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CFP - HPBench 2020
by Samar Aseeri 29 May '20

29 May '20

Dear Sir, dear Madam, Please, can you pass this announcement also to interested colleagues. Kind regards ========================================================================== CALL FOR PAPERS The 7th Special Session on High Performance Computing for Application Benchmarking and Optimization (HPBench 2020) As part of the International Conference on High Performance Computing & Simulation (HPCS 2020) http://hpcs2020.cisedu.info/ or http://conf.cisedu.info/rp/hpcs20 Barcelona, Spain ========================================================================== Benchmarking is an essential aspect of modern high performance computing and computational science, and as such, it provides a means for quantifying and comparing the performance of different computer systems. With a large combination of aspects to benchmark, all the way from the capability of a single core, to cluster configuration, and to various software configurations, the benchmarking process is more of an art than science. However, the results of this process drive modern science and are vital for the community to draw sensible conclusions on the performance of applications and systems. This special session focuses on research work aimed at benchmarking modern parallel and distributed systems for addressing a number of real world problems. As such, contributions concerning the definition of new open platforms, new benchmarks to match modern architectural evolutions, studies on the aspects of benchmarking different aspects of systems (from raw runtime performance to energy consumption to energy consumed per data movement) and mathematical foundations of benchmarking are sought. IMPORTANT DATES : Papers Due: 1 July 2020 Author Notification: 22 July 2020 Camera-Ready Submission: 10 August 2020 Conference Dates: 26-30 October 2020 TOPICS : The HPBench topics of interest include, but are not limited to -Open Platforms for Parallel and Distributed Application Benchmarking and Optimization -Benchmarking on the Cloud -Benchmarking of Clusters, Supercomputers, and large-scale systems -Benchmarking the Performance of I/O -Benchmarking of Energy and Energy Efficiency -Benchmarking Web Services -Virtualization for Distributed Benchmarking -Data Distribution for Benchmarking -Performance results of benchmarks on modern platforms -Scalability Aspects of Benchmarking Parallel Applications on Parallel and Distributed Systems -Benchmarking of Parallel Scientific and Business Applications -Performance of Benchmarking Applications (Eg: NAS parallel benchmarks) -Techniques, frameworks and results concerning the benchmarking of library packages -Tools and frameworks for performance modeling systems and applications -Tools and frameworks for simulation, measurement and monitoring -Performance Measurements, Monitoring, Modeling and Simulation -Domain-specific benchmarks and applications (such as image processing, pattern recognition, cryptography, biometrics, differential equation solvers, signal processing and alike) -Mathematical Foundations of Benchmarking, Metrics and Heuristics GENERAL CHAIRS : Samar Aseeri, King Abdullah University of Science and Technology, Saudi Arabia Luigi Iapichino, Leibniz Supercomputing Centre (LRZ), Germany TECHNICAL PROGRAM COMMITTEE: Cosimo Anglano, Universitá del Piemonte Orientale, Italy Fabio Baruffa, Intel, Germany Suren Byna, Lawrence Berkeley National Laboratory, California, USA Paul Carpenter, Barcelona Supercomputing Center, Spain Douglas Doerfler, Lawrence Berkeley National Laboratory, USA Zhiyi Huang, University of Otago, New Zealand Clay Hughes, Sandia National Laboratories, USA Aleksandar Ilic, Universidade de Lisboa, Portugal Bok Jik Lee, Seoul National University, Korea Ravi Reddy Manumachu, University College Dublin, Ireland Dana Petcu, West University of Timisoara, Romania Ivan Rodero, Rutgers University, USA ********************************************************************* For more information see http://conf.cisedu.info/rp/hpcs20/2-conference/special-sessions/session02-h… Kind Regards -- Samar Aseeri, PhD Computational Scientist Extreme Computing Research Center (ECRC) Building 1 -Office: 0128 *King Abdullah University of Science & Technology* Thuwal, Saudi Arabia -- This message and its contents, including attachments are intended solely for the original recipient. If you are not the intended recipient or have received this message in error, please notify me immediately and delete this message from your computer system. Any unauthorized use or distribution is prohibited. Please consider the environment before printing this email.

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CFP - HPBench 2020
by Samar Aseeri 29 May '20

29 May '20

Dear Sir, dear Madam, Please, can you pass this announcement also to interested colleagues. Kind regards ========================================================================== CALL FOR PAPERS The 7th Special Session on High Performance Computing for Application Benchmarking and Optimization (HPBench 2020) As part of the International Conference on High Performance Computing & Simulation (HPCS 2020) http://hpcs2020.cisedu.info/ or http://conf.cisedu.info/rp/hpcs20 Barcelona, Spain ========================================================================== The Special Session on Compiler Architecture, Design and Optimization provides a premier venue to bring together systems researchers working on compiler architecture, design and code optimization of high performance computing systems, particularly for many-core, GPU, and accelerators. The track spans the spectrum from compiler performance to energy optimization, and from purely static to fully dynamic approaches. IMPORTANT DATES : Papers Due: 1 July 2020 Author Notification: 22 July 2020 Camera-Ready Submission: 3 August 2020 Conference Dates: 26-30 October 2020 TOPICS : The HPBench topics of interest include, but are not limited to -Open Platforms for Parallel and Distributed Application Benchmarking and Optimization -Benchmarking on the Cloud -Benchmarking of Clusters, Supercomputers, and large-scale systems -Benchmarking the Performance of I/O -Benchmarking of Energy and Energy Efficiency -Benchmarking Web Services -Virtualization for Distributed Benchmarking -Data Distribution for Benchmarking -Performance results of benchmarks on modern platforms -Scalability Aspects of Benchmarking Parallel Applications on Parallel and Distributed Systems -Benchmarking of Parallel Scientific and Business Applications -Performance of Benchmarking Applications (Eg: NAS parallel benchmarks) -Techniques, frameworks and results concerning the benchmarking of library packages -Tools and frameworks for performance modeling systems and applications -Tools and frameworks for simulation, measurement and monitoring -Performance Measurements, Monitoring, Modeling and Simulation -Domain-specific benchmarks and applications (such as image processing, pattern recognition, cryptography, biometrics, differential equation solvers, signal processing and alike) -Mathematical Foundations of Benchmarking, Metrics and Heuristics GENERAL CHAIRS : Samar Aseeri, King Abdullah University of Science and Technology, Saudi Arabia Luigi Iapichino, Leibniz Supercomputing Centre (LRZ), Germany TECHNICAL PROGRAM COMMITTEE: Cosimo Anglano, Universitá del Piemonte Orientale, Italy Fabio Baruffa, Intel, Germany Suren Byna, Lawrence Berkeley National Laboratory, California, USA Paul Carpenter, Barcelona Supercomputing Center, Spain Douglas Doerfler, Lawrence Berkeley National Laboratory, USA Zhiyi Huang, University of Otago, New Zealand Clay Hughes, Sandia National Laboratories, USA Aleksandar Ilic, Universidade de Lisboa, Portugal Bok Jik Lee, Gwangju Institute of Science and Technology, Korea Ravi Reddy Manumachu, University College Dublin, Ireland Dana Petcu, West University of Timisoara, Romania Ivan Rodero, Rutgers University, USA ********************************************************************* For more information see http://conf.cisedu.info/rp/hpcs20/2-conference/special-sessions/session02-h… Kind Regards -- Samar Aseeri, PhD Computational Scientist Extreme Computing Research Center (ECRC) Building 1 -Office: 0128 *King Abdullah University of Science & Technology* Thuwal, Saudi Arabia -- This message and its contents, including attachments are intended solely for the original recipient. If you are not the intended recipient or have received this message in error, please notify me immediately and delete this message from your computer system. Any unauthorized use or distribution is prohibited. Please consider the environment before printing this email.

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GECON 2020, Final Call, Submission Deadline Extended to June 7th, 17th International Conference on Economics of Grids, Clouds, Systems & Services
by Jörn ALTMANN 26 May '20

26 May '20

=========================================================== 17th International Conference on Economics of Grids, Clouds, Systems & Services Extended Deadline: June 7th, 2020 =========================================================== ONLINE CONFERENCE with high interaction between participants WWW: http://2020.gecon-conference.org Dates: 15-17 September 2020 Proceedings: Springer LNCS =========== / NOTICES! / =========== Extended Deadlines: Extended abstract Submission deadline: May 31st, 2020 Full papers deadline: June 7th, 2020 The organizing committee of GECON 2020 has decided all sessions will be held exclusively online! We consider the new online format to offer opportunities for exploring new ways of improving the interaction and feedback of the audience with speakers and promoting networking among the conference participants. The registration fee of the online conference has been reduced to 250€ for one author of each publication, 100 € for participants, and 50€ for students. The selection process will run as planned. The timely publication of accepted papers in the proceedings of GECON 2020 will be published in the LNCS series of Springer as announced. Due to the new online format, GECON maintains open the proposal for special sessions. With the objective of encouraging alternative forms of participation that can increase discussions of technical topics and new ideas. We solicit new topics and birds-of-a-feather session proposals. Deadline for proposals is August 15th, 2020. ======== / SCOPE / ======== GECON 2020 builds upon the very successful tradition of the conference previous editions (http://www.gecon-conference.org) since 2003. GECON solicits contributions that are interdisciplinary, combining business and economic aspects with engineering and computer science related themes. ============== / Important Dates / ============== Deadlines: Extended abstract submission deadline: May 31st, 2020 Full papers deadline: June 7th, 2020 Notification of acceptance: July 6th, 2020 Camera Ready deadline: July 13th, 2020 Poster Submission for accepted papers: July 20th, 2020 Birds of a feather session proposals: August 15th, 2020 ============================== / Publication and Submission Guidelines / ============================== Original full papers and work-in-progress papers, which are not currently under review by another conference, will be considered. Manuscripts will be reviewed based on technical merit, originality, and relevance. Past acceptance rates have been around 30 per cent in recent years. Full papers, work-in-progress (WIP) papers, and wild-and-crazy-ideas (WACI) papers shall be submitted using the Springer LNCS format. Submitted full papers should not exceed 12 pages, WIP papers should not exceed 8 pages (including references and appendices) and WACI papers (4 pages). For further details, visit the GECON 2020 web page. Paper submissions are managed through EasyChair at (https://easychair.org/conferences/?conf=gecon2020) The proceedings will be published by Springer LNCS. Extended versions of up to 10 accepted papers in the Computer Science field will be invited for publication in a special issue of the: - Elsevier Journal of Future Generation Computing Systems. For papers targeting mainly business and economic aspects, a special issue of the - Springer Electronic Markets Journal or - Elsevier Electronic Commerce and Applications with up to 5 papers is foreseen. ============== / Topics of Interest / ============== As a global market for infrastructures, platforms, and software services emerge, the need to understand and deal with its implications and its interdisciplinary challenges is quickly growing. To address this, GECON encourages the submission of papers, which combine at least one economic/legal area and one technologic area. GECON list of areas includes, but is not limited to: -Economics- Incentive design, strategic behavior & game theory Market mechanisms, auctions models, and bidding languages Economic efficiency Techno-economic analysis and modelling Pricing schemes and revenue models Metering, accounting, and billing Cost-benefit analysis Automated trading and bidding support tools Trust, reputation, security, and risk management Performance monitoring, optimization, and prediction Reports on industry test-beds and operational markets Energy efficiency Sustainability Business models and strategies Decision support Open source ecosystems -Law and Legal Aspects- Standardization, interoperability, and legal aspects Service level agreements (SLAs), negotiation, Monitoring and enforcement Governance of ecosystems Privacy -Clouds, Grids, Systems and Services- IaaS, SaaS, PaaS and Federation of resources Vertical scaling, burstable computing, vertical elasticity Resource management: allocation, sharing, scheduling Capacity planning Virtualization and containers Service science, management and engineering (SSME) Software engineering Security -Technologies Transforming the Economy- Smart grids, smart cities, and smart buildings Energy-aware infrastructures and services Fog, edge, osmosis computing Micro-services, serverless computing Internet-of-Things Blockchains Community networks Social networks Social computing Big data Data stream ingestion and complex event processing Additionally, the following special topic sessions have been lined up (a detailed description is available on the GECON 2020 submission web site): -Digital Infrastructures to Support Decision Making for Pandemic Response and Countermeasures- Contact: GECON 2020 Chairs, gecon2020(a)easychair.org -Decentralising Clouds to Deliver Intelligence at the Edge- Contact: Seugwoo Kum, Korean Electronics Technology Institute, Korea, seungwoo.kum(a)gmail.com; Domenico Siracusa, Fondazione Bruno Kessler, Italy, dsiracusa(a)fbk.eu. -Sustainability of Digital Infrastructures: Social, Economic, and Policy Aspects for Material Resources Supporting the Digital World- Contact: Leandro Navarro Universitat Politecnica de Catalunya, Spain, leandro(a)ac.upc.edu; Felix Freitag Universitat Politecnica de Catalunya, Spain, felix(a)ac.upc.edu -Business and Economic Aspects of Machine Learning, Cognitive Systems and Data Science- Contact: Aurilla Aurelie Arntzen University of South-Eastern, Norway, aurilla.aurelie.arntzen(a)usn.no ==================== / Conference Organization / ==================== Conference Chair Vlado Stankovski (University of Ljubljana,Slovenia) Conference Vice-Chairs Karim Djemame (University of Leeds, UK) Orna Agmon Ben-Yehuda (University of Haifa, Israel) Jorn Altmann (Seoul National University, South-Korea) Jose Angel Banares (Zaragoza University, Spai Steering Committee Karim Djemame (University of Leeds, UK) Jorn Altmann (Seoul National University, South-Korea) Jose Angel Banares (Zaragoza University, Spain) Orna Agmon Ben-Yehuda (Technion, Israel) Steven Miller (Singapore Management University, Singapore) Omer F. Rana (Cardiff University, UK) Gheorghe Cosmin Silaghi (Babes-Bolyai University, Romania) Konstantinos Tserpes (Harokopio University, Greece) Maurizio Naldi (Universita di Roma, Italy) Contact for Questions: gecon2020(a)easychair.org @&@#^%&*%$@*#*&%#%^&$#@^@^&@%$@*^#&@ @%#&#@^*$@@#*%&%#@*$*&^@#$%@#%&$&%@ Prof. Dr. Jörn ALTMANN office 37-305 Technology Management, Economics, and Policy Program Departmentof Industrial Engineering Collegeof Engineering Seoul National University 1 Gwanak-Ro, Gwanak-Gu, 08826 Seoul, South-Korea phone: +82 70 7678 6676 phone: +49 4155 129333 phone: +1 510 962 3062 phone: +44 20 32393134 fax: +1 610 956 4404 email: jorn.altmann(a)acm.org www: http://altmann.my-groups.de/

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CFP for Virtualization in Machine Learning, High Performance Computing and Simulation
by Uday Kurkure 24 May '20

24 May '20

*The Third Special Session on Virtualization in Machine Learning, High Performance Computing and Simulation* *(VIRT 2020)* *CALL FOR PAPERS & PARTICIPATION* *As part of * *The 18th International Conference on High Performance Computing & Simulation (HPCS 2020)http://hpcs2020.cisedu.info/ <http://hpcs2020.cisedu.info/> or http://conf.cisedu.info/rp/hpcs20 <http://conf.cisedu.info/rp/hpcs20>* *26 - 30 October* * 2020* *Barcelona, Spain* *(Tentative)* * Paper Submission Deadline: 17 June 2020* *Submissions could be for full papers, short papers, poster papers, or posters* *PURPOSE AND SCOPE* Virtualization has become the foundation of cloud computing. The scale of cloud computing data centers is similar to the supercomputers used in High Performance Computing. Both involve millions of CPU cores, tens of thousands of accelerators like GPUs, FPGAs connected by high speed interconnects and different connection topologies. Studies have shown that the GPU utilization in HPC is often at 50%. Virtualization can be the key to increasing resource utilization and managing massive infrastructures efficiently. GPU vendors have introduced virtualized versions of GPUs. FPGAs are being deployed in virtual infrastructure. These and other developments in the field, along with future exascale systems, will provide increasing degree of virtualization within the systems. The goal of this special session is to be an opportunity to discuss and exchange research on the different virtualization technologies and how they can be efficiently applied in High Performance Computing. Theoretical research, engineering solutions dealing with practical tradeoffs, and complex system implementation papers are welcomed. *The VIRT topics include (but are not limited to) the following: * - *Virtualization in HPC* o Energy efficient solutions for HPC applications in the cloud environment o High-availability based on system-level virtualization mechanisms for HPC o Fault tolerance mechanisms based on system-level virtualization mechanisms for HPC o Performance and evaluation of diverse HPC workloads in virtualization environment o Security Isolation, Resource Isolation and Data Isolation in Virtualized HPC o Flexibility and Ease of system administration and management for virtualized environments for HPC o Running diverse workloads o Running heterogeneous Operating Systems o Live Migration and Suspend/Resume of VMs to improve resource utilization and avoid downtime o Scheduling of resources and Workloads o Software Defined Data Centers (SDDC) o Hypervisors and other virtualization solutions tailored for HPC systems o Big Data and Analytics in Virtualized Environments o Enterprise High Performance Computing in Virtualized Environments - *Accelerators in Virtualized HPC Environments:* o Virtualized GPUs o Scheduling of Virtual GPUs o Using FPGAs in Virtualization Stack o Dynamic Reconfiguration of FPGAs - * IO Virtualization* o Network Virtualization o SR-IOV o Software Defined Networking (SDN) o Storage Virtualization o RDMA and vRDMA - - Containers in HPC o Isolation of Multiple User-Spaces o Running containers in Virtual Machines - *Tools* o Virtualization solutions for dealing with heterogeneity in HPC environments o Compilers for heterogenous architectures involving GPUS, FPGAs, multi-core CPUs o Operating system support for virtualization in HPC systems o Debugging and/or profiling in virtual environments - *Algorithms* o Distributed Resource Scheduling o Distributed Computing - *AI, Machine Learning and Deep Learning* o Virtualization of Deep Learning Workloads o Deep Learning in HPC Simulations o Resource Allocation Using Machine Learning o Reinforcement Learning for Resource Allocation o Machine Learning to build tools for measurement & calibration - *Virtualization in Simulation* *INSTRUCTIONS FOR PAPER SUBMISSIONS * You are invited to submit original and unpublished research works on above and other topics related to *virtualization in high performance computing and simulation*. Submitted papers must not have been published or simultaneously submitted elsewhere until it appears in HPCS proceedings, in the case of acceptance, or notified otherwise. Submission can be for *- Regular papers*, please submit a PDF copy of your full manuscript, not to exceed 8 double-column formatted pages per template, and include up to 6 keywords and an abstract of no more than 400 words. Additional pages will be charged additional fee. Submission should include a cover page with authors' names, affiliation addresses, fax numbers, phone numbers, and all authors email addresses. Please, indicate clearly the corresponding author(s) although all authors are equally responsible for the manuscript. *- Short papers* (up to 4 pages), please submit a PDF copy of your full manuscript, not to exceed 4 double-column formatted pages per template, and include up to 6 keywords and an abstract of no more than 400 words. Additional pages will be charged additional fee. Submission should include a cover page with authors' names, affiliation addresses, fax numbers, phone numbers, and all authors email addresses. Please, indicate clearly the corresponding author(s) although all authors are equally responsible for the manuscript. *- Poster papers* and *Posters* (please refer to http://hpcs2020.cisedu.info/1-call-for-papers-and-participation/call-for-po… for posters submission details) will also be considered. Please specify the type of submission you have. Please include page numbers on all preliminary submissions to make it easier for reviewers to provide helpful comments. Submit a PDF copy of your full manuscript to the special session paper submission site at https://cmt3.research.microsoft.com/VIRT2020 . Acknowledgement will be sent within 48 hours of submission. *Conference Policies* Only PDF files will be accepted, uploaded to the submission link above. Each paper will receive a minimum of three reviews. Papers will be selected based on their originality, relevance, significance, technical clarity and soundness, presentation, language, and references. Submission implies the willingness of at least one of the authors to register and present the paper, if accepted. At least one of the authors of each accepted paper will have to register and attend the HPCS 2020 conference to present the paper at the special session as scheduled. By submitting the paper to the HPCS conference, all authors agree to abide by all HPCS conference paper submission, publication and presentation policies as well as following ethical and professional codes of conduct, including those of the professional co-sponsoring organizations. Contents of manuscripts submitted to the tracks program committees shall be regarded as privileged as well and handled in the same manner and standards. For more information, please refer to the *Authors Info* and *Registration Info* pages. *Proceedings* Accepted papers will be published in the Conference proceedings. Instructions for final manuscript format and requirements will be posted on the HPCS 2020 Conference web site. It is our intent to have the proceedings formally published in hard and soft copies and be available at the time of the conference. The proceedings is projected to be included in the IEEE or ACM Digital Library and indexed in all major indexing services accordingly. *SPECIAL ISSUE* Plans are underway to have the best papers, in extended version, selected for possible publication in a reputable journal as special issue. Detailed information will soon be announced and will be made available on the conference website. If you have any questions about paper submission or the special session, please contact the special session organizers. *IMPORTANT DATES* *Paper Submissions: ------------------------------------------- 17 June 2020* *Acceptance Notification: -------------------------------------- 10 July 2020* *Camera Ready Papers and Registration Due by: ----------- 03 August 2020* *Conference Dates: -------------------------------------------- 26-30 October 2020* *SPECIAL SESSION ORGANIZERS* *Uday Kurkure * VMware, Inc. 3401 Hillview Avenue Palo Alto, CA 94304, USA Phone: +1 650-427-1179 Fax: +1 650- Email: uday(a)alumni.stanford.edu *Hari Sivaraman * VMware, Inc. 3401 Hillview Avenue Palo Alto, CA 94304, USA Phone: +1 650-427-3681 Fax: +1 650- Email: hsivaraman(a)vmware.com *Lan Vu * VMware, Inc. 3401 Hillview Avenue Palo Alto, CA 94304, USA Phone: +1 650-427-1327 Fax: +1 650- Email: lanv(a)vmware.com *International Program Committee*: * All submitted papers will be rigorously reviewed by the special session technical program committee members following similar criteria used in HPCS 2020 and will be published as part of the HPCS 2020 Proceedings. - *Cristina Boeres*, Fluminense Federal University, Brazil - *Isaac Gelado*, Nvidia Corp., Santa Clara, California, USA - *Kyle Hale*, Illinois Institute of Technology, Illinois, USA - *Xiaoyi Lu*, The Ohio State University - Columbus, Ohio, USA - *Carlos Reano*, Queen's University Belfast, U.K. - *Federico Silla*, Universitat Politecnica de Valencia, Spain - *Alex Sim*, Lawrence Berkeley National Laboratory, California, USA - *Giang Son Tran*, University of Science and Technology of Hanoi, Hanoi, Vietnam - *Blesson Varghese*, Queen's University Belfast, U.K. - *Dong Ping Zhang*, AMD Inc., San Jose, California, USA - *Jie Zhang*, Amazon Inc., Washington, USA - *Yongli Zhao*, Beijing University of Posts and Telecommunications, Beijing, China

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Postdoc Position at Berkeley Lab in Ice Sheet Modeling
by Esmond G. Ng 21 May '20

21 May '20

Berkeley Lab's Computational Research Division has an opening for a Postdoctoral Scholar to work on the BISICLES Ice Sheet Model. The Applied Numerical Algorithms Group (ANAG), in partnership with the Universities of Bristol and Swansea in the UK, is a home of BISICLES, an open-source adaptive mesh refinement (AMR) ice sheet model under development as a part of the U.S. Department of Energy-funded ProSPect SciDAC partnership (see http://bisicles.lbl.gov) You will join an interdisciplinary team of scientists and engineers in extending the current BISICLES capabilities while applying the model to a range of idealized and realistic problems. ANAG develops advanced numerical algorithms and software for partial differential equations integrated with the application of the software to problems of independent scientific and engineering interest. The primary focus of our work is in the development of high-resolution and adaptive finite difference methods for partial differential equations in complex geometries with applications to DOE-mission applications including porous media flows, magnetohydrodynamics, industrial problems, climate, and fusion energy. Details, including how to apply, can be found here: https://jobs.lbl.gov/jobs/bisicles-ice-sheet-model-postdoctoral-scholar-2616

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CFP: Resilience@Euro-Par 2020 - Papers due June 12 (deadline extended)
by Thomas Naughton 20 May '20

20 May '20

We apologize if you receive multiple copies of this call for papers. -------------------------------------------------------------------------------- 13th Workshop on Resiliency in High Performance Computing (Resilience) in Clusters, Clouds, and Grids <https://www.csm.ornl.gov/srt/conferences/Resilience/2020> in conjunction with the 26th International European Conference on Parallel and Distributed Computing (Euro-Par), Warsaw, Poland August 24 - 28, 2020 <http://2020.euro-par.org> 2020 Workshop Format: Due to the exceptional situation of COVID-19, this year Euro-Par and its workshops will be organized as an all-virtual event. This includes the main conference and workshops. The accepted workshop papers must be presented by one of the authors in order to be included in the proceedings. There will be a single minimal registration fee for each accepted paper in order to cover expenses associated with organization and proceedings publication. Only one author per paper needs to register (150 euros). Lastly, the preferred presentation format for the workshop will be via a streaming presentation, with slides and pre-recorded video presentations used in exceptional situations. Overview: Resilience is a critical challenge as high performance computing (HPC) systems continue to increase component counts, individual component reliability decreases (such as due to shrinking process technology and near-threshold voltage (NTV) operation), hardware complexity increases (such as due to heterogeneous computing) and software complexity increases (such as due to complex data- and workflows, real-time requirements and integration of artificial intelligence (AI) technologies with traditional applications). Correctness and execution efficiency, in spite of faults, errors, and failures, is essential to ensure the success of the HPC systems, cluster computing environments, Grid computing infrastructures, and Cloud computing services. The impact of faults, errors, and failures in such HPC systems can range from financial losses due to system downtime (sometimes several tens-of-thousands of Dollars per lost system-hour), to financial losses due to unnecessary overprovision (acquisition and operating costs), to financial losses and legal liabilities due to erroneous or delayed output. The emergence of AI technology opens up new possibilities, but also new problems. Using AI technology for operational intelligence that enables resilience in HPC systems and centers is a complex control problem, while designing resilient AI technology for HPC applications is a difficult algorithmic problem. Resilience for HPC systems encompasses a wide spectrum of fundamental and applied research and development, including theoretical foundations, error/failure and anomaly detection, monitoring and control, end-to-end data integrity, enabling infrastructure, and resilient algorithms. This workshop brings together experts in the community to further research and development in HPC resilience and to facilitate exchanges across the computational paradigms of extreme-scale HPC, cluster computing, Grid computing, and Cloud computing. Submission Guidelines: Authors are invited to submit papers electronically in English in PDF format. Submitted manuscripts should be structured as technical papers and BETWEEN 10 AND 12 PAGES, including figures, tables and references, using Springer's Lecture Notes in Computer Science (LNCS) format at <http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0>. Papers with less than 10 or more than 12 pages will not be accepted due to publisher guidelines. Submissions should include abstract, key words and the e-mail address of the corresponding author. Papers not conforming to these guidelines may be returned without review. All manuscripts will be reviewed and will be judged on correctness, originality, technical strength, significance, quality of presentation, and interest and relevance to the conference attendees. Submitted papers must represent original unpublished research that is not currently under review for any other conference or journal. Papers not following these guidelines will be rejected without review and further action may be taken, including (but not limited to) notifications sent to the heads of the institutions of the authors and sponsors of the conference. Submissions received after the due date or not appropriately structured may also not be considered. The proceedings will be published in Springer's LNCS as post-conference proceedings. At least one author of an accepted paper must register for and attend the workshop for inclusion in the proceedings. Authors may contact the workshop program chairs for more information. Important websites: - Resilience 2020 Website: <https://www.csm.ornl.gov/srt/conferences/Resilience/2020> - Resilience 2020 Submissions: <https://easychair.org/conferences/?conf=europar2020workshop> - Euro-Par 2020 website: <http://2020.euro-par.org> Topics of interest include, but are not limited to: - Theoretical foundations for resilience: - Metrics and measurement - Statistics and optimization - Simulation and emulation - Formal methods - Efficiency modeling and uncertainty quantification - Experience reports - Error/failure/anomaly detection and reliability/dependability modeling: - Statistical analyses - Machine learning and artificial intelligence - Digital twins - Data collection and aggregation - Information visualization - Monitoring and control for resilience: - Center, system and application monitoring and control - Reliability, availability, serviceability and performability - Tunable fidelity and quality of service - Automated response and recovery - Operational intelligence to enable resilience - End-to-end integrity: - Fault tolerant design of centers, systems and applications - Forward migration and verification - Degraded operation - Error propagation, failure cascades, and error/failure containment - Testing and evaluation, including fault/error/failure injection - Enabling infrastructure for resilience: - Reliability, availability, serviceability systems - System software and middleware - Resilience extensions for programming models - Tools and frameworks - Support for resilience in heterogeneous architectures - Resilient algorithms: - Algorithmic detection and correction - Resilient solvers and algorithm-based fault tolerance - Fault tolerant numerical methods - Robust iterative algorithms - Resilient artificial intelligence Important Dates: - Workshop papers due: June 12, 2020 (extended) - Workshop author notification: July 21, 2020 - Workshop author registration: TBA - Workshop paper (for informal workshop proceedings): July 21, 2020 - Workshop date: August 24 or 25, 2020 - Workshop camera-ready papers: September 11, 2020 (after the conference) General Co-Chairs: - Stephen L. Scott Tennessee Tech University, USA scottsl(a)ornl.gov - Christian Engelmann Oak Ridge National Laboratory , USA engelmannc(a)ornl.gov Program Co-Chairs: - Ferrol Aderholdt Middle Tennessee State University, USA ferrol.aderholdt(a)mtsu.edu - Thomas Naughton Oak Ridge National Laboratory , USA naughtont(a)ornl.gov Workshop Chair Emeritus: - Chokchai (Box) Leangsuksun Louisiana Tech University, USA box(a)latech.edu Program Committee: - Wesley Bland, Intel Corporation, USA - Hans-Joachim Bungartz, Technical University of Munich, Germany - Marc Casas, Barcelona Supercomputer Center, Spain - Zizhong Chen, University of California at Riverside, USA - Robert Clay, Sandia National Laboratories, USA - Nathan DeBardeleben, Los Alamos National Laboratory, USA - James Elliott, Sandia National Laboratories, USA - Kurt Ferreira, Sandia National Laboratories, USA - Saurabh Hukerikar, NVIDIA, USA - Ignacio Laguna, Lawrence Livermore National Laboratory, USA - Scott Levy, Sandia National Laboratories, USA - Rolf Riesen, Intel Corporation, USA - Yves Robert, ENS Lyon, France - Thomas Ropars, Universite Grenoble Alpes, France - Martin Schulz, Technical University of Munich, Germany - Keita Teranishi, Sandia National Laboratories, USA _________________________________________________________________________ Thomas Naughton naughtont(a)ornl.gov Research Associate (865) 576-4184

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CVML live Web lectures 20th May 2020: 1) Motion estimation, 2) Introduction to Machine Learning. Change of CVML web lectures date/time.
by ioannakoroni＠csd.auth.gr 15 May '20

15 May '20

Dear Computer Vision/Machine Learning/Autonomous Systems students, engineers, scientists and enthusiasts, Artificial Intelligence and Information analysis (AIIA) Lab, Aristotle University of Thessaloniki, Greece is proud to have launched the live CVML Web lecture series that covers very important Computer Vision/Machine Learning topics. Two new upcoming 45 min lectures will take place soon: 1) Motion estimation 2) Introduction to Machine Learning New!: Date/time: Wednesday 20th May 2020, 17:00-18:30 EEST for both lectures (7:00-8:30 am California time, 10:00-11:30 am New York time, 22:00-23:30 Beijing time). Registration can be done using the link: <http://icarus.csd.auth.gr/cvml-web-lecture-series/> http://icarus.csd.auth.gr/cvml-web-lecture-series/ Registration for asynchronous access to CVML live Web lecture material (video, pdf/ppt) for any past/present lecture can be done using the link: <http://icarus.csd.auth.gr/cvml-web-lecture-series/> http://icarus.csd.auth.gr/cvml-web-lecture-series/ Lecture abstracts 1) Motion estimation, Wednesday 20th May 2020, 17:00-17:45 EEST Summary: Motion estimation principals will be analyzed. Initiating form 2D and 3D motion models, displacement estimation as well as quality metrics for motion estimation will subsequently be detailed. One of the basic motion estimation techniques, namely block matching, will also be presented, along with three alternative, faster methods. A good overview of deep neural notion estimation will be presented. Phase correlation will be described, next followed by optical flow equation methods. Finally, a brief introduction to object detection and tracking will conclude the lecture. 2) Introduction to Machine Learning, Wednesday 20th May 2020, 17:45-18:30 EEST Summary: This lecture will cover the basic concepts of Machine Learning. Supervised, self-supervised, unsupervised, semi-supervised learning. Multi-task Machine Learning. Classification, regression. Object detection, Object tracking. Clustering. Dimensionality reduction, data retrieval. Artificial Neural Networks. Adversarial Machine Learning. Generative Machine Learning. Temporal Machine learning (Recurrent Neural Networks). Continual Learning (few-shot learning, online learning). Reinforcement Learning. Adaptive learning (Knowledge Distillation, Domain adaptation, Transfer learning, Activation Pattern Analysis, Federated learning/Collaborative learning, Ensemble learning). Precise mathematical definitions of ML tasks will be presented. Lecturer: Prof. Ioannis Pitas (IEEE fellow, IEEE Distinguished Lecturer, EURASIP fellow) received the Diploma and PhD degree in Electrical Engineering, both from the Aristotle University of Thessaloniki, Greece. Since 1994, he has been a Professor at the Department of Informatics of the same University. His current interests are in the areas of machine learning, computer vision, intelligent digital media, human centered interfaces, affective computing, 3D imaging and biomedical imaging. He has published over 860 papers, contributed in 44 books in his areas of interest and edited or (co-)authored another 11 books. He has also been member of the program committee of many scientific conferences and workshops. In the past he served as Associate Editor or co-Editor of 9 international journals and General or Technical Chair of 4 international conferences. He participated in 69 R&D projects, primarily funded by the European Union and is/was principal investigator/researcher in 41 such projects. He has 31000+ citations to his work and h-index 83+ (Google Scholar). Prof. Pitas lead the big European H2020 R&D project MULTIDRONE: <https://multidrone.eu/> https://multidrone.eu/ and is principal investigator (AUTH) in H2020 projects Aerial Core and AI4Media. He is chair of the Autonomous Systems initiative <https://ieeeasi.signalprocessingsociety.org/> https://ieeeasi.signalprocessingsociety.org/. Lecturing record of Prof. I. Pitas: He was Visiting/Adjunct/Honorary Professor/Researcher and lectured at several Universities: University of Toronto (Canada), University of British Columbia (Canada), EPFL (Switzerland), Chinese Academy of Sciences (China), University of Bristol (UK), Tampere University of Technology (Finland), Yonsei University (Korea), Erlangen-Nurnberg University (Germany), National University of Malaysia, Henan University (China). He delivered 90 invited/keynote lectures in prestigious international Conferences and top Universities worldwide. He run 17 short courses and tutorials on Autonomous Systems, Computer Vision and Machine Learning, most of them in the past 3 years in many countries, e.g., USA, UK, Italy, Finland, Greece, Australia, N. Zealand, Korea, Taiwan, Sri Lanka, Bhutan. Relevant links: a) Prof. I. Pitas: <https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el> https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el b) AIIA Lab <http://www.aiia.csd.auth.gr> www.aiia.csd.auth.gr General information: Lectures will consist primarily of live lecture streaming and PPT slides. Attendees (registrants) need no special computer equipment for attending the lecture. They will receive the lecture PDF before each lecture and will have the ability to ask questions real-time. Audience should have basic University-level undergraduate knowledge of any science or engineering department (calculus, probabilities, programming, that are typical e.g., in any ECE, CS, EE undergraduate program). More advanced knowledge (signals and systems, optimization theory, machine learning) is very helpful but nor required. These two lectures are part of a 14 lecture CVML web course 'Computer vision and machine learning for autonomous systems' (April-June 2020): Introduction to autonomous systems (delivered 25th April 2020) Introduction to computer vision (delivered 25th April 2020) Image acquisition, camera geometry (delivered 2nd May 2020) Stereo and Multiview imaging (delivered 9th May 2020) Structure from Motion (delivered 9th May 2020) 2D convolution and correlation algorithms Motion estimation Introduction to Machine Learning Introduction to neural networks, Perceptron, backpropagation Deep neural networks, Convolutional NNs Deep learning for object/target detection Object tracking Localization and mapping Fast convolution algorithms. CVML programming tools. Sincerely yours Prof. Ioannis Pitas Director of Artificial Intelligence and Information analysis (AIIA) Lab, Aristotle University of Thessaloniki, Greece Post scriptum: To stay current on CVMl matters, you may want to register to the CVML email list, following instructions in <https://lists.auth.gr/sympa/info/cvml> https://lists.auth.gr/sympa/info/cvml <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campai gn=sig-email&utm_content=emailclient&utm_term=icon> Virus-free. <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campai gn=sig-email&utm_content=emailclient&utm_term=link> www.avast.com

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GrAPL 2020 - Virtual Event - Call for Participation
by Tumeo, Antonino 15 May '20

15 May '20

[Please accept our apologies for multiple postings.] CALL FOR PARTICIPATION ******************************************************************************* GrAPL 2020: Workshop on Graphs, Architectures, Programming, and Learning https://hpc.pnl.gov/grapl/ May 18, 2020 8AM – 10AM PDT IMPORTANT: This year, GrAPL will hold two LIVE 45 minute Q&A sessions with the authors of the accepted papers and invited talks according to the schedule below. Papers and static presentations for the entire conference including the GrAPL Workshop will be made available to all conference registrants by Friday May 15th. Register for free at the IPDPS website (http://www.ipdps.org) to get instructions on how to access to this content. In addition, links to 3-5 minute lightning talks by the workshop speakers will be found at the GrAPL website (https://hpc.pnl.gov/grapl/) by May 15th. To attend the Zoom Sessions, we ask participants to register in advance at the following link: https://tinyurl.com/grapl2020 The organizing committee will then provide the link to the session. ****************************************************************************** Program for May 18th: 0800 – 0845 (PDT): Session 1 Welcome message. Algorithms and Applications Kronecker Graph Generation with Ground Truth for 4-Cycles and Dense Structure in Bipartite Graphs Trevor Steil (University of Minnesota), Scott McMillan (SEI, Carnegie Mellon University), Geoffrey Sanders (LLNL), Roger Pearce (LLNL), Benjamin Priest (LLNL) A scalable graph generation algorithm to sample over a given shell distribution M. Yusuf Özkaya (Georgia Institute of Technology), Muhammed Fatih Balin (Georgia Institute of Technology), Ali Pinar (SNL), Ümit V. Çatalyürek (Georgia Institute of Technology) An incremental GraphBLAS solution for the 2018 TTC Social Media case study Márton Elekes (Budapest University of Technology and Economics), Gábor Szárnyas (Budapest University of Technology and Economics) Linear Algebraic Louvain Method in Python Tze Meng Low (Carnegie Mellon University), Daniele Spampinato (Carnegie Mellon University), Scott McMillan (SEI, Carnegie Mellon University), Michel Pelletier (FPX, LLC) 0900 – 0945 (PDT): Session 2 Keynote - The GraphIt Universal Graph Framework: Achieving High-Performance across Algorithms, Graph Types and Architectures Saman Amarasinghe (Massachusetts Institute of Technology) API's and Implementations Parallelizing Maximal Clique Enumeration on Modern Manycore Processors Jovan Blanuša (IBM Research - Zürich, EPFL), Radu Stoica (IBM Research - Zürich), Paolo Ienne (EPFL), Kubilay Atasu (IBM Research - Zürich) A Roadmap for the GraphBLAS C++ API Benjamin A. Brock (UC Berkeley), Aydın Buluç (LBNL), Timothy G. Mattson (Intel), Scott McMillan (SEI, Carnegie Mellon University), José E. Moreira (IBM) Considerations for a Distributed GraphBLAS API Benjamin A. Brock (UC Berkeley), Aydın Buluç (LBNL), Timothy G. Mattson (Intel), Scott McMillan (SEI, Carnegie Mellon University), José E. Moreira (IBM), Roger Pearce (LLNL), Oguz Selvitopi (LBNL), Trevor Steil (University of Minnesota) 75,000,000,000 Streaming Inserts/Second Using Hierarchical Hypersparse GraphBLAS Matrices Jeremy Kepner (MIT Lincoln Laboratory) ****************************************************************************** GrAPL is the result of the combination of two IPDPS workshops: GABB: Graph Algorithms Building Blocks GraML: Workshop on The Intersection of Graph Algorithms and Machine Learning SUMMARY ------- Data analytics is one of the fastest growing segments of computer science. Many real-world analytic workloads are a mix of graph and machine learning methods. Graphs play an important role in the synthesis and analysis of relationships and organizational structures, furthering the ability of machine-learning methods to identify signature features. Given the difference in the parallel execution models of graph algorithms and machine learning methods, current tools, runtime systems, and architectures do not deliver consistently good performance across data analysis workflows. In this workshop we are interested in graphs, how their synthesis (representation) and analysis is supported in hardware and software, and the ways graph algorithms interact with machine learning. The workshop’s scope is broad and encompasses the wide range of methods used in large-scale data analytics workflows. This workshop seeks papers on the theory, model-based analysis, simulation, and analysis of operational data for graph analytics and related machine learning applications. In particular, we are interested, but not limited to the following topics: • Provide tractability and performance analysis in terms of complexity, time-to-solution, problem size, and quality of solution for systems that deal with mixed data analytics workflows; • Discuss the problem domains and problems addressable with graph methods, machine learning methods, or both; • Discuss programming models and associated frameworks such as Pregel, Galois, Boost, GraphBLAS, GraphChi, etc., for building large multi-attributed graphs; • Discuss how frameworks for building graph algorithms interact with those for building machine learning algorithms; • Discuss hardware platforms specialized for addressing large, dynamic, multi-attributed graphs and associated machine learning; Besides regular papers, short papers (up to four pages) describing work-in-progress or incomplete but sound, innovative ideas related to the workshop theme are also encouraged. ORGANIZATION ------------ General co-Chairs: Scott McMillan (CMU SEI), smcmillan(a)sei.cmu.edu Manoj Kumar (IBM), manoj1(a)us.ibm.com Program Chairs: Danai Koutra (University of Michigan, Ann Arbor), dkoutra(a)umich.edu Mahantesh Halappanavar (PNNL), hala(a)pnnl.gov GrAPL's Little Helpers: Tim Mattson (Intel) Antonino Tumeo (PNNL) Program Committee: Nesreen K Ahmed, Intel Research and Intel AI, USA Sasikanth Avancha, Intel Labs - Parallel Computing Lab, India Aydin Buluç, Lawrence Berkeley National Lab, USA Timothy A. Davis, University of Florida, USA Jana Doppa, Washington State University, USA John Gilbert, University of California at Santa Barbara, USA Sergio Gómez, Universitat Rovira i Virgili, Catalonia Will Hamilton, McGill University, Mila, Canada Stratis Ioannidis, Northeastern University, Boston, USA Bharat Kaul, Intel Labs - Parallel Computing Labs, India Kamesh Madduri, The Pennsylvania State University, USA Henning Meyerhenke, Humboldt University of Berlin, Germany Indranil Roy, Natural Intelligence, USA Robert Rallo, Pacific Northwest National Lab, USA P. Sadayappan, University of Utah, USA Yizhou Sun, University of California, Los Angeles, USA Flavio Vella, Free University of Bozen, Italy Steering Committee: David A. Bader (New Jersey Institute of Technology) Aydın Buluç (LBNL) John Feo (PNNL) John Gilbert (UC Santa Barbara) Tim Mattson (Intel) Ananth Kalyanaraman (Washington State University) Jeremy Kepner (MIT Lincoln Laboratory) Antonino Tumeo (PNNL)

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FIRST INTERNATIONAL WORKSHOP ON LEVERAGING MACHINE LEARNING IN PROCESS MINING ML4PM 2020 - 5 OCTOBER, 2020 - PADUA, ITALY
by Paolo Ceravolo 14 May '20

14 May '20

FIRST INTERNATIONAL WORKSHOP ON LEVERAGING MACHINE LEARNING IN PROCESS MINING ML4PM 2020 - 5 OCTOBER, 2020 - PADUA, ITALY http://ml4pm2020.di.unimi.it AN ACTIVITY FROM THE IEEE TASK FORCE ON PROCESS MINING ON THE INTERNATIONAL CONFERENCE ON PROCESS MINING (https://icpmconference.org/2020/) ## About ML4PM The interest in Machine Learning applications in Process Mining has seen increasing growth in the last few years along with the relevance of the ICPM conference. Thus, this workshop offers a focused environment to discuss new approaches, applications and their results to a wide audience, composed of researchers and practitioners. ML4PM will be held in online (due to covid-19), in conjunction with the ICPM conference. ### Call for Papers This workshop invites papers that present works that lay in the intersection between machine learning and process mining. The event provides a suitable environment to discuss new approaches presented by researchers and practitioners. Main themes include automated process modeling, predictive process mining, application of deep learning techniques and online process mining. The workshop will count with leading researchers, engineers and scientists who are actively working on these topics. Full papers must be written in English, not exceed 12 pages and must be an original contribution, not previously published or under review. Workshop papers will be published by Springer as a post-workshop proceedings volume in the series Lecture Notes in Business Information Processing (LNBIP). ### Virtual conference Due to the exceptional circumstances of the COVID-19 outbreak, ICPM 2020 will be a fully virtual conference, with no travel involved. However, the entire program, including the co-located events, will be retained, and will not change. With the spirit of keeping the entire conference as interactive as possible, presentations will be given live using webinars. The presentations will also be broadcasted, and also available after the conference for off-line viewing. Attendees will be able to ask questions, which will be answered at the end of the each presentation. When multiple sessions run in parallel (e.g., workshops), the conference will feature parallel virtual rooms. ### Topics Topics of interest for submission include, but are not limited to: * Outcome and time prediction * Classification and clusterization of business processes * Application of Deep Learning for PM * Stream mining for online process environments * Anomaly detection for PM * Natural Language Processing and Text Mining for PM * Multi-perspective analysis of processes * Machine Learning for robot process automation * Automated process modeling and updating * Conformance checking based on Machine Learning * Transfer Learning applied to business processes * IoT business services leveraged by Machine Learning * Multidimensional Process Mining * Predictive Process Mining * Prescriptive Learning in Process Mining * Convergence of Machine Learning and Blockchain in Process Mining ### Submission Guidelines Submissions must use the Springer LNCS/LNBIP format (https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu…) Submissions must be in English and cannot exceed 12 pages (including tables, figures, the bibliography and appendices). Each paper should clarify the relation of the paper to the workshop’s main topics, clearly state the problem being addressed, the goal of the work, the results achieved, and the relation to other work. Submissions must be original contributions that have not been published previously, nor already submitted to other conferences or journals in parallel with this workshop. Accepted papers will be presented during one of the workshop’s sessions and one author of each accepted paper must register and participate in the workshop. ### Important Dates Abstract Submission: August 18 2020 Paper Submission: August 25 2020 Notification of Acceptance: September 14 2020 Submission of Camera Ready Papers: September 22 2020 Workshop: October 5 2020 ## Organizers * Paolo Ceravolo, Università degli Studi di Milano, Italy (https://orcid.org/0000-0002-4519-0173) * Sylvio Barbon Jr., State University of Londrina, Brazil (https://orcid.org/0000-0002-4988-0702) * Annalisa Appice, Università degli Studi di Bari, Italy (https://orcid.org/0000-0001-9840-844X) ### Program Committee María Teresa Gómez, University of Seville Rafael Accorsi, PwC Digital Services Niek Tax, Booking.com Josep Carmona, Universitat Politècnica de Catalunya Ernesto Damiani, Khalifa University of Science Technology Chiara Di Francescomarino, Fondazione Bruno Kessler Antonella Guzzo, Università della Calabria Mariangela Lazoi, University of Salento Matthias Ehrendorfer, University of Vienna Fabrizio Maria Maggi, University of Tartu Paola Mello, Università di Bologna Gabriel Marques Tavares, Università degli Studi di Milano Emerson Cabrera Paraiso, Pontifícia Universidade Católica do Paraná Bruno Bogaz Zarpelão, State University of Londrina Irene Teinemaa, Booking.com Michelangelo Ceci, University of Bari Aldo Moro Natalia Sidorova, Eindhoven University of Technology

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Postdoc position at UGR: Marie Skłodowska-Curie fellowship in Automation of Systematic Reviews
by Juan Manuel Fernández Luna 11 May '20

11 May '20

The University of Granada, Spain, and more specifically its Department of Computer Science and Artificial Intelligence offers a Marie Skłodowska-Curie individual European fellowship on the automation of systematic reviews using Artificial Intelligence. Published biomedical research needs to be synthesised for health practitioners. This currently takes too long to contemporaneously enhance health care quality because the methods of evidence synthesis that bring together published studies to underpin guidance for practice have well recognised, serious delays taking on average 5 staff members over 12 months to complete a review. We postulate that artificial intelligence (AI) can assist in evidence synthesis, improving the timeliness of guidelines. The objective of this project is, using beyond state-of-the-art AI methodology, develop an integrated system using modern AI technologies to support the complete process of systematic reviews. We will validate the performance the AI-based system quantifying its accuracy, precision, heterogeneity, bias and generalizability compared to a standard meta-analysis. We wish to form an international consortium of well-established researchers with individually distinctive track records in computer science, systematic review, study quality assessment, meta-analysis, evidence grading, public health, cardiometabolic research, and various forms of evidence synthesis including both randomized and real-world data. This will allow the delivery of a much-needed, exciting, ground breaking, high-quality and impactful project. Our output will help accelerate the process of meta-analyses, evidence synthesis and transfer of research into guidelines for improving the quality of health care. So we are looking for an experienced researcher with a PhD in Computer Science, with a strong background in Information Retrieval, Machine Learning, Natural Language Processing and Text Mining to be integrated in a friendly and strong research group. She/he will collaborate with a multidisciplinary team in order to automating several of the stages of systematic reviews, where all these previously disciplines must be involved. The candidate will work and live at the beautiful city of Granada, at southern Spain. Those interested candidates should send a letter of interest and presentation (including the reasons why she/he would be interested in this position, her/his possible contributions to the research and skills) to Juan Manuel Fernández Luna (jmfluna <at> decsai.ugr.es) in addition to her/him CV. After a first selection from all the CVs, the selected candidate will work with the members of the research team to elaborate a successful proposal. More information about the fellowship is in the following link: https://euraxess.ec.europa.eu/jobs/hosting/msca-if-joint-application-univer… And about the call in this one: *https://ec.europa.eu/research/mariecurieactions/actions/individual-fellowships_en * ----------- Juan M. Fernández Luna Department of Computer Science and Artificial University of Granada, Spain.

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