- computational.science - lists.iccsa.org

PhD in formal methods and security, cotutelle France-Scotland
by Barbara Fila (Kordy) 25 Mar '20

25 Mar '20

We have a fully-funded three-year PhD position in formal methods for information security. This is a joint doctorate (cotutelle) between IRISA (Rennes, France) and Heriot-Watt University (Edinburgh, Scotland). The student will obtain a PhD degree from both universities. For more details, see http://people.irisa.fr/Barbara.Kordy/vacancies.php The deadline for applications is Friday, May 15, 2020, but applications will be considered until the position is filled. For all inquiries please contact Barbara Fila (barbara.fila(a)irisa.fr) and Saša Radomirović (sasa.radomirovic(a)hw.ac.uk) With kind regards, Barbara ---------------------- http://people.irisa.fr/Barbara.Kordy/

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CFP: Special Issue "Modeling and Analysis of Data-Driven Systems through Computational Neuroscience" with Hindawi's Computational Intelligence and Neuroscience
by Computational Science Mailing List 24 Mar '20

24 Mar '20

[Apologies for Multiple Emails] Please consider submitting your manuscript to the special issue of "Modeling and Analysis of Data-Driven Systems through Computational Neuroscience" with Hindawi's Computational Intelligence and Neuroscience. Theme of this special issue: Artificial intelligence(AI)based application systems are becoming the mainstream in the software industry and application domains such as computational neuroscience, bioinformatics, and healthcare. Recent advances in big data generation and management have created an avenue for decision makers to utilize these huge volumes of data for different purposes and analyses. AI-based application developers have long utilized conventional machine learning techniques to design better user interfaces and vulnerability predictions. However, with the advancement of deep learning-based and neural-based networks and algorithms, researchers are able to explore and learn more about data and their exposed relationships or hidden features. This new trend of developing data-driven application systems seeks the adaptation of computational neural network algorithms and techniques in many application domains, including software systems, cyber security, human activity recognition, and behavioral modeling. As such, computational neural networks algorithms can be refined to address problems in data-driven applications. This Special Issue aims to foster machine and deep learning approaches to data-driven applications, in which data governs the behavior of applications. Original research and review articles that consider how to model and build data-driven applications using computational neuroscience are encouraged. More specifically, it is of interest to learn how neuron networks can represent data-driven applications and their behaviors in order to extract key features. The Special Issue will enable researchers from academia and industry to share innovative applications and creative solutions to common problems when modeling neural-based applications in computational neuroscience and neuroengineering. Topics of Interest: Potential topics include but are not limited to the following: - Neural programming and coding in data-driven systems using machine and deep learning - Attention and learning of data-driven systems using neural memory networks - Neural-based mathematical formulation of information and data using machine and deep learning - Human perception, cognition, and decision making through neural networks - Human activity recognition through deep neural modeling - Modeling and prediction of human behavior using computational neuroscience techniques - Modeling human-computer interactions through neural networks - Modeling humanoid intelligent bots and mimicking human behavior using computational neuroscience techniques For more information regarding this special issue, please visit the following link: https://www.hindawi.com/journals/cin/si/696425/ Sincerely, Akbar Namin, The lead editor of this special issue.

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ICCSA 2020 workshop Advanced Transport Tools and Methods - A2TM deadline extension and coronavirus outbreak news
by Computational Science Mailing List 24 Mar '20

24 Mar '20

Dear Collegue, I hope to find yourself in good health. Inside the 20th International Conference on Computational Science and Its Application, to be held in Cagliari, Italy in July 1-4 2020, we organized the workshop: Advanced Transport Tools and Methods - A2TM http://www.iccsa.org/workshops The Local Organizing Commitee is doing a great job laying the foundation for a great conference. We are not experts on epidemics and, in order to be sure, it is better to observe the evolution of the phenomenon in order to take better decisions. For this reason we decided new deadlines: Â·Â Â Â Â Â Â full paper submission 26 April 2020 for our Workshop Transport and Mo, the sessions can have different deadlines; Â·Â Â Â Â Â Â notification of Acceptance 24 May 2020; Â·Â Â Â Â Â Â submission deadline for camera ready paper and registration 15 June 2020. In last days the submission flow increased a lot, this means that in all cases the proceedings (Springer LNCS) will be published. Due to the deadline extension, the volumes will be published after the conference. I hope that in the summer, with the hot temperatures of Sardinia, the situation will be solved, but in next weeks we will continue to analyse the evolution of the situation and we will inform you. Best regards, Massimiliano Petri and Antonio Pratelli

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CFP: Special Issue "Deep Learning for the Internet of Things" with MDPI Electronics
by Computational Science Mailing List 24 Mar '20

24 Mar '20

[Apologies for Duplicate Emails] Please consider submitting your manuscripts to the special issue on "Deep Learning for the Internet of Things" with MDPI Electronics The Special Issue Theme: The recent advancements in artificial intelligence; machine learning; and, more importantly, deep learning, with its many variations of algorithms and platforms, have radically transformed conventional software applications into a set of smart and connected components with the capability of data-driven decision-making; intelligent data sensing and filtering; proactive and collaborative integration of software and hardware devices; and, more importantly, the ability to capture tons of useful interaction data. Machine and deep learning-based components are becoming the backbone of modern systems such as cyber-physical systems (CPS) and Internet of Things (IoT), where intelligent integrations and collaborations of smart devices along with their outstanding data collection capabilities make them a perfect application domain for such sophisticated learning algorithms. The beauty of smart and connected devices governed by software utilities has already been demonstrated in several application domains such as healthcare, agriculture and farming, manufacturing, smart buildings, transportation, energy, and environmental surveillance monitoring systems. While these IoT-based systems can capture a good amount of data, the usage of these valuable and hard-to-produce data are not being fully utilized. Deep learning enables one to explore these data in further detail and capturing the hidden relationships that may exist among their key factors and parameters, thus providing further insight into the underlying application domains. Furthermore, deep learning algorithms are also capable of addressing challenging problems that are natural in IoT but remain unsolved in systems such as real time optimization problems, modeling non-linear characteristics of IoT devices and components, and several instances of prediction and classification problems. This Special Issue aims to foster deep learning-based modeling, solutions, and approaches to problems in Internet of Things systems. It seeks to explore deep learning algorithms, including generative adversarial models, attention-based networks, deep reinforcement learning, and recurrent deep neural networks, in capturing features and modeling the behavior of the involved software and hardware components. Topics of Interest: Academic researchers and industrial practitioners are invited to contribute their valuable research and experiences to state-of-the-art of deep learning-based approaches to modeling Internet of Things and associated problems. Topics of interest include but are not limited to the following applications of deep learning techniques to - Modeling IoT systems using deep learning; - Generative adversarial networks (GANS) in IoT and CPS; - Long short-term memory (LSTM) modeling of IoT time series data; - Attention-based approaches to capture significant features in IoT; - Deep learning-based modeling and experience in IoT-based applications such as smart building, healthcare, agriculture, manufacturing, left-driving cars, and cyber security; - Deep reinforcement learning for modeling decision making and uncertainty in IoT. For more information regarding this special issue, please visit the following link: https://www.mdpi.com/journal/electronics/special_issues/Deep_Learning_IoT Sincerely, Akbar Namin Guest Editor

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Ada-Europe Int'l Conference 2020 (AEiC 2020) cancelled!
by Computational Science Mailing List 21 Mar '20

21 Mar '20

----------------------------------------------------------------------- Notice of CANCELLATION 25th Ada-Europe International Conference on Reliable Software Technologies (AEiC 2020) www.ada-europe.org/conference2020 (was planned to be held 8-12 June 2020, Santander, Spain) #AdaEurope #AEiC2020 #AdaProgramming #ConferenceCancelled ----------------------------------------------------------------------- Saturday, 21 March 2020 The containment measures put in place on a world scale against the COVID-19 pandemic, which is affecting us all so severely, have taken precedence in everybody's personal and professional life. The consequent regulations issued by national governments and public health authorities in the regard of public gatherings, oblige us to cancel the Ada-Europe International Conference 2020 (AEiC 2020), scheduled for 8-12 June 2020, in Santander, Spain. Consequent to that obligation, the organizing committee and its principal sponsor Ada-Europe have made a number of decisions, which we wish to share with authors, sponsors, participants and any other interested parties. In regard to the calendar of events promoted by Ada-Europe: - Santander, Spain, will be the venue of the next Ada-Europe International Conference on Reliable Software Technologies in June 2021. - The venue originally earmarked for the 2021 edition of the AEiC, Ghent, Belgium, will be the prime candidate to host the 2022 edition of the conference. - Selected elements of the technical program of the 2020 conference program will be considered for presentation at an Ada event co-organized with the International Real-Time Ada Workshop (IRTAW 2020), now tentatively postponed to late October 2020, near Valencia, Spain. The details of that event will be announced in due course, contingent on the lifting of current sanitary restrictions. In regard to the elements of the 2020 conference program: - The processing of the Journal-track submissions continues seamlessly, with a view to ensuring prompt open-access publication to those that gain acceptance. The authors of the accepted papers will be invited to present their work at the 2021 conference. - The authors of the Industrial Presentations that are accepted after review will be invited to forward their work to the Ada User Journal for immediate publication. - The call for Work-in-Progress submissions is cancelled. The prospective authors are invited to forward their work to the Ada User Journal for consideration. We express our heartfelt friendship to all members of our community and their families in these difficult times, and look forward to the restoration of a safe normality. See you all soon! The Ada-Europe Board -----------------------------------------------------------------------

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E-courses on Computer vision, Machine Learning, Autonomous Systems, Image/Video Processing/Analysis, Human-Centered Computing
by Computational Science Mailing List 20 Mar '20

20 Mar '20

Dear Colleague/Professor, this message is sent to you, as several Universities switch to tele-education, in reaction to COVID-19 pandemic. As a result of my very long University teaching career, complemented by rich dissemination activities in many European funded R&D projects, we have developed a long list of educational material (100+ 1-hour lecture ppts, more under development) and student assessment tools that allow tele-education of one or more of the following senior undergraduate/MSc/PhD full-semester courses: 1) Computer Vision 2) Machine Learning 3) Autonomous Systems 4) Image Processing and Analysis 5) Video Processing and Analysis 6) Human-Centered Computing 7) Social Media Analysis. As an example, the Computer Vision course lecture list is attached (final lecture list from parts A-E can be configured, depending on University rules/priorities). The lecture list of the rest of the courses can be sent upon request. A multitude of other courses can be devised, matching special education needs of any University. Any of these courses can be delivered upon request in various formats (e.g., intensive e-short course, regular e-course with weekly lectures) using tele-education tools (typically Skype for Business) to any audience that has appropriate background (typically senior undergraduate/MSc/PhD students of ECE/CS/EE departments, or other Science/Engineering departments). Educational material can also be delivered to be used by other Professors, upon request Sample educational material can be sent upon request. A lecture example can be found in: http://icarus.csd.auth.gr/wp-content/uploads/2019/12/Fast-convolution-algor… Sincerely yours I. Pitas 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. He served as a Visiting Professor at several Universities. His current interests are in the areas of image/video processing, 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 30500+ citations to his work and h-index 81+ (Google Scholar). Prof. Pitas leads the big European H2020 R&D project MULTIDRONE: https://multidrone.eu/. He is chair of the IEEE Autonomaous Systems Initiative https://ieeeasi.signalprocessingsociety.org/ https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=en Computer vision lecture list Part A Mathematical foundations of computer vision Mathematical analysis fundamentals Linear algebra fundamentals Geometry fundamentals Part B Image/video acquisition and analysis Introduction to computer vision Digital images and videos Image acquisition Color theory Image/video perception Image registration Edge detection Region segmentation Texture description Image topology 2D shape description and recognition Motion estimation Object detection Object tracking Part C 3D Computer Vision Camera geometry Stereo and Multiview imaging Structure from Motion 3D object Localization and Mapping Semantic 3D world mapping 3D object localization Multiview object detection and tracking Object pose estimation Part D 3D Imaging 3D (volumetric) image processing 3D image geometry and topology 3D image segmentation 3D shape analysis Part E Applications Autonomous systems perception (cars/drones) Human centered computing (face detection, recognition, facial expression recognition, activity recognition) Medical imaging (CT/MRI/X-ray/ultrasonic image/volume analysis, medical image registration)

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CFP: Resilience@Euro-Par 2020 - Papers due May 8
by Computational Science Mailing List 19 Mar '20

19 Mar '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> 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> - 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: May 8, 2020 - Workshop author notification: June 30, 2020 - Workshop author registration: TBA - Workshop paper (for informal workshop proceedings): July 10, 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 _________________________________________________________________________ Thomas Naughton naughtont(a)ornl.gov Research Associate (865) 576-4184

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CfPapers: European Dependable Computing Conference - EDCC 2020
by Computational Science Mailing List 19 Mar '20

19 Mar '20

***Submission deadline extension to April 8th (abstract) and April 15th (full paper)*** The 16th European Dependable Computing Conference - EDCC 2020 September 7-10, 2020, Munich, Germany Call for Papers The European Dependable Computing Conference is a leading venue for presenting and discussing the latest research, industrial practice and innovations in dependable and secure computing. The European Dependable Computing Conference is a unique forum for researchers and practitioners to present and discuss their latest research results on theory, techniques, systems, and tools for the design, validation, operation and evaluation of dependable and secure computing systems. The conference will cover a broad range of topics related to dependability and security, which includes, but is not limited to: * Hardware and software architectures of dependable systems; * Model-driven and formal engineering approaches; * Fault-tolerant networks & ultra-reliable low-latency communication; * Dependability modelling and tools; * Verification and validation methods; * Development of safety and security-critical systems; * Dependability and security of o critical infrastructures, e.g. smart energy grids, intelligent transportation systems, smart cities; o cyber-physical systems and (industrial) IoT; o cloud, fog, and edge computing systems; o data analytics applications & systems based on machine learning and artificial intelligence; o databases and distributed ledgers (incl. block chains); o artificial intelligence-based systems and components * Data protection and data privacy The conference is inviting submissions to its different tracks in the following categories: -Regular papers (up to 8 pages) solicited on theory, techniques, systems, and tools for the design, validation, operation and evaluation of dependable and secure computing systems, covering any fault model, from traditional hardware and software faults to accidental and malicious human interactions. -Practical experience reports (up to 6 pages) dedicated to dependability in practice: industrial applications, experience in introducing dependability in industry, use of new or mature dependability approaches to new challenging problems or domains, etc. -Short papers (3-4 pages) describing preliminary research work (position papers) or a prototype/tool description, outlining the design or implementation of a software tool, or the prototyping of an operational system. The papers submitted to the conference should present an original contribution and formatted according to IEEE style: https://www.ieee.org/conferences/publishing/templates.html. All submissions must be made electronically through the EasyChair submission web page, and should clearly indicate in which category the paper is being submitted. Detailed indications about the paper format are provided in the paper submission page: http://edcc.dependability.org/papersubmission.html Best Paper Award Submissions will be judged on originality, significance, correctness and impact. Three distinguished papers will be selected among accepted papers and presented in a dedicated session of the conference program. Full research papers and practical experience reports are eligible for the distinction. Important Dates: Abstract Submission: (March 17, 2020) - new: April 8, 2020 Full Paper Submission: (March 24, 2020) - new: April 15, 2020 Author Notification: (May 25, 2020) - new: June 1, 2020 Camera-ready Paper: June 22, 2020 General chairs: Michael Paulitsch, Intel Mario Trapp, Fraunhofer Program Committee chair: Elena Troubitsyna, KTH Sweden Publicity chair: Alexander Romanovsky, Newcastle University Publication chair: Miguel Pardal, Universidade de Lisboa Students Forum chair: Marcello Cinque, Frederico II University of Naples For more information, visit: http://edcc.dependability.org/

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Computational and Applied Statistics at ICCSA 2020 - special extended deadline
by Computational Science Mailing List 17 Mar '20

17 Mar '20

Dear Colleague, I hope you are well, beyond the hardships that everyone, in every part of the world, is experiencing. Taking into account the exceptional situation that the whole world is going through, the dates related to submission and decision-making on articles submitted to the 7th edition of the Computational and Applied Statistics (CAS2020) (https://cas2020.webnode.com/) workshop have been changed. The new deadline for paper submission is April 26, 2020. *********************************************************************** ****************** APOLOGIES FOR MULTIPLE COPIES RECEIVED *************** *********************************************************************** ********************* CAS 2020 CALL FOR PAPERS ************************** ********************* NEW deadline: April 26, 2020 ******************** Computational and Applied Statistics (CAS 2020<https://cas2020.webnode.com/>) Workshop of the 20th International Conference on Computational Science and Applications (ICCSA 2020, http://www.iccsa.org/) will be held on July 1 - 4, 2020 in Cagliari, Italy. TOPICS ====== The aim of CAS workshop is to bring together scientists working in computational statistics, scientific computation and applications in all areas of sciences, engineering, industry, economics, life sciences and social sciences. Topics of interest include (but are not limited to): * Computational Statistics: new issues in the design of computational algorithms for implementing statistical methods, development in R, etc * Applications: statistical case study in all areas of sciences, engineering and industry, including economics, medicine, biology, earth sciences and social sciences. IMPORTANT DATES (NEW) ====================== April 26, 2020: Deadline for abstract and paper submission to the CAS Workshop. May 24, 2020: Notification of Acceptance June 15, 2020: Early-bird Registration ends June 15, 2020: Submission deadline for the final version of the Proceeding Papers July 1-4, 2020: ICCSA 2020 Conference. PROCEEDINGS ============ The proceedings of the CAS 2020 Workshop will appear in the Springer-Verlag, Lecture Notes in Computer Science (LNCS) series. The paper must be camera-ready, between 10 and 16 pages long and formatted according to the LNCS rules SUBMISSION DETAILS ================== All accepted papers will be included in the Springer Lecture Notes in Computer Science (LNCS, http://www.springer.com/gp/computer-science/lncs ) series and indexed by Scopus, EI Engineering Index, Thomson Reuters Conference Proceedings Citation Index (included in ISI Web of Science), and several other indexing services. The papers will contain linked references, XML versions and citable DOI numbers. Submitted papers will be subject to stringent peer review by at least three experts and carefully evaluated based on originality, significance, technical soundness, and clarity of exposition. The authors can submit abstracts and papers to your session accessing the electronic submission site: http://ess.iccsa.org/ You can find the instructions to prepare and submit papers on the web site: http://www.iccsa.org/instructions-for-authors If you are not registered, you must to register before the submission. From the personal page the author is able to submit first an abstract (phase 1), then a full paper (phase 2), selecting the session from the list of sessions in the submission forms. The author will be able to update the paper until the submission deadline. ORGANIZER =========== * Ana Cristina Braga (acb(a)dps.uminho.pt<mailto:acb@dps.uminho.pt>), Dep. of Production and Systems (University of Minho), Algoritmi Research Centre (University of Minho), Portugal. If you have some doubts or problems, do not hesitate to contact the organizer. Best regards, Ana Cristina Braga (CAS 2020 organizer)

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Call For Papers - IEEE International Conference on High Performance Computing, Data, and Analytics 2020
by Computational Science Mailing List 11 Mar '20

11 Mar '20

********************************************************************** We apologize if you received multiple copies of this Call for Papers Please feel free to distribute it to those who might be interested ********************************************************************** HiPC 2020 CALL FOR PAPERS ********************************************************************* 27th IEEE International Conference on High Performance Computing, Data, and Analytics 16--19 December, 2020 in Pune India https://hipc.org/ PROGRAM CHAIRS HPC: Bora Uçar, CNRS and ENS Lyon, France Data Science: Gagan Agrawal, Augusta University, USA PROGRAM VICE-CHAIRS HPC TRACKS Algorithms: Kamesh Madduri, Pennsylvania State University, USA Applications: Yogesh Simmhan, Indian Institute of Science, India Architecture: Biswabandan Panda, IIT Kanpur, India System Software: Marco Aldinucci, University of Torino, Italy DATA SCIENCE TRACKS Scalable Algorithms and Analytics: Bingsheng He, National University of Singapore Scalable Systems and Software: Suren Byna, Lawrence Berkeley National Laboratory, USA HiPC 2020 Call For Papers HiPC 2020 will be the 27th edition of the IEEE International Conference on High Performance Computing, Data, Analytics and Data Science. HiPC serves as a forum to present current work by researchers from around the world as well as highlight activities in Asia in the areas of high performance computing and data science. The meeting focuses on all aspects of high performance computing systems, and data science and analytics, and their scientific, engineering, and commercial applications. Authors are invited to submit original unpublished research manuscripts that demonstrate current research in all areas of high performance computing, and data science and analytics, covering all traditional areas and emerging topics including from machine learning, big data analytics and blockchain. Each submission should be submitted to one of the tracks listed under the two broad themes of High Performance Computing and Data Science. Up to two best paper awards will be given for outstanding contributed papers. HIGH PERFORMANCE COMPUTING Algorithms. This track invites papers that describe original research on developing new parallel and distributed computing algorithms, and related advances. Examples of topics that are of interest include (but not limited to): * New parallel and distributed algorithms and design techniques; * Advances in enhancing algorithmic properties or providing guarantees (e.g., fault tolerance, resilience, concurrency, data locality, communication-avoiding); * Algorithmic techniques for resource allocation and optimization (e.g., scheduling, load balancing, resource management); * Provably efficient parallel and distributed algorithms for advanced scientific computing and irregular applications (e.g., numerical linear algebra, graph algorithms, computational biology); * Classical and emerging computation models (e.g., parallel/distributed models, quantum computing, neuromorphic and other bioinspired models). Architecture. This track invites papers that describe original research on the design and evaluation of high performance computing architectures, and related advances. Examples of topics of interest include (but not limited to): * High performance processing architectures (e.g., reconfigurable, system-on-chip, manycores, vector processors); * Networks for high performance computing platforms (e.g., interconnect topologies, network-on-chip); * Memory, cache and storage architectures (e.g., 3D, photonic, Processing-In-Memory, NVRAM, burst buffers, parallel I/O); * Approaches to improve architectural properties (e.g., energy/power efficiency, reconfigurable, resilience/fault tolerance, security/privacy); * Emerging computational architectures (e.g., quantum computing, neuromorphic and other bioinspired architectures). Applications. This track invites papers that describe original research on the design and implementation of scalable and high performance applications for execution on parallel, distributed and accelerated platforms, and related advances. Examples of topics of interest include (but not limited to): * Shared and distributed memory parallel applications (e.g., scientific computing, simulation and visualization applications, graph and irregular applications, data-intensive applications, science/engineering/industry applications, emerging applications in IoT and life sciences, etc.); * Methods, algorithms and optimizations for scaling applications on peta- and exa-scale platforms (e.g., co-design of hardware and software, heterogeneous and hybrid programming); * Hardware acceleration of parallel applications (e.g., GPUs, FPGA, vector processors, manycore); * Application benchmarks and workloads for parallel and distributed platforms. Systems Software. This track invites papers that describe original research on the design, implementation and evaluation of systems software for high performance computing platforms, and related advances. Examples of topics of interest include (but not limited to): * Scalable systems and software architectures for high performance computing (e.g., middleware, operating systems, I/O services); * Techniques to enhance parallel performance (e.g., compiler/runtime optimization, learning from application traces, profiling); * Techniques to enhance parallel application development and productivity (e.g., Domain-Specific Languages, programming environments, performance/correctness checking and debugging); * Techniques to deal with uncertainties, hardware/software resilience, and fault tolerance; * Software for cloud, data center, and exascale platforms (e.g., middleware tools, schedulers, resource allocation, data migration, load balancing); * Software and programming paradigms for heterogeneous platforms (e.g., libraries for CPU/GPU, multi-GPU clusters, and other accelerator platforms). DATA SCIENCE Scalable Algorithms and Analytics. This track invites papers that describe original research on developing scalable algorithms for data analysis at scale, and related advances. Examples of topics of interest include (but not limited to): * New scalable algorithms for fundamental data analysis tasks (supervised, unsupervised learning, and pattern discovery); * Scalable algorithms that are designed to address the characteristics of different data sources and settings (e.g., graphs, social networks, sequences, data streams); * Scalable algorithms and techniques to reduce complexity of large-scale data (e.g., streaming, sublinear data structures, summarization, compressive analytics); * Scalable algorithms that are designed to address requirements in different data-driven application domains (e.g., life sciences, business, agriculture); * Scalable algorithms that ensure the transparency and fairness of the analysis; * Case studies, experimental studies and benchmarks for scalable algorithms and analytics; * Scaling and accelerating machine learning, deep learning and computer vision applications. Scalable Systems and Software. This track invites papers that describe original research on developing scalable systems and software for handling data at scale, and related advances. Examples of topics of interest include (but not limited to): * Design of scalable system software to support various applications (e.g., recommendation systems, web search, crowdsourcing applications, streaming applications) * Scalable system software for various architectures (e.g., OpenPower, GPUs, FPGAs). * Architectures and systems software to support various operations in large data frameworks (e.g., storage, retrieval, automated workflows, data organization, visualization, visual analytics, human-in-the-loop); * Systems software for distributed data frameworks (e.g., distributed file system, virtualization, cloud services, resource optimization, scheduling); * Standards and protocols for enhancing various aspects of data analytics (e.g., open data standards, privacy preserving and secure schemes). IMPORTANT DATES (2020) Abstract Submissions : June 8, 2020 Paper Submissions : June 15, 2020 Reviews for Rebuttals: August 4, 2020 Initial Submission Decisions: August 21, 2020 Revisions Due: September 22, 2020 Author Notifications: October 2, 2020 Camera Ready: October 16, 2020 Manuscript Guidelines Submitted manuscripts should be structured as technical papers and may not exceed ten (10) single-spaced double-column pages using 10-point size font on 8.5x11 inch pages (IEEE conference style), including figures, tables, and references. See style templates for details: •LaTex Package (ZIP) – will be linked •Word Package (ZIP) – will be linked Electronic submissions must be in the form of a readable PDF file. All manuscripts will be reviewed by the Program Committee and evaluated on originality, relevance of the problem to the conference theme, technical strength, rigor in analysis, quality of results, and organization and clarity of presentation of the paper. Authors are highly encouraged to list the key contributions of their paper, for example in a separate paragraph in the introduction of the paper. The review process is “single-blind” (i.e., authors can list their names on the paper), and that there will be a rebuttal period. 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, exceeding length limit, or not appropriately structured may also not be considered. Authors may contact the Program Chair at the email address below for further information or clarification. A published proceedings will be available at the conference. At least one author of each paper must be registered for the conference in order for the paper to be published in the proceedings. Presentation of an accepted paper at the conference in person is a requirement of publication. Any paper that is not presented at the conference will not be included in IEEE Xplore. Authors of selected high quality papers in HiPC 2020 will be invited to submit extended versions of their papers for possible publication in a special issue of Journal of Parallel and Distributed Computing. Submit your paper: https://easychair.org/conferences/?conf=hipc2020. __________________________________________________________________________ HiPC 2020 is co-sponsored by * IEEE Computer Society Technical Committee on Parallel Processing (TCPP) * HiPC Education Trust, India In cooperation with: * ACM Special Interest Group on Algorithms and Computation Theory (SIGACT); * ACM Special Interest Group on Computer Architecture (SIGARCH); * IFIP Working Group on Concurrent Systems; * Manufacturers' Association for Information Technology (MAIT); * National Association of Software and Service Companies (NASSCOM).

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