October 2019 - wg-all - lists.ogf.org

New OGF document in public comment: GLUE spec v2.1
by Greg Newby 31 Oct '20

31 Oct '20

Dear OGF Community: One new OGF document is now available for public comment. Please consider reading and providing feedback. Brief affirmations are very useful to demonstrate community input and support. More detailed analysis is, of course, welcome. * GLUE Specification v2.1 <https://redmine.ogf.org/projects/editor-pubcom/boards/43> ( https://redmine.ogf.org/projects/editor-pubcom/boards/43) This is a Recommendation Track document, with a 60-day public comment period. When published, it will obsoletes GFD #147 Abstract: The GLUE specification is an information model for Grid entities described using the natural language and UML Class Diagrams. As a conceptual model, it is designed to be independent from the concrete data models adopted for its implementation. This document defines the GLUE 2.1 model by extending the GLUE 2.0 model to include Cloud resources and services. Rendering to concrete data models such XML Schema, LDAP Schema and SQL are provided in a separate document. Note that public comments are received via the Open Grid Forum Redmine instance. Anyone may register for a Redmine username. - Greg Newby, OGF Standards Editor -- Gregory Newby Ph.D. Chief Technology Officer / Chef de la Technologie gbnewby(a)computecanada.ca / (o) 416-228-1234 (f) 416-907-1555 (c) 613-334-8373 155 University Avenue, Suite 302, Toronto, Ontario, Canada M5H 3B7 www.computecanada.ca / www.calculcanada.ca / @ComputeCanada

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Geoffrey C. Fox Named 2019 ACM-IEEE CS Ken Kennedy Award Recipient
by Sill, Alan 23 Oct '19

23 Oct '19

Dear OGF colleagues, We are pleased to congratulate long-time OGF participant, colleague, and past member of the OGF Board of Directors Prof. Geoffrey C. Fox on his selection as this year’s recipient of the ACM-IEEE CS Ken Kennedy Award for his "foundational contributions to parallel computing methodology, algorithms and software, and data analysis, and their interfaces with broad classes of applications” as listed on the citation linked below. This award is of course well-deserved and in perfect consistency with the tradition of scholarship, community service, and mentorship set by the late Ken Kennedy, for whom the award is named and in whose memory it is given. We are also grateful for the long pattern of service and contribution given by Prof. Fox over the years to advance the goals of the OGF community. On behalf of the Grid Forum Steering Group and the OGF community, congratulations to Prof. Fox! Alan Sill, Ph.D Managing Director, High Performance Computing Center Adjunct Professor of Physics, Texas Tech University Co-Director, NSF Center for Cloud and Autonomic Computing President, Open Grid Forum -------------------------------------- ACM Bulletin Archives<https://www.acm.org/membership/acm-bulletin-archive> October 23, 2019 [to view image click on] Geoffrey C. Fox Named 2019 ACM-IEEE CS Ken Kennedy Award Recipient [to view image click on] ACM and the IEEE Computer Society (IEEE-CS) have named Geoffrey C. Fox of Indiana University Bloomington as the recipient of the 2019 ACM-IEEE CS Ken Kennedy Award<https://awards.acm.org/kennedy>. Fox was cited for foundational contributions to parallel computing methodology, algorithms and software, and data analysis, and their interfaces with broad classes of applications. The award will be presented at SC19: The International Conference for High Performance Computing, Networking, Storage and Analysis<https://sc19.supercomputing.org/>, November 17-22, in Denver, Colorado. Fox has made several important technical contributions to high performance computing. He identified the principles behind the use of decomposition and efficient message passing in early multiple instruction, multiple data (MIMD) hypercubes, which pioneered application development on parallel machines. In several well-received papers, Fox demonstrated the synergies between message passing interface (MPI) and MapReduce. Fox’s service to the community includes involvement with several organizations, including the National Association for Equal Opportunity in Higher Education, to identify research opportunities in computing for the students and staff of minority serving institutions (MSIs). He has also taught Java and parallel computing online courses to historically black colleges and universities and MSIs. Fox has also taken on many volunteer roles, including General Chair, of several conferences and workshops. Fox is Director of the Digital Science Center, Associate Dean for Research and Graduate Studies at the Indiana University School of Informatics and Computing, and a professor of Informatics and Computing and Physics at Indiana University Bloomington. ACM and the IEEE Computer Society co-sponsor the Kennedy Award, which was established in 2009 to recognize substantial contributions to programmability and productivity in computing and significant community service or mentoring contributions. It was named for the late Ken Kennedy, founder of Rice University’s computer science program and a world expert on high performance computing. The Kennedy Award carries a $5,000 honorarium endowed by the SC Conference Steering Committee. Read the ACM news release<https://www.acm.org/media-center/2019/october/kennedy-award-2019>. [to view image click on] Association for Computing Machinery 1601 Broadway, 10th Floor, New York, NY 10019-7434 Copyright © 2019, ACM, Inc. All rights reserved

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[ASGC] Last & Final ISGC 2020 CFP Extension - until 21 October, 2019
by Sill, Alan 14 Oct '19

14 Oct '19

[Apologize if you receive multiple postings] CFP DEADLINE Extension: 21 October, 2019 We welcome you to contribute or encourage your colleagues to contribute to the ISGC 2020. The submission deadline is extended to 14 October, 2019. Thank you very much for forwarding call to those potentially interested to submit. ************************************************ CALL for PARTICIPATION / ABSTRACTS International Symposium on Grids and Clouds (ISGC<https://nam04.safelinks.protection.outlook.com/?url=http%3A%2F%2Fevent.twgr…>) 2020 8 ~ 13 March 2020, Academia Sinica, Taipei, Taiwan Call for Abstracts • On-line Submission: https://indico4.twgrid.org/indico/event/11/<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Findico4.t…> • Submission Deadline Extension: Monday, 21 October 2019 • Abstract Word Limit: 400 (minimum)～600 (maximum) words • Acceptance Notification to Authors: (the week of) Monday, 9 December 2019 • Conference website: http://event.twgrid.org/isgc2020/<https://nam04.safelinks.protection.outlook.com/?url=http%3A%2F%2Fevent.twgr…> Theme: Challenges in High Performance Data Analytics: Combining Approaches in HPC, HTC, Big Data and AI While the research data are becoming a real asset nowadays, it is an information and knowledge gained through thorough analysis that makes them so valuable. To process vast amounts of data collected, novel high performance data analytics methods and tools are needed, combining classical simulation oriented approaches, big data processing and advanced AI methods. Such a combination is not straightforward and needs novel insights at all levels of the computing environment – from the network and hardware fabrics through the operating systems and middleware to the platforms and software, not forgetting the security – to support data oriented research. Challenging use cases that apply difficult scientific problems are necessary to properly drive the evolution and also to validate such high performance data analytics environments. The goal of ISGC 2020<https://nam04.safelinks.protection.outlook.com/?url=http%3A%2F%2Fevent.twgr…> is to create a face-to-face venue where individual communities and national representatives can present and share their contributions to the global puzzle and contribute thus to the solution of global challenges. We cordially invite and welcome your participation! Topics of Interest: 1. Applications and results from the Virtual Research Communities and Industry (1) Physics (including HEP) and Engineering Applications Submissions should report on experience with physics and engineering applications that exploit grid and cloud computing services, applications that are planned or under development, or application tools and methodologies. Topics of interest include: (1) End-user data analysis including ML/DL based one; (2) Management of distributed data; (3) Applications level monitoring; (4) Performance analysis and system tuning; (5) Workload scheduling; (6) Management of an experimental collaboration as a virtual organization; (7) Comparison between grid and other distributed computing paradigms as enablers of physics data handling and analysis; (8) Expectations for the evolution of computing models drawn from recent experience handling extremely large and geographically diverse datasets; and (9) Application software development, optimization and benchmarking. (2) Biomedicine & Life Sciences Applications During the last decade, research in Biomedicine and Life Sciences has dramatically changed thanks to the continuous developments in High Performance Computing and highly Distributed Computing Infrastructures such as grids and clouds, but also in big-data solutions to deal with the explosion in genomic data. This track aims at discussing problems, solutions and application examples related to this area of research, with a particular focus on non-technical end users. Submissions should concentrate on practical applications and solutions in the fields of Biomedicine and Life Sciences, such as Drug discovery, Structural biology, Bioinformatics, Medical imaging, Public health applications / infrastructures, High throughput (grid and cloud-based) data processing/analysis, Distributed data computing and services, and Big data management issues. Submissions should ideally highlight how the availability and use of Big Data has enabled new processes for or dramatically evolved the scope of their research. (3) Earth & Environmental Sciences & Biodiversity Applications Natural and Environmental sciences are placing an increasing emphasis on the understanding of the Earth as a single, highly complex, coupled system with living and dead organisms. It is well accepted, for example, that the feedback involving oceanic and atmospheric processes can have major consequences for the long-term development of the climate system, which in turn affects biodiversity, natural hazards and can control the development of the cryosphere and lithosphere. Natural disaster mitigation is one of the most critical regional issues in Asia Despite the diversity of environmental sciences, many projects share the same significant challenges. These include the collection of data from multiple distributed sensors (potentially in very remote locations), the management of large low-level data sets, the requirement for metadata fully specifying how, when and where the data were collected, and the post-processing of those low-level data into higher-level data products which need to be presented to scientific users in a concise and intuitive form. This session would in particular address how these challenges are being handled with the aids of e-Science paradigm. (4) Humanities, Arts, and Social Sciences (HASS) Applications Disciplines across the Humanities, Arts and Social Sciences (HASS) have critically engaged with technological innovations such as grid- and cloud computing, and, most recently, various data analytic technologies. The increasing availability of data, ranging from social media text data to consumer big data has led to an increasing interest in analysis methods such as natural language processing, social network analysis, machine learning and text mining. These developments pose challenges as well as opening up opportunities and members of the HASS community have been at the forefront of discussions about the impact that novel forms of data, novel computational infrastructures and novel analytical methods have for the pursuit of science endeavours and our understanding of what science is and can be. The ISGC 2020 HASS track invites papers and presentations covering applications demonstrating the opportunities of new technologies or critically engaging with their methodological implications in the Humanities, Arts and Social Sciences. Innovative application of analytical tools for survey data, social media data, and government (open) data are welcomed. We also invite contributions that critically reflect on the following subjects: (1) the impact that ubiquitous and mobile access to information and communication technologies have for society more generally, especially around topics such as smart cities, civic engagement, and digital journalism; (2) philosophical and methodological reflections on the development of the techniques and the approaches by which data scientists use to pursue knowledge. 2. Technologies that provide access and exploitation of different site resources and infrastructures (5) Virtual Research Environment (including tools, services, workflows, portals, … etc.) Virtual Research Environments (VRE) provide an intuitive, easy-to-use and secure access to (federated) computing resources for solving scientific problems, trying to hide the complexity of the underlying infrastructure, the heterogeneity of the resources, and the interconnecting middleware. Behind the scenes, VREs comprise tools, middleware and portal technologies, workflow automation as well a security solutions for layered and multifaceted applications. Topics of interest include but are not limited to: (1) Real-world experiences building and/or using VREs to gain new scientific knowledge; (2) Middleware technologies, tools, services beyond the state-of-the-art for VREs; (3) Science gateways as specific VRE environments, (4) Innovative technologies to enable VREs on arbitrary devices, including Internet-of-Things; and (5) One-step-ahead workflow integration and automation in VREs. (6) Data Management & Big Data The rapid growth of the data available to scientists and scholars – in terms of Velocity and Variety as well as sheer Volume – is transforming research across disciplines. Increasingly these data sets are generated not just through experiments, but as a byproduct of our day-to-day digital lives. This track explores the consequences of this growth, and encourages submissions relating to two aspects in particular - firstly, the conceptual models and analytical techniques required to process data at scale; secondly, approaches and tools for managing and creating these digital assets throughout their lifecycle. 3. Infrastructure for Research (7) Network, Security, Infrastructure & Operations Networking and the connected e-Infrastructures are becoming ubiquitous. Ensuring the smooth operation and integrity of the services for research communities in a rapidly changing environment are key challenges. This track focuses on the current state of the art and recent advances in these areas: networking, infrastructure, operations, and security. The scope of this track includes advances in high-performance networking (software defined networks, community private networks, the IPv4 to IPv6 transition, cross-domain provisioning), the connected data and compute infrastructures (storage and compute systems architectures, improving service and site reliability, interoperability between infrastructures, data centre models), monitoring tools and metrics, service management (ITIL and SLAs), and infrastructure/systems operations and management. Also included here are issues related to the integrity, reliability, and security of services and data: developments in security middleware, operational security, security policy, federated identity management, and community management. Submissions should address solutions in at least one of these areas. (8) Infrastructure Clouds and Virtualizations This track will focus on the development of cloud infrastructures and on the use of cloud computing and virtualization technologies in large-scale (distributed) computing environments in science and technology. We solicit papers describing underlying virtualization and "cloud" technology including integration of accelerators and support for specific needs of AI/ML and DNN, scientific applications and case studies related to using such technology in large scale infrastructure as well as solutions overcoming challenges and leveraging opportunities in this setting. Of particular interest are results exploring the usability of virtualization and infrastructure clouds from the perspective of machine learning and other scientific applications, the performance, reliability and fault-tolerance of solutions used, and data management issues. Papers dealing with the cost, price, and cloud markets, with security and privacy, as well as portability and standards, are also most welcome. (9) Converging High Performance infrastructures: Supercomputers, clouds, accelerators The classical simulation-oriented computing is nowadays complemented by the novel general machine learning and specifically deep neural networks based approaches. This requires novel approaches to build high performance infrastructures, combining supercomputers, high performance clouds, specialized DNN hardware and other accelerators. An additional challenge lies in the individual components being provided by different owners, usually in a federated distributed way. This track solicits recent research and development achievements and best practices in building and exploiting these converging high performance infrastructures or their components. The topics of interest include, but are not limited to the followings: (1) Building and use of modern high performance computing systems, including special support for AI and DNN in particular; (2) Use of virtualization techniques and containers to support access to and portability across different heterogeneous systems; (3) Experiences, use cases and best practices on the development and operation of large-scale heterogeneous applications; (4) Integration and interoperability to support coordinated federated use of different e-infrastructures (supercomputers, accelerated clouds, …) and their building blocks; (5) Performance of different applications on these integrated high performance infrastructures. Program Committees (In last name alphabetic order) Kento Aida, NII, JP Jim Basney, Univ. of Illinois at Urbana-Champaign. US Daniele Bonacorsi, Univ. of Bologna,, IT Alexandre M.J.J Bonvin, Utrecht Univ., NL Yaning, Arthur Chen, Tamkang Univ., TW Gang Chen, IHEP/ CAS, CN Patrick Fuhrmann, DESY, DE David Groep, Nikhef, NL Mark Hedges, King's College London, UK David Kelsey, STFC-RAL, UK Dieter Kranzlmüller, LMU Munich, DE Yannick Legre, EGI.eu<http://EGI.eu>, NL Simon C. Lin, Academia Sinica, TW Satoshi Matsuoka, Tokyo Inst. of Tech, JP Ludek Matyska, CESNET, CZ Glenn Moloney, Univ. of Melbourne, AU Tomoaki Nakamura, KEK, JP Suhaimi Napis, UPM, MY Alan Sill, Texas Tech Univ., US Basuki Suhardiman, ITB, ID Junichi Tanaka, Univ. of Tokyo, JP Andrea Valassi, CERN, CH Alexander Voss, Univ. of St. Andrews, UK Von Welch, Indiana University, US Remarks All submitted abstracts will be reviewed by the ISGC program committee and track conveners. Authors will receive notification of acceptance in the week of 9 December 2019. For any further questions, please contact the Secretariat. Ms. Stella Shen (stella.shen(a)twgrid.org<mailto:stella.shen@twgrid.org>) Ms. Vicky Huang (vic(a)twgrid.org)<mailto:vic@twgrid.org> Tel: +886-2-2789-8375 Fax: +886-2-2783-5434 Sincerely, ISGC Secretariat Academia Sinica Grid Computing Centre (ASGC) Taipei, Taiwan _______________________________________________

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