computational.science July 2017

computational.science@lists.iccsa.org

37 participants
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Call for Papers: ScalA@SC 2017 - Papers due August 28
by Engelmann, Christian 04 Nov '20

04 Nov '20

We apologize if you receive multiple copies of this notice. ----------------------------------------------------------------------------- ScalA’17: 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems held in conjunction with the SC17: The International Conference on High Performance Computing, Networking, Storage and Analysis in cooperation with ACM SIGHPC November 13, 2017, Denver, CO, USA <http://www.csm.ornl.gov/srt/conferences/Scala/2017> Novel scalable scientific algorithms are needed in order to enable key science applications to exploit the computational power of large-scale systems. This is especially true for the current tier of leading petascale machines and the road to exascale computing as HPC systems continue to scale up in compute node and processor core count. These extreme-scale systems require novel scientific algorithms to hide network and memory latency, have very high computation/communication overlap, have minimal communication, and have no synchronization points. Scientific algorithms for multi-petaflop and exa-flop systems also need to be fault tolerant and fault resilient, since the probability of faults increases with scale. Resilience at the system software and at the algorithmic level is needed as a crosscutting effort. Finally, with the advent of heterogeneous compute nodes that employ standard processors as well as GPGPUs, scientific algorithms need to match these architectures to extract the most performance. This includes different system-specific levels of parallelism as well as co-scheduling of computation. Key science applications require novel mathematical models and system software that address the scalability and resilience challenges of current- and future-generation extreme-scale HPC systems. Submission Guidelines Authors are invited to submit manuscripts in English structured as technical papers not exceeding 8 letter size (8.5in x 11in) pages including figures, tables, and references using the ACM format for conference proceedings. Submissions not conforming to these guidelines may be returned without review. Reference style files are available at <http://www.acm.org/sigs/publications/proceedings-templates>. All manuscripts will be reviewed and judged on correctness, originality, technical strength, and significance, quality of presentation, and interest and relevance to the workshop 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, exceeding length limit, or not appropriately structured may also not be considered. At least one author of an accepted paper must register for and attend the workshop. Authors may contact the workshop program chair for more information. Papers should be submitted electronically at: <https://easychair.org/conferences/?conf=scala17>. Full papers will be published with the SC'17 workshop proceedings in the ACM Digital Library and IEEE Xplore. Selected papers will be invited for an extended version in a special issue of the Journal of Computational Science (JoCS). Important Dates - Full paper submission: August 28, 2017 - Notification of acceptance: September 11, 2017 - Final paper submission (firm): October 9, 2017 - Workshop/conference early registration: TBD - Workshop: November 13, 2017 Topics of interest include, but are not limited to: - Novel scientific algorithms that improve performance, scalability, resilience, and power efficiency - Porting scientific algorithms and applications to many-core and heterogeneous architectures - Performance and resilience limitations of scientific algorithms and applications at scale - Crosscutting approaches (system software and applications) in addressing scalability challenges - Scientific algorithms that can exploit extreme concurrency (e.g. 1 billion for exascale by 2020) - Naturally fault tolerant, self-healing, or fault oblivious scientific algorithms - Programming model and system software support for algorithm scalability and resilience Workshop Chairs - Vassil Alexandrov, Barcelona Supercomputing Center, Spain - Al Geist, Oak Ridge National Laboratory, USA - Jack Dongarra, University of Tennessee, Knoxville, USA Workshop Program Chair - Christian Engelmann, Oak Ridge National Laboratory, USA Program Committee - Vassil Alexandrov, Barcelona Supercomputing Center, Spain - Hartwig Anzt, University of Tennessee, Knoxville, USA - Rick Archibald, Oak Ridge National Laboratory, USA - Franck Cappello, Argonne National Laboratory and University of Illinois at Urbana Champaign, USA - Zizhong Chen, University of California, Riverside, USA - James Elliott, Sandia National Laboratories, USA - Nahid Emad, University of Versailles SQ, France - Christian Engelmann, Oak Ridge National Laboratory, USA - Wilfried Gansterer, University of Vienna, Austria - Michael Heroux, Sandia National Laboratories, USA - Kirk E. Jordan, IBM T.J. Watson Research, USA - Dieter Kranzlmueller, Ludwig-Maximilians-University Munich, Germany - Ignacio Laguna, Lawrence Livermore National Laboratory, USA - Piotr Luszczek, University of Tennessee, Knoxville, USA - Michael Mascagni, Florida State University, USA - Ron Perrot, University of Oxford, UK - Yves Robert, ENS Lyon, France - Stuart Slattery, Oak Ridge National Laboratory, USA - Keita Teranishi, Sandia National Laboratories, USA -- Christian Engelmann, Ph.D. R&D Staff Scientist Computer Science Research Group Computer Science and Mathematics Division Oak Ridge National Laboratory Mail: P.O. Box 2008, Oak Ridge, TN 37831-6173, USA Phone: +1 (865) 574-3132 / Fax: +1 (865) 576-5491 e-Mail: engelmannc(a)ornl.gov / Home: www.christian-engelmann.info

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CFP: Resilience@Euro-Par 2017 - Papers due May 5
by Christian Engelmann 08 May '19

08 May '19

We apologize if you receive multiple copies of this call for papers. -------------------------------------------------------------------------------- 10th Workshop on Resiliency in High Performance Computing (Resilience) in Clusters, Clouds, and Grids <http://www.csm.ornl.gov/srt/conferences/Resilience/2017> in conjunction with the 23rd International European Conference on Parallel and Distributed Computing (Euro-Par), Santiago de Compostela, Spain, August 28 - September 1, 2017 <http://europar2017.usc.es> 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), and software complexity increases. Application correctness and execution efficiency, in spite of frequent faults, errors, and failures, is essential to ensure the success of the extreme-scale HPC systems, cluster computing environments, Grid computing infrastructures, and Cloud computing services. While a fault (e.g., a bug or stuck bit) is the cause of an error, its manifestation as a state change is considered an error (e.g., a bad value or incorrect execution), and the transition to an incorrect service is observed as a failure (e.g., an application abort or system crash). A failure in a computing system is typically observed through an application abort or a full/partial service or system outage. A detectable correctable error is often transparently handled by hardware, such as a single bit flip in memory that is protected with single-error correction double-error detection (SECDED) error correcting code (ECC). A detectable uncorrectable error (DUE) typically results in a failure, such as multiple bit flips in the same addressable word that escape SECDED ECC correction, but not detection, and ultimately cause an application abort. An undetectable error (UE) may result in silent data corruption (SDC), e.g., an incorrect application output. There are many other types of hardware and software faults, errors, and failures in computing systems. Resilience for HPC systems encompasses a wide spectrum of fundamental and applied research and development, including theoretical foundations, fault detection and prediction, monitoring and control, end-to-end data integrity, enabling infrastructure, and resilient solvers and algorithm-based fault tolerance. 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 2017 Website: <http://www.csm.ornl.gov/srt/conferences/Resilience/2017> - Resilience 2017 Submissions: <https://easychair.org/conferences/?conf=europar2017workshops> - Euro-Par 2017 website: <http://europar2017.usc.es> 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 - Fault detection and prediction: - Statistical analyses - Machine learning - Anomaly detection - Data and information collection - Visualization - Monitoring and control for resilience: - Platform and application monitoring - Response and recovery - RAS theory and performability - Application and platform knobs - Tunable fidelity and quality of service - End-to-end data integrity: - Fault tolerant design - Degraded modes - Forward migration and verification - Fault injection - Soft errors - Silent data corruption - Enabling infrastructure for resilience: - RAS systems - System software and middleware - Programming models - Tools - Next-generation architectures - Resilient solvers and algorithm-based fault tolerance: - Algorithmic detection and correction of hard and soft faults - Resilient algorithms - Fault tolerant numerical methods - Robust iterative algorithms - Scalability of resilient solvers and algorithm-based fault tolerance Important Dates: - Workshop papers due: May 5, 2017 - Workshop author notification: June 16, 2017 - Workshop early registration: TBD - Workshop paper (for informal workshop proceedings): July 21, 2017 - Workshop camera-ready papers: October 3, 2017 General Co-Chairs: - Stephen L. Scott Senior Research Scientist - Systems Research Team Tennessee Tech University and Oak Ridge National Laboratory, USA scottsl(a)ornl.gov - Chokchai (Box) Leangsuksun, SWEPCO Endowed Associate Professor of Computer Science Louisiana Tech University, USA box(a)latech.edu Program Co-Chairs: - Patrick G. Bridges University of New Mexico, USA bridges(a)cs.unm.edu - Christian Engelmann Oak Ridge National Laboratory , USA engelmannc(a)ornl.gov Program Committee: - Ferrol Aderholdt, Oak Ridge National Laboratory, USA - Dorian Arnold, University of New Mexico, USA - Rizwan Ashraf, Oak Ridge National Laboratory, USA - Wesley Bland, Intel Corporation, USA - Hans-Joachim Bungartz, Technical University of Munich, Germany - Franck Cappello, Argonne National Laboratory and University of Illinois at Urbana-Champaign, USA - Marc Casas, Barcelona Supercomputer Center, Spain - Zizhong Chen, University of California at Riverside, USA - Robert Clay, Sandia National Laboratories, USA - Miguel Correia, Universidade de Lisboa, Portugal - Nathan DeBardeleben, Los Alamos National Laboratory, USA - James Elliott, Sandia National Laboratories, USA - Kurt Ferreira, Sandia National Laboratories, USA - Michael Heroux, Sandia National Laboratories, USA - Saurabh Hukerikar, Oak Ridge National Laboratory, USA - Dieter Kranzlmueller, Ludwig-Maximilians University of Munich, Germany - Sriram Krishnamoorthy, Pacific Northwest National Laboratory, USA - Ignacio Laguna, Lawrence Livermore National Laboratory, USA - Scott Levy, University of New Mexico, USA - Kathryn Mohror, Lawrence Livermore National Laboratory, USA - Christine Morin, INRIA Rennes, France - Dirk Pflueger, University of Stuttgart, Germany - Nageswara Rao, Oak Ridge National Laboratory, USA - Alexander Reinefeld, Zuse Institute Berlin, Germany - Rolf Riesen, Intel Corporation, USA - Yves Robert, ENS Lyon, France - Thomas Ropars, Universite Grenoble Alpes, France - Martin Schulz, Lawrence Livermore National Laboratory, USA - Keita Teranishi, Sandia National Laboratories, USA -- Christian Engelmann, Ph.D. R&D Staff Scientist Computer Science Research Group Computer Science and Mathematics Division Oak Ridge National Laboratory Mail: P.O. Box 2008, Oak Ridge, TN 37831-6173, USA Phone: +1 (865) 574-3132 / Fax: +1 (865) 576-5491 e-Mail: engelmannc(a)ornl.gov / Home: www.christian-engelmann.info

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IEEE HPCS Workshop on High Performance Computing Systems for Bioinformatics and Life Sciences (BILIS 2017) - Ext Deadline
by Mario Cannataro 03 Oct '18

03 Oct '18

I apologize for any cross-posting of this announcement. ======================================================================================== Int. Workshop on High Performance Computing Systems for Bioinformatics and Life Sciences (BILIS 2017) http://hpcs2017.cisedu.info/conference/workshops---hpcs2017/workshop17-bilis July 17 – July 21, 2017 Genoa, Italy held in conjunction with International Conference on High Performance Computing & Simulation (HPCS 2017) http://hpcs17.cisedu.info/ ======================================================================================== * * * CALL FOR PAPERS * * * EXTENDED Submission Deadline: April 15, 2017 Submissions could be for full papers, short papers, poster papers, or posters ======================================================================================== IMPORTANT DATES Paper Submissions: --------------------------------- April 15, 2017 - Extended Acceptance Notification: --------------------------- April 28, 2017 Camera Ready Papers and Registration Due by: ------- May 11, 2017 Conference Dates: --------------------------------- July 17 – 21, 2017 ======================================================================================== SCOPE AND OBJECTIVES Incorporating new advancements of Information Technology (IT) in general and High Performance Computing (HPC) in particular in the domain of Life Sciences and Biomedical Research continues to receive tremendous attention of researchers, biomedical institutions and the rest of the biomedical community. Although medical instruments have benefited a great deal from the technological advances of the couple of decades, the impact of integrating IT advancements in addressing critical problems in biomedical research remains limited and the process of penetrating IT tools in the medical profession continues to be a very challenging problem. For example, the use of electronic medical records and Hospital Information Systems in improving health care remains fragmented. Similarly, the use of advanced computational tools seamlessly in the biomedical research cycle continues to be minimal. Due to the computational intensive problems in life sciences, the marriage between the Bioinformatics domain and high performance computing is critical to the advancement of Biosciences. In addition, the problems in this domain tend to be highly parallelizable and deal with large datasets, hence using HPC is a natural fit. The Bioinformatics domain is rich in applications that require extracting useful information from very large and continuously growing sequence of databases. Most methods used for analyzing DNA/Protein sequences are known to be computationally intensive, providing motivation for the use of powerful computational systems with high throughput characteristics. Moreover, high-throughput wet lab platforms such as next generation sequencing, microarray and mass spectrometry, are producing a huge amount of experimental "omics" data. The increasing availability of omics data poses new challenges to bioinformatics applications that need to face in a semi-automatic way an overwhelming availability of raw data. Main challenges regard: 1) the efficient storage, retrieval and integration of experimental data; 2) their efficient and high-throughput preprocessing and analysis; 3) the building of reproducible "in silico" experiments; 4) the integration of analysis results with pre-existing knowledge usually stored into ontologies. As the storage, preprocessing and analysis of raw experimental data is becoming the main bottleneck of the analysis pipeline, parallel computing is playing an important role in all steps of the life sciences research pipeline, from raw data management and processing, to data integration and analysis, and to data exploration and visualization. Moreover, Cloud Computing is becoming the key technology to hide the complexity of computing infrastructures, to reduce the cost of the data analysis task, and especially to change the overall business model of biomedical research and health provision. Considering the complex analysis pipeline of the biomedical research, the bottleneck is more and more moving toward the storage, integration, and analysis of experimental data, as well as their correlation and integration with publicly available data banks In such a scenario, large-scale distributed databases and parallel bioinformatics tools are key tools for organizing and exploring biological and biomedical data with the aim to discover new knowledge in biology and medicine. In the current Information age, further progress of Medical Sciences requires successful integration with Computational and Information Sciences. The workshop attempts to attract innovative ways of how such integration can be achieved via Bioinformatics and Biomedical Informatics research, particularly in taking advantage of the new advancements in HPC systems. The focus of data analysis and data mining tools in biomedical research highlights the current state of research in the key biomedical research areas such as bioinformatics, medical informatics and biomedical imaging. Addressing performance concerns in managing and accessing medical data, while facilitating the ability to integrate and correlate different biomedical databases remains an outstanding problem in biomedical research. The amount of available biomedical data continues to grow in an exponential rate; however, the impact of utilizing such resources remains minimal. The development of innovative tools in HPC environments to integrate, analyze and mine such data sources is a key step towards achieving large impact levels. The workshop focuses on topics related to the utilization of HPC systems and new models of parallel computing and cloud computing in problems related to Biomedical Informatics and Life Sciences, along with the use of data integration and data mining tools to support biomedical research and Health Care. The BILIS Workshop topics include (but are not limited to) the following: HPC for the Analysis of Biological Data Bioinformatics Tools for Health Care Parallel Algorithms for Bioinformatics Applications Ontologies in Biology and Medicine Integration and Analysis of Molecular and Clinical Data Parallel Bioinformatics Algorithms Algorithms and Tools for Biomedical Imaging and Medical Signal Processing Energy Aware Scheduling Techniques for Large Scale Biomedical Applications HPC for analyzing Biological Networks Next Generation Sequencing and Advanced Tools for DNA Assembly HPC for Gene, Protein/RNA Analysis and Structure Prediction Identification of Biomarkers Biomedical Visualization Tools Efficient Clustering and Classification Algorithms Correlation Networks in Biomedical Research Data Mining Techniques in Biomedical Applications Heterogeneous Data Integration HPC systems for Ontology and Database Integration Pattern Recognition and Search Tools in Biological and Clinical Databases Ubiquitous Medical Knowledge Discovery and Exchange HPC for Monitoring and Treatment Facilities Drug Design and Modeling Computer Assisted Surgery and Medical Procedures Remote Patient Monitoring, Homecare Applications Mobile and Wireless Healthcare and Biomedical Applications Cloud Computing for Bioinformatics, Medicine, and Health Systems INSTRUCTIONS FOR PAPER SUBMISSIONS You are invited to submit original and unpublished research works on above and other topics related to HPC for Bioinformatics, Healthcare and Life Sciences. Submitted papers must not have been published or simultaneously submitted elsewhere. 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), poster papers and posters (please refer to http://hpcs2017.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 workshop organizers via email as attachments to Hesham Ali: hali(a)unomaha.edu, Mario Cannataro: cannataro(a)unicz.it. Acknowledgement will be sent within 48 hours of submission. 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 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 2017 conference to present the paper at the workshop. PROCEEDINGS Accepted papers will be published in the Conference proceedings. Instructions for final manuscript format and requirements will be posted on the HPCS 2017 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 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 workshop, please contact the workshop organizers. IMPORTANT DATES Paper Submissions: ------------------------------------ April 15, 2017 - Extended Acceptance Notification: ------------------------------ April 28, 2017 Camera Ready Papers and Registration Due by: ---------- May 11, 2017 Conference Dates: ------------------------------------ July 17 – 21, 2017 WORKSHOP ORGANIZERS Prof. Hesham H. Ali Department of Computer Science College of Information Science and Technology University of Nebraska at Omaha Omaha, NE 68182 USA Email: hesham(a)unomaha.edu Prof. Mario Cannataro Department of Medical and Surgical Sciences University "Magna Græcia" of Catanzaro Viale Europa (Località Germaneto) 88100 Catanzaro, Italy Email: cannataro(a)unicz.it

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Machine Learning positions and PhD studentships available now
by Peter Bentley 31 Jul '17

31 Jul '17

FULL-TIME POSITIONS, PHD STUDENTSHIPS, & CONSULTANCY OPPORTUNITIES AT BRAINTREE LTD, LONDON, UK Braintree is looking to hire exceptional talent in machine learning immediately. The company encourages imaginative applicants who may wish a career in the development of innovative AI solutions. We have opportunities for: Data Scientists and Software Developers ======================================= You will join a dynamic team of developers and researchers who are leading the way in applied machine learning. You have the opportunity to tackle real problems and build systems in a range of domains, including: 1. retail (clustering/customer segmentation in large datasets) 2. fault prediction (large-scale multi variate analysis in time series data) 3. semantic networks of research papers (text/concept mining) 4. graph-native machine learning tools Essential qualifications and skills: + Degree in machine learning or related discipline (MSc and PhD preferred). + JAVA / C / Python to high standard + Quick learner + Good communication + Creative, independent, motivated, proactive + Experienced in machine learning Good to have experience in one or more of: + Statistical analysis of large datasets + Machine learning for big data + Neural networks, genetic algorithms, deep learning + Clustering (K-Means, SOM) + Natural language processing (Text mining) + Graph database (Neo4j) + Novel hardware, optimised architectures + User interface design Senior and junior positions available now. To apply, send your CV to p.bentley(a)cs.ucl.ac.uk or p.bentley(a)braintree.com, with Subject: Braintree Job Enquiry PhD Studentships ================ Braintree is offering full UK/EU funding for 3 PhD students in machine learning. Applicants should meet the entry requirements for UCL CS PhD programmes. Projects are available in the following areas: + graph-native machine learning + parallel architectures / optimised hardware for machine learning + analysis/visualisation of massive graphs + agent-based modelling + novel machine learning algorithm development + affective computing / social robots (other topics may be considered) Candidates must hold or expect to hold a UK first or upper second class honours degree, or equivalent qualification, in a discipline relevant to the project. Candidates will normally have relevant research experience gained through their Bachelor’s degree course, a Masters or work experience. At least two satisfactory academic or relevant work placement/employment references will be required. Students in receipt of a studentship offer will need to provide acceptable proof of legal right to study in the UK and satisfy the current requirements of UK Visa and Immigration. The offer of a Braintree studentship does not automatically confer an offer by UCL, whose application process must be followed in full. To apply, send your CV to p.bentley(a)cs.ucl.ac.uk or p.bentley(a)braintree.com, with Subject: Braintree PhD Studentship Enquiry Consultancy =========== Braintree needs expertise from world-class brains. If you are currently a PhD student, a postdoc researcher, or a member of academic staff, and you wish to have a side income by helping industry with their machine learning problems, Braintree will pay for your time as a consultant. If you can spare a couple of hours a week or a couple of days a month, you will also gain valuable real-world experience and make great contacts. Roles may optionally include travel to Europe, all expenses paid. We need consultants who have expertise in one or more of: + Machine learning for big data + Neural networks, genetic algorithms, deep learning + Natural language processing, Text Mining + Data architectures + Data Modelling for Graph databases (Neo4j) + Networking, server specification and setup + Large scale system architectures Applicants must be able to demonstrate expertise in their area with at least three recent publications in recognised international conferences or journals, and/or have more than 5 years work experience in a recognised centre of excellence. To apply, send your CV to p.bentley(a)cs.ucl.ac.uk or p.bentley(a)braintree.com, with Subject: Braintree Consultancy Enquiry ABOUT BRAINTREE LTD: ================== Braintree Ltd www.braintree.com <http://www.braintree.com/> is a Research and Development AI company based at 7 Gower St, London, UK (across the road from UCL). First created in 2002, it offers machine learning, optimisation, and analytics solutions to large multi-national organisations including governments, retailers, and the manufacturing industry. Since 2016, UCL researcher Peter Bentley has been CTO and Director of Braintree, bringing his UCL CS PhD students into the company, and forming close ties with UCL CS. Braintree has several contracts with industry and has just been awarded an Innovate UK grant to work with UCL CS on graph-based machine learning. The company has a culture of nurturing talent, encouraging personal growth, and allowing freedom for imaginative and creative problem-solvers. Come and join us!

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CFP: Special Issue on 'Software Defined Networking and Network Function Virtualization' in Scalable Computing and Communications (Springer)
by Javid Taheri 31 Jul '17

31 Jul '17

--------------------------------------------------------------------------------- Please accept our apologies if you receive multiple copies of this CFP --------------------------------------------------------------------------------- CALL FOR PAPERS Scalable Computing and Communications ~Special Issue Call for Papers~ Software Defined Networking and Network Function Virtualization IMPORTANT DATES: - Submission Deadline: 15 Dec 2017 - Notification of Acceptance: 31 March 2018 - Final Version: 31 May 2018 INTRODUCTION AND MOTIVATION With maturity of virtualization techniques, more and more services are to be run inside virtualized Data Centers vDCs) to further reduce Operational (OPEX) and Capital Expenditures (CAPEX). Aligned with the general trend of migrating traditional IT architectures to clouds (public or private), next generation of telecommunication networks such as 5G are also envisaged to be run on virtualized environments where network functions are deployed on virtual machines and/or containers instead of current proprietary equipment. Several proof-of-concept and initial industrial deployments proved that Software Defined Networking (SDN) and Network Function Virtualization (NFV) are two promising technologies to enable such technological shift. Nevertheless, how to optimize and guarantee the performance of such virtualized systems is still challenging, because they require accurate modelling and efficient optimization to satisfy ever increasing demand of future networks. To address several major issues raised by migrating network applications to virtualized infrastructures, this special issue aims to highlight challenges, state-of-the-art, and solutions to a set of currently unresolved key questions including, but not limited to: performance, modelling, optimizations, reliability, security, and techno-economic aspects of virtualized networks. By addressing these concerns, technology might be one step closer to understanding, and consequently, closing the gap between the performance of the next generation SDN/NFV-based networks and their current counterparts in proprietary boxes. In this special issue, we welcome contributions that can shed light onto any of the following questions: 1. How virtualized networks should be designed to guarantee the performance required by network operations? 2. How virtualized services can be benchmarked and/or compared? 3. How virtualized services should be designed and/or operated to take advantage of cloud infrastructures and further provide flexibilities (such as load migration) that current proprietary equipment cannot provide? 4. How network functions should be placed and/or network capacities should be sliced to optimize network critical metrics such as throughput, delay, jitter, etc.? 5. How virtualized services should/can be efficiently orchestrated, monitored, and managed? PAPER SUBMISSION: - Authors are encouraged to submit high-quality, original work that has neither appeared in, nor is under consideration by, other journals. - All papers will be reviewed following standard reviewing procedures for the Journal. - Papers must be prepared in accordance with the Journal guidelines: www.springer.com/41122 - Submit manuscripts to: http://SCAC.edmgr.com. Topics to be covered in this Special Issue are including, but not limited to: 1. Model, benchmark, and/or optimize operation of SDN/NFV-based networks and services. 2. Resource and/or content allocation for SDN/NFV-based networks and services. 3. Reliability and resiliency of SDN/NFV-based networks and services. 4. Dynamic/flexible construction and deployment of Service Function Chains using SDN/NFV technologies. 5. Fault detection and/or correction for SDN/NFV-based networks and services. 6. Architectures, applications, and use cases of SDN/NFV to provide networking services. 7. Monitoring techniques for SDN/NFV-based networks and services. 8. Deployment, management, and orchestration of SDN/NFV-based networks and services. 9. Business/economic aspects of SDN/NFV-based networks and services. 10. Security concerns of SDN/NFV-based networks and services. 11. Mobile and/or Wireless Networks enabled by SDN/NFV-based networks and services.

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CFP: 3rd Workshop on Heterogeneous High-performance Reconfigurable Computing (H2RC 2017) at SC17: Extended abstracts due Sept. 1
by Jason D. Bakos 29 Jul '17

29 Jul '17

========================================================================== ** Call for Papers ** ========================================================================== Third International Workshop on Heterogeneous High-performance Reconfigurable Computing (H2RC 2017) Held in conjunction with Supercomputing 2017 Friday Morning, November 17, 2017 Denver, CO http://h2rc.cse.sc.edu ========================================================================== Submission Deadline: September 1, 2017 (one page extended abstracts) ========================================================================== As conventional von-Neumann architectures are suffering from rising power densities, we are facing an era with power, energy efficiency, and cooling as first-class constraints for scalable HPC. FPGAs can tailor the hardware to the application, avoiding overheads and achieving higher hardware efficiency than general-purpose architectures. Leading FPGA manufacturers have recently made a concerted effort to provide a range of higher-level, easier to use high-level programming models for FPGAs. Such initiatives are already stimulating new interest within the HPC community around the potential advantages of FPGAs over other architectures. With this in mind, this workshop, now in its third year, brings together HPC and heterogeneous-computing researchers to demonstrate and share experiences on legacy and new high-level programming models, optimizations specific to scientific computing and data analytics, tools for performance/energy improvements, FPGA computing in the cloud, and popular applications for reconfigurable computing such as machine learning and big data. ========================================================================== Submissions (one page extended abstract): Submissions are solicited that explore the state of the art in the use of FPGAs in heterogeneous high-performance computing architectures and, at a system level, in data centers and supercomputers. FPGAs may be considered from either or both the distributed, parallel and composable fabric of compute elements or from their dynamic reconfigurability. We particularly encourage submissions which focus on the mapping of algorithms and applications to heterogeneous FPGA-based systems as well as the overall impact of such architectures on the compute capacity, cost, power efficiency, and overall computational capabilities of data centers and supercomputers. Submissions may report on theoretical or applied research, implementation case studies, benchmarks, standards, or any other area that promises to make a significant contribution to our understanding of heterogeneous high-performance reconfigurable computing and will help to shape future research and implementations in this domain. A non-comprehensive list of potential topics of interest is given below: 1. FPGAs in Supercomputer, Cloud and Data Center: FPGAs in relation to challenges to Cloud/Data Center/Supercomputing posed by the end of Dennard scaling 2. Supercomputing, Cloud and Data Center Applications: Exploiting FPGA compute fabric to implement critical cloud/HPC applications 3. Leveraging Reconfigurability: Using reconfigurability for new approaches to algorithms used in cloud/HPC applications 4. Benchmarks: Compute performance and/or power and cost efficiency for cloud/HPC with heterogeneous architectures using FPGAs 5. Implementation Studies: Heterogenous Hardware and Management Infrastructure 6. Programming Languages/Runtimes/OS/Tools/Frameworks for Heterogeneous High Performance Reconfigurable Computing 7. Future-gazing: New Applications/The Cloud Enabled by Heterogeneous High Performance Reconfigurable Computing, Evolution of Computer Architecture in relation to Heterogeneous High Performance Reconfigurable Computing 8. Community building: Standards, consortium activity, open source, education, initiatives to enable and grow Heterogeneous High Performance Reconfigurable Computing Prospective authors are invited to submit original and unpublished contributions as a ONE PAGE EXTENDED ABSTRACT in ACM SIG Proceedings format. ========================================================================== You can submit your contribution(s) through a link on the H2RC website: http://h2rc.cse.sc.edu ========================================================================== Important dates: Submission Deadline: September 1, 2017 Acceptance Notification: October 15, 2017 Camera-ready Manuscripts Due: November 4, 2017 Workshop Date: November 17, 2017 ========================================================================== Workshop Format: H2RC is a half-day Friday workshop. It will be comprised of Keynote and invited talks and talks selected from paper submissions. ========================================================================== Organizing Committee: Workshop Organizers: Michaela Blott, Xilinx Franck Cappello, Argonne National Lab Torsten Hoefler, ETH Zurich Jason D. Bakos, University of South Carolina Program Committee: Rizwan Ashraf, Oak Ridge National Laboratory Paul Chow, University of Toronto Carl Ebeling, Altera Hans Eberle, NVIDIA Alan George, University of Florida Christoph Hagleitner, IBM Miriam Leeser, Northeastern University Viktor Prasanna, Univ. of Southern California Marco Santambrogio, Politecnico Di Milano Jeffrey Vetter, Oak Ridge National Lab -- Jason D. Bakos, Ph.D. Professor Dept. of Computer Science and Engineering Univ. of South Carolina 301 Main St., Suite 3A01L Columbia, SC 29208 803-777-8627 (voice), 803-777-3767 (fax) http://www.cse.sc.edu/~jbakos jbakos(a)cse.sc.edu

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[Deadline extended to Aug. 13] - CFP: 12th Workflows in Support of Large-Scale Science (WORKS) Workshop
by Ilia Pietri 28 Jul '17

28 Jul '17

********** WORKS 2017 Workshop ********** Workflows in Support of Large-Scale Science Workshop http://works.cs.cardiff.ac.uk/ Monday 13 November 2017, Denver, Colorado, USA. Held in conjunction with SC17, http://sc17.supercomputing.org/ Paper submission deadline: 13 August 2017 ***************************************** Call For Papers Data-intensive workflows (a.k.a. scientific workflows) are routinely used in most scientific disciplines today, especially in the context of high-performance, parallel and distributed computing. They provide a systematic way of describing a complex scientific process and rely on sophisticated workflow management systems to execute on a variety of parallel and distributed resources. With the dramatic increase of raw data volume in every domain, they play an even more critical role to assist scientists in organizing and processing their data and to leverage HPC or HTC resources, being at the interface between end-users and computing infrastructures. This workshop focuses on the many facets of data-intensive workflow management systems, ranging from actual execution to service management and the coordination and optimization of data, service and job dependencies. The workshop covers a broad range of issues in the scientific workflow lifecycle that include: data-intensive workflows representation and enactment; designing workflow composition interfaces; workflow mapping techniques to optimize the execution of the workflow for different infrastructures; workflow enactment engines that need to deal with failures in the application and execution environment; and a number of computer science problems related to scientific workflows such as semantic technologies, compiler methods, scheduling and fault detection and tolerance. The topics of the workshop include but are not limited to: Big Data analytics workflows Data-driven workflow processing (including stream-based workflows) Workflow composition, tools, and languages Workflow execution in distributed environments (including HPC, clouds, and grids) Reproducible computational research using workflows Dynamic data dependent workflow systems solutions Exascale computing with workflows Workflow fault-tolerance and recovery techniques Workflow user environments, including portals Workflow applications and their requirements Adaptive workflows Workflow optimizations (including scheduling and energy efficiency) Performance analysis of workflows Workflow debugging Workflow provenance Interactive workflows (including workflow steering) ***************************************** Important Dates Papers Due: 13 August 2017 (EXTENDED) Notifications of Acceptance: 9 September 2017 E-copyright registration completed by authors: 1 October 2017 Final Papers Due: 1 October 2017 Submitted papers must be at most 10 pages long. The proceedings should be formatted according to http://www.acm.org/publications/proceedings-template. WORKS papers will be published in collaboration with SIGHPC and will be available from both ACM and IEEE digital repositories. ***************************************** WORKS 2017 Organizing Committee – PC Chairs Sandra Gesing, University of Notre Dame, USA Rizos Sakellariou, University of Manchester, UK – General Chairs Johan Montagnat, CNRS, Sophia Antipolis, France Ian Taylor, Cardiff University, UK and University of Notre Dame, USA – Steering Committee David Abramson, University of Queensland, Australia Malcolm Atkinson, University of Edinburgh, UK Ewa Deelman, University of Southern California, USA Michela Taufer, University of Delaware, USA – Publicity Chairs Rafael Ferreira da Silva, USC, USA Ilia Pietri, University of Athens, Greece ***************************************** WORKS 2017 Program Committee Pinar Alper, King's College London, UK Ilkay Altintas, San Diego Supercomputer Center, USA Khalid Belhajjame, Université Paris-Dauphine, France Adam Belloum, University of Amsterdam, the Netherlands Ivona Brandic, TU Wien, Austria Kris Bubendorfer, Victoria University of Wellington, New Zealand Jesus Carretero, Universidad Carlos III de Madrid, Spain Henri Casanova, University of Hawaii at Manoa, USA Ewa Deelman, USC Information Sciences Institute, USA Rafael Ferreira Da Silva, USC Information Sciences Institute, USA Daniel Garijo, USC Information Sciences Institute, USA Sandra Gesing, University of Notre Dame, USA Tristan Glatard, CNRS, France Daniel Katz, University of Illinois Urbana-Champaign, USA Tamas Kiss, University of Westminster, UK Dagmar Krefting, HTW Berlin, Germany Maciej Malawski, AGH University of Science and Technology, Poland Anirban Mandal, Renaissance Computing Institute, USA Marta Mattoso, Federal Univ. Rio de Janeiro, Brazil Andrew Stephen Mcgough, Newcastle University, UK Paolo Missier, Newcastle University, UK Jarek Nabrzyski, University of Notre Dame, USA Daniel de Oliveira, Fluminense Federal University, Brazil Ilia Pietri, University of Athens, Greece Radu Prodan, University of Innsbruck, Austria Omer Rana, Cardiff University, UK Ivan Rodero, Rutgers University, USA Rizos Sakellariou, University of Manchester, UK Domenico Talia, University of Calabria, Italy Rafael Tolosana-Calasanz, Universidad de Zaragoza, Spain Chase Wu, New Jersey Institute of Technology, USA

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Special issue on Optimisation Solutions in Systems
by Fernando Rubio 25 Jul '17

25 Jul '17

*CALL FOR PAPERS * *http://antares.sip.ucm.es/~fernando/jsit/cfp.htm <http://antares.sip.ucm.es/~fernando/jsit/cfp.htm>* *A Special Issue of the Journal of Systems and Information Technology on Optimisation Solutions in Systems* *Aims and Scope* Optimisation is a major necessity in Science and Engineering. No matter if we want to reduce the amount of needed resources to perform a task or maximize the output of some process, so often the difficulty of making the right decisions can be rephrased as some kind of optimisation problems. Unfortunately, for many optimisation problems finding the optimal solution is not feasible in general due to the hardness of the problem —moreover, for some of them we cannot even guarantee any constant ratio between the quality of the optimal solution and the quality of any solution found in reasonable time. Despite these disheartening theoretical limits, optimisation problems appear whenever there is a sophisticated system, so we do have to face them by some means —necessarily non-exhaustive methods. Some of these methods are specific to the problem under consideration, whereas others are adaptations of general optimization heuristics (metaheuristics) to the studied problem. Typically, the latter search for solutions similar to the most promising observed ones, or their combinations, for example by making some simple entities interact with each other according to simple rules and collaboratively construct new solutions. Within this category we can find evolutionary computation methods and swarm optimization methods, which are sometimes inspired by some natural process. Regardless of the method selected to tackle a hard optimization problem, the difficulty of the problem and the performance of the best known heuristics for the problem may have a high impact on the application field the problem belongs to, since the difficulty of a scientific or engineering process can be, to some extent, due to the computational difficulty of the underlying optimization problem it implicitly poses. The goal of this special issue is to introduce new research, or comprehensive compilations of existing ones, on optimisation techniques for engineering systems, and their applications. *We solicit contributions related, but not limited to the following topics:* · New optimisation algorithms and metaheuristics, enhancement of existing ones · Problem-specific and generic optimisation methods · Comparison of optimisation algorithms and metaheuristics · Nature inspired metaheuristics, evolutionary computation, swarm intelligence · Classification and generalization of metaheuristics, hybridisation of methods · Optimisation problems on real data, case studies · Benchmark usage and generation · Optimisation hardness, complexity of problems and optimisation algorithms · Impact of the optimisation difficulty on Social Sciences, Natural Sciences and Engineering · Comprehensive compilations of the state of art on any aspect of optimisation We encourage submissions from both academics and practitioners. *Submission Procedure* Full papers should be submitted to: *http://mc.manuscriptcentral.com/jsit* <http://mc.manuscriptcentral.com/jsit> (all manuscripts should follow the submission guidelines available at http://emeraldgrouppublishing. com/products/journals/author_guidelines.htm?id=jsit You must first create an author account in the system if you do not have one. Once registered, you will see the Author Centre button when you sign in to your account. Click on the ‘click here to submit a new manuscript’ link, which will take you through to the Manuscript Submission page. Follow the instructions to complete all fields and browse to upload your manuscript. At the ‘please select the issue you are submitting to’ dropdown list (under Details & Comments) please choose *“Special Issue on Optimisation Solutions in Systems”*. *Important dates:* · Please submit papers on or before October 1st 2017. All submissions will be peer-reviewed following the review process of the Journal of Systems and Information Technology. (Prospective authors are encouraged to indicate their interests any time before the submission deadline. Please, contact fernando(a)sip.ucm.es) · Notification of results: December 15th 2017. · Final submission: January 31st 2018. · The special issue will be published in June 2018 Special Issue Guest Editors: Dr. Pablo Rabanal, Facultad de Informática, Universidad Complutense de Madrid, Spain Dr. Ismael Rodríguez, Facultad de Informática, Universidad Complutense de Madrid, Spain Dr. Fernando Rubio, Facultad de Informática, Universidad Complutense de Madrid, Spain

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Call For Papers [Best Paper Award, Keynote Speaker and Panel]: ESPM2@SC17 - Third International Workshop on Extreme Scale Programming Models and Middleware
by Hari Subramoni 24 Jul '17

24 Jul '17

======================================================================== Call For Papers Third International IEEE Workshop on Extreme Scale Programming Models and Middleware (ESPM2 2017) November 12, 2017, Denver, Colorado to be held in conjunction with SuperComputing 2017, November 12 - 16, 2017 Denver, Colorado http://nowlab.cse.ohio-state.edu/espm2/ ======================================================================== Next generation architectures and systems being deployed are characterized by high concurrency, low memory per-core, and multiple levels of hierarchy and heterogeneity. These characteristics bring out new challenges in energy efficiency, fault-tolerance and, scalability. It is commonly believed that software has the biggest share of the responsibility to tackle these challenges. In other words, this responsibility is delegated to the next generation programming models and their associated middleware/runtimes. This workshop focuses on different aspects of programming models such as task-based parallelism (Charm++, OCR, Habanero, Legion, X10, HPX, etc), PGAS (OpenSHMEM, UPC, CAF, Chapel, UPC++, etc.), BigData (Hadoop, Spark, etc), Deep Learning (Caffe, Microsoft CNTK, Google TensorFlow), directive-based languages (OpenMP, OpenACC) and Hybrid MPI+X, etc. It also focuses on their associated middleware (unified runtimes, interoperability for hybrid programming, tight integration of MPI+X, and support for accelerators) for next generation systems and architectures. The ultimate objective of the ESPM2 workshop is to serve as a forum that brings together researchers from academia and industry working in the areas of programming models, runtime systems, compilers, programming languages, and application developers. ESPM2 2017 will be held as a full day workshop in conjunction with the SuperComputing (SC 2017), Denver, Colorado, USA, Sunday, November 12th, 2017. Topics ------ ESPM2 2017 welcomes original submissions in a range of areas, including but not limited to: * New programming models, languages and constructs for exploiting high concurrency and heterogeneity * Experience with and improvements for existing parallel languages and run-time environments such as: - MPI - PGAS (OpenSHMEM, UPC, CAF, Chapel, UPC++, etc.) - Directive-based programming (OpenMP, OpenACC) - Asynchronous Task-based models (Charm++, OCR, Habanero, Legion, X10, HPX, etc) - Hybrid MPI+X models - BigData (Hadoop, Spark, etc), and - Deep Learning (Caffe, Microsoft CNTK, Google TensorFlow) * Parallel compilers, programming tools, and environments * Software and system support for extreme scalability including fault tolerance * Programming environments for heterogeneous multi-core systems and accelerators such as KNL, OpenPOWER, ARM, GPUs, FPGAs, MICs, and DSPs Papers should present original research and should provide sufficient background material to make them accessible to the broader community. Best Paper Award ---------------- Intel has generously offered to sponsor the Best Paper Award. This award will be given to the author(s) of the paper selected by the Technical Program Committee and the Program Chairs. The award will be determined from viewpoints of the technical and scientific merits, impact on the science and engineering of the research work and the clarity of presentation of the research contents in the paper. Keynote Speakers ---------------- We are happy to announce that Prof. William D. Gropp, Interim Director and Chief Scientist at the National Center for Supercomputing Applications and the Thomas M. Siebel Chair in Computer Science at the University of Illinois Urbana-Champaign will deliver the keynote address at ESPM2'17. Panel Information ----------------- Panel Topic : Effective Programming Models for Deep Learning at Scale Panel Moderator : Daniel Holmes, EPCC, The University of Edinburgh, UK. Panel Members : Coming soon! Paper Submission and Registration --------------------------------- Abstracts and papers need to be submitted via the EasyChair conference system. EasyChair URL for ESPM2'17: https://easychair.org/conferences/?conf=espm22017 Submissions should not exceed 8 pages using ACM format with 10pt font. Each submission must be a single PDF file. Papers must be submitted in PDF format (readable by Adobe Acrobat Reader 5.0 and higher) and formatted for 8.5" x 11" (U.S. Letter). The manuscript should be formatted according to ACM format (see http://www.acm.org/sigs/publications/proceedings-templates) Papers should present original research and should provide sufficient background material to make them accessible to the broader community. It should not be submitted in parallel to any other conference or journal. At least one of the authors of each accepted paper must register as a participant of the workshop and present the paper at the workshop, in order to have the paper published in the proceedings. Each research paper will be taken through a comprehensive peer review process by an internationally recognized group of experts in the field. Papers will be evaluated along the metrics of a) Quality of Presentation; b) Novelty / Originality; c) Relation to State of the Art; d) Technical Strength; e) Significance of Work; and f) Relevance to Workshop. Every effort will be made to ensure that each paper receives multiple reviews. Please contact the Program Chairs for any questions/clarifications Proceedings Information ----------------------- ACM SigHPC will publish the workshop proceedings which will be available through the ACM Digital Library. The camera-ready versions need to be submitted via the EasyChair conference management system. The link to the submission site will be provided soon. Please contact the Program Chairs for any questions/clarifications. Important Dates --------------- Technical paper submission deadline : 11:59 PM, AoE, August 31, 2017 Author notification : October 1, 2017 Camera-ready deadline : 11:59 PM, AoE, October 7, 2017 Workshop : Sunday, November 12, 2017 ESPM2'17 Workshop Organizers ------------------------------ Hari Subramoni, The Ohio State University Karl Schulz, Intel Corporation Dhabaleswar K. (DK) Panda, The Ohio State University Program Committee ----------------- * Guang R. Gao, University of Delaware * Vladimir Getov, University of Westminster, UK * Jeff Hammond, Intel Labs * Michael A. Heroux, Sandia National Laboratories * Costin Iancu, Lawrence Berkeley National Laboratory * Darren Kerbyson, Pacific Northwest National Laboratory * Guangming Tan, Institute of Computing Technology, Chinese Academy of Sciences, China * Olivier Tardieu, IBM T.J. Watson Research Center * Daniel Tian, The Portland Group * Sean Treichler, NVIDIA Corporation * Abhinav Vishnu, Pacific Northwest National Laboratory Further Information ------------------- See the ESPM2'17 website at http://nowlab.cse.ohio-state.edu/espm2/ Thanks, The ESPM2'17 Organizing Committee.

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[CFP] IA^3 2017 - Seventh SC Workshop on Irregular Applications: Architectures and Algorithms
by Tumeo, Antonino 24 Jul '17

24 Jul '17

[Apologies if you receive multiple copies of this CFP] IA^3 2017 Seventh Workshop on Irregular Applications: Architectures and Algorithms http://hpc.pnl.gov/IA3/ November 13, 2017 In conjunction with SC17 In collaboration with ACM SIGHPC Sponsored by IEEE TCHPC Call for Papers Irregular applications occur in many subject matters. While inherently parallel, they exhibit highly variable execution performance at a local level due to unpredictable memory access patterns and/or network transfers, divergent control structures, and data imbalances. Moreover, they often require fine-grain synchronization and communication on large-data structures such as graphs, trees, unstructured grids, tables, sparse matrices, deep nets, and their combinations (such as, for example, attributed graphs). They have a significant degree of latent parallelism, which however is difficult to exploit due to their complex behavior. Current high performance architectures rely on data locality and regular computation to reduce access latencies, and often do not cope well with the requirements of these applications. Furthermore, irregular applications are difficult to scale on current supercomputing machines, due to their limits in fine-grained synchronization and small data transfers. Irregular applications pertain both to well established and emerging fields, such as machine learning, social network analysis, bioinformatics, semantic graph databases, Computer Aided Design (CAD), and computer security. Many of these application areas also process massive sets of unstructured data, which keep growing exponentially. Addressing the issues of irregular applications on current and future architectures will become critical to solve the challenges in science and data analysis of the next few years. This workshop seeks to explore solutions for supporting efficient execution of irregular applications in the form of new features at the level of the micro- and system-architecture, network, languages and libraries, runtimes, compilers, analysis, algorithms. Topics of interest, of both theoretical and practical significance, include but are not limited to: * Micro- and System-architectures, including multi- and many-core designs, heterogeneous processors, accelerators (GPUs, vector processors, Automata processor), reconfigurable (coarse grained reconfigurable and FPGA designs) and custom processors * Network architectures and interconnect (including high-radix networks, optical interconnects) * Novel memory architectures and designs (including processors-in memory) * Impact of new computing paradigms on irregular workloads (including neuromorphic processors and quantum computing) * Modeling, simulation and evaluation of novel architectures with irregular workloads * Innovative algorithmic techniques * Combinatorial algorithms (graph algorithms, sparse linear algebra, etc.) * Impact of irregularity on machine learning approaches * Parallelization techniques and data structures for irregular workloads * Data structures combining regular and irregular computations (e.g., attributed graphs) * Approaches for managing massive unstructured datasets (including streaming data) * Languages and programming models for irregular workloads * Library and runtime support for irregular workloads * Compiler and analysis techniques for irregular workloads * High performance data analytics applications, including graph databases Besides regular papers, papers describing work-in-progress or incomplete but sound, innovative ideas related to the workshop theme are also encouraged. We solicit both 8-page regular papers and 4-page position papers. Authors of exciting but not mature enough regular papers may be offered the option of a short 4-page paper and related short presentation. Artifact Evaluation For this edition of IA3, authors of accepted regular papers will be invited to formally submit their supporting materials to the Artifact Evaluation process, similarly to the process followed for SC17. The participation to the Artifact Evaluation process is voluntary and will not change decisions regarding the paper. However, papers that undergo the evaluation process will receive a seal of approval on the paper, and will be able to participate in the BEST PAPER AWARD selection. DIVIDITI will provide an Amazon Gift Voucher (valued $200) to the authors of the paper that passes artifact evaluation with the highest score and that shares the artifact in the CK (Collective Knowledge - https://github.com/ctuning/ck) format. Authors that go through the Artifact Evaluation process are also encouraged (but not mandated) to submit the supporting materials as “Source Materials” in the digital library. For details on how to submit supporting materials to the Artifact Evaluation process, please refer to: http://ctuning.org/ae/submission.html. For any additional question on the Artifact Evaluation process please contact the Artifact Evaluation Chair Flavio Vella. Important Dates Abstract submission: 22 August 2017 Position or full paper submission: 29 August 2017 Notification of acceptance: 3 October 2017 Camera-ready position and full papers: 10 October 2017 Workshop: 13 November 2017 Submissions Submission site: https://easychair.org/conferences/?conf=ia32017 All submissions should be in double-column, single-spaced letter format, with at least one-inch margins on each side and respect the ACM standard proceedings templates (sigconf) available at: https://www.acm.org/publications/proceedings-template. The proceedings of the workshop will be published in cooperation with ACM SIGHPC. Submitted manuscripts may not exceed eight (8) pages in length for regular papers and four(4) pages for position papers including figures, tables and references. Organizers Antonino Tumeo, PNNL, US John Feo, PNNL/NIAC, US, Vito Giovanni Castellana, PNNL, US Artifact Evaluation Chair Flavio Vella, DIVIDITI, UK Publication Chair Marco Minutoli, PNNL, US Program Committee Scott Beamer, LBNL, US Michela Becchi, North Carolina State University, US Erik Boman, Sandia National Laboratories, US David Brooks, Harvard University, US Aydin Buluc, LBNL, US Sunita Chandrasekaran, University of Delaware, US Fabio Checconi, IBM, US Rajiv Gupta, Univerisity of California Riverside, US Maya Gokhale, LLNL, US Peter Kogge, Univ. of Notre Dame, US Vivek Kumar, Rice University, US John Leidel, Texas Tech University, US Kamesh Madduri, Pennsylvania State University, US Naoya Maruyama, RIKEN AICS, JP Tim Mattson, Intel, US Miquel Moreto, BSC and UPC, SP Richard Murphy, Micron Technology Inc, US Walid Najjar, University of California Riverside, US Maxim Naumov, NVIDIA, US Jacob Nelson, University of Washington, US Sreepathi Pai, University of Rochester, US Roger Pearce, LLNL, US Miquel Pericas, Chalmers University, SE Viktor Prasanna, University Of Southern California, US Alejandro Rico, ARM, US Jason Riedy, Georgia Institute of Technology, US Erik Saule, University of North Carolina at Charlotte, US John Shalf, LBNL, US Shaden Smith, University of Minnesota, US Bora Ucar, CNRS and LIP ENS Lyon, FR Ruud Van Der Pas, Oracle, US Flavio Vella, DIVIDITI, UK Ana Lucia Varbanescu, University of Amsterdam, NL

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computational.science July 2017