantum networks. Copyright © 2022, The Authors. All rights reserved.

关键词： Tomography

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High fusion computers: The IoTs, edges, data centers, and humans-in-the-loop as a computer

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BenchCouncil Transactions on Benchmarks, Standards and Evaluations 2022年第3期2卷 100075-100075页

作者： Gao, Wanling Wang, Lei Chen, Mingyu Xiong, Jin Luo, Chunjie Zhang, Wenli Huang, Yunyou Li, Weiping Kang, Guoxin Zheng, Chen Xie, Biwei Dai, Shaopeng He, Qian Ye, Hainan Bao, Yungang Zhan, Jianfeng State Key Lab of Processors and Research Center for Advanced Computer Systems Institute of Computing Technology Chinese Academy of Sciences No. 6 Kexueyuan South Road Haidian District Beijing 100190 China Yuquan Road Shijingshan District Beijing 100049 China Guangxi Normal University No. 15 Yucai Road Qixing District Guangxi Guilin541010 China Civil Aviation Flight University of China No. 46 Section 4 Nanchang Road Sichuan Guanghan618307 China Institute of Software Chinese Academy of Sciences No. 4 South 4th Street Beijing Zhongguancun100190 China Beijing Institute of Open Source Chip No. 7 Caoqiao Northwest Corner of Haidian Bridge Haidian District Beijing 100080 China

Emerging and future applications rely heavily upon systems consisting of Internet of Things (IoT), edges, data centers, and humans-in-the-loop. Significantly different from warehouse-scale computers that serve independent concurrent user requests, this new class of computer systems directly interacts with the physical world, considering humans an essential part and performing safety-critical and mission-critical operations;their computations have intertwined dependencies between not only adjacent execution loops but also actions or decisions triggered by IoTs, edge, datacenters, or humans-in-the-loop;the systems must first satisfy the accuracy metric in predicting, interpreting, or taking action before meeting the performance goal under different cases. This article argues we need a paradigm shift to reconstruct the IoTs, edges, data centers, and humans-in-the-loop as a computer rather than a distributed system. We coin a new term, high fusion computers (HFCs), to describe this class of systems. The fusion in the term has two implications: fusing IoTs, edges, data centers, and humans-in-the-loop as a computer, fusing the physical and digital worlds through HFC systems. HFC is a pivotal case of the open-source computer systems initiative. We laid out the challenges, plan, and call for uniting our community's wisdom and actions to address the HFC challenges. Everything, including the source code, will be publicly available from the project homepage: https://***/HFC/. © 2022 The Authors

关键词： Internet of things

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High Fusion Computers: The IoTs, Edges, Data Centers, and Humans-in-the-loop as a Computer

arXiv

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arXiv 2022年

作者： Gao, Wanling Wang, Lei Chen, Mingyu Xiong, Jin Luo, Chunjie Zhang, Wenli Huang, Yunyou Li, Weiping Kang, Guoxin Zheng, Chen Xie, Biwei Dai, Shaopeng He, Qian Ye, Hainan Bao, Yungang Zhan, Jianfeng State Key Lab of Processors Research Center for Advanced Computer Systems Institute of Computing Technology Chinese Academy of Sciences No. 6 Kexueyuan South Road Haidian District Beijing100190 China Yuquan Road Shijingshan District Beijing100049 China Guangxi Normal University No. 15 Yucai Road Qixing District Guangxi Guilin541010 China Civil Aviation Flight University of China No. 46 Section 4 Nanchang Road Sichuan Guanghan618307 China Institute of Software Chinese Academy of Sciences No. 4 South 4th Street Zhongguancun Beijing100190 China Beijing Institute of Open Source Chip No. 7 Caoqiao northwest corner of Haidian Bridge Haidian District Beijing100080 China

Emerging and future applications rely heavily upon systems consisting of Internet of Things (IoT), edges, data centers, and humans-in-the-loop. Significantly different from warehouse-scale computers that serve independent concurrent user requests, this new class of computer systems directly interacts with the physical world, considering humans an essential part and performing safety-critical and mission-critical operations;their computations have intertwined dependencies between not only adjacent execution loops but also actions or decisions triggered by IoTs, edge, datacenters, or humans-in-the-loop;the systems must first satisfy the accuracy metric in predicting, interpreting, or taking action before meeting the performance goal under different cases. This article argues we need a paradigm shift to reconstruct the IoTs, edges, data centers, and humans-in-the-loop as a computer rather than a distributed system. We coin a new term, high fusion computers (HFCs), to describe this class of systems. The fusion in the term has two implications: fusing IoTs, edges, data centers, and humans-in-the-loop as a computer, fusing the physical and digital worlds through HFC systems. HFC is a pivotal case of the open-source computer systems initiative. We laid out the challenges, plan, and call for uniting our community’s wisdom and actions to address the HFC challenges. Everything, including the source code, will be publicly available from the project homepage: https://***/HFC/. © 2022, CC BY-NC-ND.

关键词： Internet of things

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Assessing Trustworthy AI in Times of COVID-19: Deep Learning for Predicting a Multiregional Score Conveying the Degree of Lung Compromise in COVID-19 Patients

IEEE Transactions on Technology and Society

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IEEE Transactions on Technology and Society 2022年第4期3卷 272-289页

作者： Allahabadi, Himanshi Amann, Julia Balot, Isabelle Beretta, Andrea Binkley, Charles Bozenhard, Jonas Bruneault, Frederick Brusseau, James Candemir, Sema Cappellini, Luca Alessandro Chakraborty, Subrata Cherciu, Nicoleta Cociancig, Christina Coffee, Megan Ek, Irene Espinosa-Leal, Leonardo Farina, Davide Fieux-Castagnet, Genevieve Frauenfelder, Thomas Gallucci, Alessio Giuliani, Guya Golda, Adam Van Halem, Irmhild Hildt, Elisabeth Holm, Sune Kararigas, Georgios Krier, Sebastien A. Kuhne, Ulrich Lizzi, Francesca Madai, Vince I. Markus, Aniek F. Masis, Serg Mathez, Emilie Wiinblad Mureddu, Francesco Neri, Emanuele Osika, Walter Ozols, Matiss Panigutti, Cecilia Parent, Brendan Pratesi, Francesca Moreno-Sanchez, Pedro A. Sartor, Giovanni Savardi, Mattia Signoroni, Alberto Sormunen, Hanna-Maria Spezzatti, Andy Srivastava, Adarsh Stephansen, Annette F. Theng, Lau Bee Tithi, Jesmin Jahan Tuominen, Jarno Umbrello, Steven Vaccher, Filippo Vetter, Dennis Westerlund, Magnus Wurth, Renee Zicari, Roberto V. Ey Netherlands Enterprise Intelligence Department Amsterdam1083 HP Netherlands Eth Zurich Health Ethics and Policy Lab Department of Health Sciences and Technology Zürich8092 Switzerland Center for Diplomatic and Strategic Studies Postgraduate Studies in Diplomacy and International Relations Paris75015 France Pisa56124 Italy Hackensack Meridian Health Bioethics Center EdisonNJ08820 United States University of Oxford Faculty of Philosophy OxfordOX2 6GG United Kingdom Collège André- Laurendeau Philosophie Department MontrealQCH8N 2J4 Canada Université du Québec À Montréal École des Médias MontrealQCH2L 2C4 Canada Pace University Philosophy Department New YorkNY10038 United States The Ohio State University Wexner Medical Center Department of Radiology ColumbusOH43210 United States Humanitas Research Hospital Department of Radiology Milan20089 Italy Humanitas University Department of Biomedical Sciences Milan20089 Italy University of New England Faculty of Science Agriculture Business and Law ArmidaleNSW2351 Australia University of Technology Sydney Faculty of Engineering and Information Technology SydneyNSW2007 Australia Scuola Superiore Sant'Anna European Centre of Excellence on the Regulation of Robotics and Ai Pisa56127 Italy University of Bremen Group of Computer Architecture Bremen28359 Germany New York University Grossman School of Medicine Division of Infectious Diseases and Immunology Department of Medicine New YorkNY10016 United States Digital Institute Ai Research Section Stockholm16731 Sweden Arcada University of Applied Sciences Department of Business Management and Analytics Helsinki00550 Finland University of Brescia Radiological Sciences and Public Health Department of Medical and Surgical Specialties Brescia25121 Italy Sncf Reseau Sa Ethique Groupe La Plaine93418 France Institute of Diagnostic and Interventional Radiology University Hospital Zurich Zürich8091 Switzerland Eindhoven University of Tech

This article's main contributions are twofold: 1) to demonstrate how to apply the general European Union's High-Level Expert Group's (EU HLEG) guidelines for trustworthy AI in practice for the domain of healthcare and 2) to investigate the research question of what does 'trustworthy AI' mean at the time of the COVID-19 pandemic. To this end, we present the results of a post-hoc self-assessment to evaluate the trustworthiness of an AI system for predicting a multiregional score conveying the degree of lung compromise in COVID-19 patients, developed and verified by an interdisciplinary team with members from academia, public hospitals, and industry in time of pandemic. The AI system aims to help radiologists to estimate and communicate the severity of damage in a patient's lung from Chest X-rays. It has been experimentally deployed in the radiology department of the ASST Spedali Civili clinic in Brescia, Italy, since December 2020 during pandemic time. The methodology we have applied for our post-hoc assessment, called Z-Inspection®, uses sociotechnical scenarios to identify ethical, technical, and domain-specific issues in the use of the AI system in the context of the pandemic. © 2020 IEEE.

关键词： COVID-19

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The 2022 report of the Lancet Countdown on health and climate change: health at the mercy of fossil fuels (vol 400, pg 1619, 2022)

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LANCET 2022年第10365期400卷 1766-1766页

作者： Romanello, M. Di Napoli, C. Drummond, P. Institute for Global Health University College London London UK School of Agriculture Policy and Development University of Reading Reading UK Institute for Sustainable Resources University College London London UK Department of Global Health Centre for Health and the Global Environment University of Washington Seattle WA USA UCL Energy Institute University College London London UK Department of Health Sciences University of York York UK Department of Meteorology University of Reading Reading UK Institute for Risk and Disaster Reduction University College London London UK School of Earth and Environment University of Leeds Leeds UK Centre on Climate Change and Planetary Health London School of Hygiene & Tropical Medicine London UK School of Population Health University of Melbourne Melbourne VIC Australia Department of Earth System Science Tsinghua University Beijing China Mercator Research Institute on Global Commons and Climate Change Berlin Germany Department of Environment Climate Change and Health World Health Organization Geneva Switzerland Institute of Environmental Sciences University of Geneva Geneva Switzerland Cardiovascular Epidemiology Unit Department of Public Health & Primary Care University of Cambridge Cambridge UK School of Government University of Birmingham Birmingham UK Economic Analysis of Climate Impacts and Policy Division Centro Euro-Mediterraneo sui Cambiamenti Climatici Venice Italy Institute for Environmental Design and Engineering University College London London UK Natural Resources Institute University of Greenwich London UK Department of Environmental Health Sciences and Yale Center on Climate Change and Health Yale University New Haven CT USA Department of Civil and Environmental Engineering Northeastern University Boston MA USA Department of Fish and Wildlife Conservation Virginia Polytechnic Institute and State University Blacksburg VA USA Department of Geography University College London London UK NU

With advancements in the science of detection and attribution studies, the influence of climate change over many events has now been quantified. Because of the rapidly increasing temperatures, vulnerable populations (adults older than 65 years, and children younger than one year of age) were exposed to 3·7 billion more heatwave days in 2021 than annually in 1986–2005 (indicator 1.1.2), and heat-related deaths increased by 68% between 2000–04 and 2017–21 (indicator 1.1.5), a death toll that was significantly exacerbated by the confluence of the COVID-19 pandemic. Despite the local cooling and overall health benefits of urban greenspaces, only 277 (27%) of 1038 global urban centres were at least moderately green in 2021 (indicator 2.2.3), and the number of households with air conditioning increased by 66% from 2000 to 2020, a maladaptive response that worsens the energy crisis and further increases urban heat, air pollution, and greenhouse gas emissions. [...]millions of people do not have access to the energy needed to keep their homes at healthy temperatures, preserve food and medication, and meet the seventh Sustainable Development Goal (to ensure access to affordable, reliable, sustainable, and modern energy for all). Aggravating this situation even further, governments continue to incentivise fossil fuel production and consumption: 69 (80%) of 86 countries reviewed had net-negative carbon prices (ie, provided a net subsidy to fossil fuels) for a net total of US$400 billion

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