June 2022 - hpc-announce - mailman3.cels.anl.gov

CfP: 8th Workshop on Heterogeneous High-performance Reconfigurable Computing (H2RC 2022) at SC22: Submission Deadline Aug. 1
by Bakos, Jason 30 Jun '22

30 Jun '22

CALL FOR PAPERS Eighth International Workshop on Heterogeneous High-performance Reconfigurable Computing (H2RC) Workshop Date: All Day Monday, November 14, 2022 http://h2rc.cse.sc.edu Accepted papers will be indexed and published in the IEEE Computer Society Digital Library Submission Deadline: August 1, 2022 (8-page full papers or 2-page extended abstract, see below) Submission link: https://bit.ly/h2rc2022 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, and much of the work in FPGA-based deep learning is built on these frameworks. 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 eighth year, brings together HPC and heterogeneous computing researchers to demonstrate and share experiences on how newly-available high-level programming models are already empowering HPC software developers to directly leverage FPGAs and to identify future opportunities and needs for research in this area. Submission Tracks and Contribution Selection Submissions are solicited for two tracks: Track 1: Full-length papers (8 pages, excluding references) for oral presentation and publication in proceedings archived by IEEE. Track 2: Extended abstracts / talk proposals (2 pages, excluding references) oral presentation without publication. Track 1 is targeted for technical papers containing a high level of implementation detail and analysis of experimental results. Track 1 is suited for members of the academic and national lab community who prefer to have their work peer-reviewed, indexed, and archived by IEEE. Track 2 is targeted for industrial contributions that describe new capabilities and opportunities offered by emerging technologies and products, or work in progress presentations by the academic and national lab community. The emphasis of this track is to initiate a discussion with the audience. These extended abstracts will be made available on the conference website. All submissions are peer reviewed and evaluated by at least three members of our technical program committee (TPC). From the TPC evaluation of each submission, the organizing committee will select papers for presentation based on a criteria that is equally weighted between scientific merit and level of interest and relevance to the HPC community. Submission Topics Submissions are solicited that explore the state of the art in the use of FPGAs in heterogeneous high-performance compute 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. Submissions investigating the use of FPGAs in combination with other devices such as CPU/GPU/APU/DPU are particularly welcomed. 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 help to shape future research and implementations in this domain. A non-comprehensive list of potential topics of interest is given below: 1. Use of FPGAs to improve performance or efficiency of HPC or data center applications 2. System integration of FPGAs in clouds and distributed HPC systems 3. Leveraging reconfigurability 4. Benchmarks 6. Programming languages, tools, and frameworks 7. Future-gazing Submission Guidelines Full papers (Track 1) Authors should submit original contributions of up to 8 pages (excluding references) in PDF format using the SC22 Linklings portal (https://submissions.supercomputing.org) which is also linked from the H2RC website (https://h2rc.cse.sc.edu) Submissions must be formatted as single-spaced, double-column, 8 US letter pages without page numbers following the IEEE conference proceedings format, including figures and tables. H2RC uses a single blind review process. We support the SC reproducibility initiative and highly encourage authors to add an artifact description/ artifact evaluation appendix of up to 2 additional pages to their paper. All accepted papers will be published in the IEEE Computer Society digital library. Talk proposals (Track 2) To apply for a talk authors should submit a 2-page extended abstract. The extended abstract will be peer-reviewed and used for deciding on the acceptance of a presentation assignment of a presentation slot, but will be published only on the workshop website but not in the proceedings. The papers shall follow the same formatting instructions as the full papers and have also to be submitted using the Linklings system. Important dates: Submission Deadline: August 1, 2022 Acceptance Notification: September 8, 2022 Camera-ready Manuscripts Due: October 13, 2022 Workshop Date: November 14, 2022 Workshop Format H2RC is a full-day Monday workshop. It will be comprised of: - Keynote and invited talks - Talks selected among paper submissions Coronavirus Outbreak Impact The impact of the coronavirus outbreak on attending the SC22 conference is uncertain at the moment. H2RC will take place according to SC22 organization directives (https://sc22.supercomputing.org/attend/coronavirus-sc) In all cases paper review, selection, ISAV program and proceedings publication will proceed up to completion according to the planned timeline. Workshop Organizers: Jason D. Bakos, University of South Carolina Franck Capello, Argonne National Lab Torsten Hoefler, ETH Zurich Ken O'Brien, AMD Christian Plessl, Paderborn University Technical Program Committee: David Andrews, U. Arkansas Paul Chow, U. Toronto Hans Eberle, Nvidia Xin Fang, Northeastern U. Christoph Hagleitner, IBM Zurich Martin Herbordt, Boston U. Yoshii Kazutomo, Argonne National Lab Miriam Leeser, Northeastern U. Seda Memik, Northwestern U. Viktor Prasanna, U. Southern California Kentaro Sano, Riken Yaman Umuroglu, Xilinx Research Jeffrey Vetter, Oak Ridge National Lab Peipei Zhou, U. Pittsburgh -- Jason D. Bakos, Ph.D., Professor Dept. of Computer Science and Engineering Univ. of South Carolina

1 0

CFP: DEADLINE EXTENSION July 5th: TestVis Hybrid Workshop on Visualization in Testing of Hardware, Software, and Manufacturing
by Kate Isaacs 30 Jun '22

30 Jun '22

CALL FOR SUBMISSIONS: * TestVis 2022 Workshop @ IEEE VIS 2022 * https://testvis.gitlab.io * Full paper deadline: 5 Jul 2022 [NEWLY EXTENDED!] * Short notes deadline: 9 Sep 2022 Testing hardware, software, and other products is a highly relevant task to ensure quality and reliability. Due to the increasing complexity of such systems or products, testing tasks are not only an inevitable step that can occur at different stages of product life cycles, but they are getting increasingly complex as well. Such tasks include, but are not limited to: test planning, defining tests and test data, carrying out test plans, as well as collecting and analyzing test results. Monitoring and profiling tasks are added when later phases in the life cycle of systems and products are taken into account. All these different tasks need to scale with an increasing number of test conditions, parameters, test samples, boundary conditions, etc., and with more sophisticated analysis methods including AI-based approaches. In many cases, interactive visualization approaches can contribute to manage or even reduce complexities, and to communicate outcomes effectively. The TestVis 2022 workshop aims to bring together researchers and practitioners from different domains where testing is relevant. We see it as a first step towards building a community of stakeholders from industry and academia interested in visualizing test and monitoring-related problems. We will solicit submissions on test-related research and work in progress including, but not limited to, the following topics. - Visualization for software testing - Visualization for hardware and integrated circuit testing - Visualization for testing in manufacturing - Visual monitoring and profiling of running systems for testing - Testing for visualization - Interactive creation of test data, constraints, and parameter settings - Interactive planning of test procedures - Visual representation of test conditions - Interactive visualization and steering of testing processes - Visualization for DevOps - Visual performance analysis - Progressive reporting of test processes - Monitoring of test telemetry - Visually supported interpretation of test results - Visualization of test results over time - Visual analysis of testing rigs and their configurations The workshop welcomes submissions on tools, systems, and approaches that are successfully used in practice as well as research approaches, work in progress, and position statements. *Important dates* 5 Jul 2022: Submission of regular (archival) papers [NEWLY EXTENDED!] 2 Aug 2022: Notification for regular papers 21 Aug 2022: Camera-ready versions of accepted regular papers 9 Sep 2022: Submission of short notes 22 Sep 2022: Notification for short notes The workshop accepts two types of paper submissions: regular submissions which are archived and will be published on IEEE Xplore and workshop internal short notes which are published on the website given the authors’ consent. Authors of accepted papers are required to present their work either onsite or online during the HYBRID workshop. Please take a look at the workshop website for more details: https://testvis.gitlab.io Organizers: Katherine E. Isaacs, Steffen Koch, Timo Ropinski, Stefan Wagner, Daniel Weiskopf testvis(a)googlegroups.com

1 0

CFP: [DRBSD 2022] The 8th International Workshop on Data Analysis and Reduction for Big Scientific Data at SC'22
by Liang, Xin 29 Jun '22

29 Jun '22

The 8th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD 2022) (Call for Papers) November 13th, 2022 @ Dallas, Texas, USA https://drbsd.github.io Important dates Full papers due: August 15, 2022 Deadlines are Anywhere on Earth (AoE) DRBSD 2022 is organized in conjunction with SC22. The Call for Papers for the 8th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD-8) is now open, with a submission deadline of August 15, 2022 (AoE). DRBSD is a prestigious workshop in scientific data reduction and analysis, and quite a few outstanding works have been published in this workshop for years. Topics of interest include but are not limited to: • Data reduction methods for scientific data ° Data deduplication methods ° Motif-specific methods (structured and unstructured meshes, particles, tensors, ...) ° Methods with accuracy guarantees ° Feature/QoI-preserving reduction ° Optimal design of data reduction methods ° Compressed sensing and singular value decomposition • Metrics to measure reduction quality and provide feedback • Data analysis and visualization techniques that take advantage of the reduced data ° AI/ML methods ° Surrogate/reduced-order models ° Feature extraction ° Visualization techniques ° Artifact removal during reconstruction ° Methods that take advantage of the reduced data • Data analysis and reduction co-design ° Methods for using accelerators ° Accuracy and performance trade-offs on current and emerging hardware ° New programming models for managing reduced data ° Runtime systems for data reduction • Large-scale code coupling and workflows • Experience of applying data reduction and analysis in practical applications or use-cases ° State of the practice ° Application use-cases which can drive the community to develop MiniApps Submission Papers should be submitted electronically on SC Submission Website. https://submissions.supercomputing.org DRBSD-8 will accept full papers (6 pages, excluding references and appendix), and extended abstracts (2 pages, including references and appendix). Submitted papers will be evaluated by at least 3 reviewers based upon technical merits.

1 0

CfP: Paper submission deadline approaching: 29th IEEE International Conference on High Performance Computing, Data & Analytics (HiPC 2022)
by Anand Panangadan 29 Jun '22

29 Jun '22

HiPC 2022 29th IEEE International Conference on High Performance Computing, Data & Analytics Dec. 18-21, 2022 Bengaluru, India Website: http://www.hipc.org CALL FOR PAPERS HiPC 2022 will be the 29th 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. Each submission should be submitted to one of the six 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. Depending on how the COVID-19 pandemic situation evolves, the presentation may be in person or in a virtual format. Authors of selected high-quality papers in HiPC 2022 will be invited to submit extended versions of their papers for possible publication in a special issue of the Journal of Parallel and Distributed Computing (JPDC). HIGH PERFORMANCE COMPUTING Algorithms: - New parallel and distributed algorithms and design techniques; - Advances in enhancing algorithmic properties or providing guarantees (e.g., concurrency, data locality, communication-avoiding, asynchronous, hybrid CPU-GPU algorithms, fault tolerance, resilience,); - 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: - High performance processing architectures (e.g., reconfigurable, system-on-chip, many cores, 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: - 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: - 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). SCALABLE DATA SCIENCE Scalable Algorithms and Analytics: - New scalable algorithms for fundamental data analysis tasks (supervised, unsupervised learning, data (pre-)processing 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 the 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, health sciences); - 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, natural language processing and computer vision applications. Scalable Systems and Software: - New parallel and distributed algorithms and design techniques; - 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, data deduplication, 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 - Submission site open: June 15, 2022 - Abstract submissions: July 4, 2022 AOE - Full Paper submissions: July 8, 2022 AOE - First-round Author notifications: September 12, 2022 - Submission of revised papers along with response to reviews: October 10, 2022 - Author notification for revised papers: November 1, 2022 - Camera-ready version: November 15, 2022 - Conference dates: December 18-21, 2022 General Co-chairs: - Chiranjib Sur, Shell, India - Neelima Bayyapu, Consultant, India Vice General Co-chairs: - Sanmukh Rao Kuppannagari, University of Southern California, USA - Vivek Yadav, IIIT-Bangalore, India- - Program Co–chairs: - High performance computing: Sathish Vadhiyar, Indian Institute of Science, India - Data science: Jun Wang, University of Central Florida, USA Program Vice-Chairs HPC TRACKS - Algorithms: Thomas Herault, University of Tennessee, USA - Applications: Yogish Sabharwal, IBM IRL, India - Architecture: Diana Goehringer, TU Dresden, Germany - System Software: Jyothi Vedurada, IIT, Hyderabad DATA SCIENCE TRACKS - Scalable Algorithms and Analytics: Zhishan Guo, University of Central Florida, USA - Scalable Systems and Software: Dan Huang, Sun Yat-Sen University, PRC Steering committee chair: - Viktor K. Prasanna, University of Southern California, USA

1 0

2nd IEEE/ACM International Workshop on RESource DISaggregation in High Performance Computing (RESDIS’22)
by John Shalf 29 Jun '22

29 Jun '22

========================================================================== CALL FOR PAPERS ========================================================================== 2nd IEEE/ACM International Workshop on RESource DISaggregation in High Performance Computing (RESDIS’22) To be held in conjunction with The International Conference for High Performance Computing, Networking, Storage and Analysis (SC’22) on November 18, 2022 In cooperation with the IEEE Computer Society ========================================================================== https://resdis.github.io/ws/2022/sc/ ========================================================================== Disaggregation is an emerging compute paradigm that splits existing monolithic servers into a number of consolidated single-resource pools that communicate over a fast interconnect. This model decouples individual hardware resources, including tightly coupled ones such as processors and memory, and enables the composition of logical compute platforms with flexible and dynamic hardware configurations. The concept of disaggregation is driven by various recent trends in computation. From an application perspective, the increasing importance of data analytics and machine learning workloads in HPC centers brings unprecedented need for memory capacity, which is in stark contrast with the growing imbalance in the peak compute-to-memory capacity ratio of traditional system board based server platforms where memory modules are co-located with processors. At the hardware front, the proliferation of heterogeneous, special purpose computing elements promotes the need for configurable compute platforms, while at the same time, the increasing maturity of optical interconnects elevates the prospects of better distance independence in networking infrastructure. The workshop intends to explore various aspects of resource disgregation, composability and their implications for high performance computing, both in dedicated HPC centers as well as in cloud environments. TOPICS OF INTEREST: ------------------- - Disaggregated hardware in high-performance computing - Operating systems and runtime support for disaggregated platforms - Simulation of disaggregated platforms with existing infrastructure - Runtime systems and programming abstractions for disaggregation and composability - Networking for disaggregation, including silicon photonics and optical interconnects - Implications of resource disaggregation for scientific computing and HPC applications - Algorithm design for disaggregated and composable systems - Disaggregated high throughput storage - Resource management in disaggregated and composable platforms TIMELINE AND SUBMISSION PROCEDURE: ---------------------------------- Submission deadline: August 5, 2022 Author notification: September 9, 2022 Final papers deadline: October 7, 2022 Workshop date: November 18, 2022 The workshop proceedings will be published electronically via the IEEE Computer Society Digital Library. Submitted manuscripts should be formatted using the IEEE template conference mode. The maximum paper length is 8 pages, not including references and other appendices. Prospective authors should submit their papers in PDF format through Linklings: https://submissions.supercomputing.org/?page=Submit&id=SC22WorkshopRESDISSu… WORKSHOP CHAIRS: ---------------- Balazs Gerofi RIKEN, Japan John Shalf Lawrence Berkeley National Laboratory, USA Keren Bergman Columbia University, USA PROGRAM COMMITTEE (CONFIRMED): ------------------------------ Manya Ghobadi Massachusetts Institute of Technology, USA Madeleine Glick Columbia University, USA Ian Karlin NVIDIA, USA John (Jack) Lange Oak Ridge National Laboratory, USA Ivy Peng Lawrence Livermore National Laboratory, USA Yu Tanaka Fujitsu, Japan Gaël Thomas Télécom SudParis, France

1 0

SDS 2022 CFP: The Ninth International Conference on Software Defined Systems , Paris, France. December 12-15, 2022
by Stanley Ewenike 29 Jun '22

29 Jun '22

[Apologies if you got multiple copies of this invitation] The Ninth International Conference on Software Defined Systems (SDS-2022) https://emergingtechnet.org/SDS2022/index.php Paris, France. December 12-15, 2022 Pending-Technically Co-Sponsored by IEEE France Section *SDS 2022 CFP:* Next generation cloud systems will require a paradigm shift in how they are constructed and managed. Conventional control and management platforms are facing considerable challenges regarding flexibility, dependability and security that next generation systems will require. The cloud computing paradigm has gone part of the way towards alleviating some of the problems associated with resource allocation, utilization and managements (e.g., via elasticity). However, many of the elements of a well-designed cloud environment remain “stiff” and hard to modify and adapt in an integrated fashion. This includes underlying networking topologies, many aspects of the user control over IaaS, PaaS or SaaS layers when such is needed, construction of XaaS services, provenance and meta-data collection, and so on. In many situations the problem may be because service abstraction is inadequate. Software Defined Systems (SDS) are systems that have added software components which help abstract actual IT equipment and other layers. One classical example, of course, are hypervisors. Such separation provides a great opportunity for system administrators to more easily construct and managing their systems through flexible software layers. Software Defined Systems include Software Defined Networking (SDN), Software Defined Storage, Software Defined Servers (Virtualization), Software Defined Datacenters (SDD), Software Defined Security (SDSec), and ultimately Software Defined Clouds (SDCloud) to name a few possibilities. Individual solutions and seamless integration of these abstractions remains in many respects a challenge. After the high success of the previous editions (SDS'2014, SDS'2015, SDS'2016, SDS'2017, SDS'2018, SDS' 2019, SDS' 2020 and SDS' 2021), The Ninth International conference on Software Defined Systems (SDS'2022) will continue to be a forum for scientists, researchers, students, and practitioners to present their latest research results, ideas, and developments in the area of software defined systems – both components and their integration - and by implication advancement of next generation clouds. SDS 2022 aims to investigate the opportunities and in all aspects of Software Defined Systems. In addition, it seeks for novel contributions that help mitigating SDS challenges. That is, the objective of SDS 2022 is to provide a forum for scientists, engineers, and researchers to discuss and exchange new ideas, novel results and experience on all aspects of Software Defined Systems. SDS is Technically Co-Sponsored by IEEE Spain Section. Researchers are encouraged to submit original research contributions in all major areas, which include, but not limited to: * Software Defined Systems support for Cloud Computing . * Software Defined Networking (SDN). * SDN concepts, architecture, and APIs. * Network Virtualization * SDN and OpenFlow protocol * Software Defined Radio * Cognitive Radio Networks . * Access Control models in SDN. * Software Defined Storage. * Storage Automation and Abstraction. * Policy-driven storage provisioning. * Software Defined Servers and Virtualization. * Software Defined Datacenters. * Software Defined Security o Security policies automation. * Self-management systems. * Autonomic Computing techniques. * Real-time load prediction model to optimize the user satisfaction. * Software Defined Systems Scalability. * Software Defined Systems optimization. * Software tools and frameworks to support SDS . * Software Defined Systems challenges and opportunities * Software Defined Systems surveys . * Social engineering, insider threats system for SDS. * Incident Handling and Penetration Testing with SDS. * Software Defined Systems support if IoT. * Security protocols in SDS. * Security and privacy of mobile SDS based cloud computing * Service-oriented architectures, service portability andP2P * Network virtualization and cloud-based radio access networks *Submissions Guidelines and Proceedings* Manuscripts should be prepared in 10-point font using the IEEE 8.5" x 11" two-column format. All papers should be in PDF format, and submitted electronically at Paper Submission Link. A full paper can be up to 8 pages (including all figures, tables and references). Submitted papers must present original unpublished research that is not currently under review for any other conference or journal. Papers not following these guidelines may be rejected without review. Also, submissions received after the due date, exceeding length limit, or not appropriately structured may also not be considered. Authors may contact the Program Chair for further information or clarification. All submissions are peer-reviewed by at least three reviewers. Accepted papers will appear in the SDS Proceeding, and be published by the IEEE Computer Society Conference Publishing Services and be submitted to IEEE Xplore for inclusion. Submitted papers must include original work, and must not be under consideration for another conference or journal. Submission of regular papers up to 8 pages and must follow the IEEE paper format. Please include up to 7 keywords, complete postal and e-mail address, and fax and phone numbers of the corresponding author. Authors of accepted papers are expected to present their work at the conference. Submitted papers that are deemed of good quality but that could not be accepted as regular papers will be accepted as short papers. Length of short papers can be between 4 to 6 pages. *Important Dates* Submission Date: 10 July, 2022 Notification to Authors: 20 October, 2022 Camera Ready Submission: 15 November, 2022 *Contact:* Please send any inquiry on SDS 2022 to the Emerging Tech. Network Team at: emergingtechnetwork(a)gmail.com

1 0

CFP: IEEE CLOUDNET 2022 - Paris, Nov. 7-10, 2022 - deadline extended to July 7
by Zhengxin Yu 28 Jun '22

28 Jun '22

The 11th IEEE International Conference on Cloud Networking IEEE CloudNet 2022 Paris, France November 07 - 10, 2022. https://www.ieee-cloudnet.org Call for Papers =============== Cloud networking has emerged as a promising direction for cost‐efficient, reliable service and data delivery across wide-area backbones and data-center fabrics. The prominent penetration of virtualization technologies into computing and communication infrastructure has led to continuous innovation, with new network protocols, software platforms, and artificial intelligence-based techniques for their orchestration. CloudNet 2022 will bring together the world’s most distinguished researchers and industry experts in this field and will provide a great opportunity for you to present your research as well as exchange ideas with a highly motivated audience. Selected CLOUDNET 2022 best-papers finalists will be invited to submit an extended version of their paper to IEEE Transactions on Network and Service Management (impact factor: 4.195), with a fast track review process. Accepted papers can be presented remotely: a link for remote participation will be available before the beginning of the conference. Invited Conference Speakers =========================== Keynotes * Tackling the Identity Problem, by Radia Perlman, Dell Technologies, USA. * Issues in Cloud Computing, by Charlie Kaufman, Dell Technologies, USA. * Building the Responsible Internet, by Paola Grosso, University of Amsterdam, Netherlands. * Cloud deployments of 5G core networks: unleashing the power of private 5G, by Nicola Di Pietro, Athonet, Italy. Additional keynotes will be announced soon. Tutorials * Tiny ML and Edge Computing, Akram Baharlouei, Meta AI (Facebook), USA * Introduction to quantum computing and post-quantum algorithms, Radia Perlman, Dell Technologies, USA. Additional tutorials will be announced soon. Conference Topics ================= The Conference topics include (but are not limited to): Cloud Network Architecture * Multi-Cloud federation and Hybrid Cloud Infrastructure * Reliability of Data Center Network and Architecture * Mobile Cloud Networking * Slicing and RAN Virtualization (SD-RAN, Cloud RAN, vRAN, OpenRAN) * Programmable Data Planes and Smart-NIC design * SDN/NFV and Virtualization of Network Equipment * Architectures to Enable AI/ML Resource Management * Data Center and Cloud-native Networks * Intra-Cloud vs. Inter-Cloud Management * Energy-Efficient Data Centers and Networks * Resource optimization and Management * Traffic Characterization and Measurements * Data Flow Management and Load Balancing * Storage Management * AI/ML-assisted Resource Management and Orchestration Cloud Supported Services * Big Data Analytics * Vehicular Cloud Computing * Network Connectivity Services * Unified User and Machine Mobility Management * Content and Service Distribution * Edge Computing * Location-based Services * Performance Enhancement of Cloud Applications Cloud Security and Privacy * Cloud Data Provenance and Data Loss Protection * Cloud Sovereignty * Cloud Storage Security * Cloud Application Security * Intrusion Detection/Prevention systems * Firewall and Deep Packet Inspection systems * AI/ML for Cloud Security Important Dates =============== Abstract registration (hard deadline): June 30, 2022 (11:59 pm AoE) Paper submission (hard deadline): July 7, 2022 (11:59 pm AoE) Acceptance notification: September 01, 2022 Camera-ready deadline: September 30, 2022 Conference: November 07 - 10, 2022 Co-located workshops ==================== * IEEE Global Internet Symposium - Nov. 7, 2022 * MathSecRes-22, workshop of the H2020 INSPIRE-5G project - Nov. 8, 2022 * AI@EDGE-22, workshop of the H2020 AI@EDGE project - Nov. 9, 2022 * NetOpt22 workshop - Nov. 10, 2022 Submission Guidelines ===================== Authors are invited to submit original contributions that have not been published or submitted for publication elsewhere. Submissions must be in IEEE single-spaced double-column style with a length limitation of 8 pages (including title, abstract, all figures, and tables) for full papers (oral presentation), excluding references. Accepted papers will be published in IEEE Xplore. Paper submission URL: https://edas.info/29433 Organization Committee ======================= General Chair: Stefano Secci, Cnam, France Technical Program Co-Chairs: Ramakrishnan Durairajan, U. Oregon, USA Leonardo Linguaglossa, Institut Polytechnique de Paris, France Demos and Posters Co-Chairs: Mathieu Bacou, Institut Polytechnique de Paris, France Anubhavnidhi Abhashkumar, ByteDance, USA Publication Chair: Stéphane Rovedakis, Cnam, France Publicity Co-Chairs: Pedro Casas, AIT, Austria Zhengxin Yu, Lancaster University, UK TPC Members: Rui Aguiar, University of Aveiro, (Portugal) Bengt Ahlgren, RISE (SICS), (Sweden) Chadi Assi, Concordia University, (Canada) Ilya Baldin, RENCI/UNC Chapel Hill, (USA) Javier Baliosian, University of the Republic, (Uruguay) Francesca Bassi, IRT SystemX, (France) Paolo Bellavista, University of Bologna, (Italy) Bartosz Belter, PSNC, (Poland) Carlos Bernardos, Universidad Carlos III de Madrid, (Spain) Luke Bertot, Telecom Paris, (France) Luiz Bittencourt, University of Campinas, (Brazil) Mohamed Boucadair, Orange, (France) Zdravko Bozakov, University of Applied Sciences Worms, (Germany) Eduardo Cerqueira, Federal University of Para & UCLA, (Brazil) Alberto Ceselli, Università degli Studi di Milano, (Italy) Nakjung Choi, Nokia, (USA) Antonio Cianfrani, University of Rome Sapienza, (Italy) Céline Comte, Eindhoven University of Technology, (The Netherlands) Rodrigo Couto, Universidade Federal do Rio de Janeiro, (Brazil) Marilia Curado, University of Coimbra, (Portugal) Luca Davoli, University of Parma, (Italy) Danny De Vleeschauwer, Nokia, (Belgium) Yuri Demchenko, University of Amsterdam, (The Netherlands) Nicola di Pietro, Athonet, (Italy) Salvatore Distefano, University of Kazan, (Russia) Maxime Elkael, Telecom Sudparis, (France) Chengyu Fan, Pure Storage, (USA) Hassan Fawaz, Télécom SudParis, (France) Mauro Femminella, University of Perugia, (Italy) Parisa Foroughi, Telecom Paris, (France) Francesca Fossati, L2S, (France) Olivier Fourmaux, Sorbonne Université, (France) Stefan Geissler, University of Wuerzburg, (Germany) Paola Grosso, University of Amsterdam, (The Netherlands) Yassine Hadjadj-Aoul, University of Rennes 1, (France) Sahar Hoteit, University Paris-SACLAY, (France) Michael Jarschel, Technische Hochschule Ingolstadt, (Germany) Yoshiaki Kiriha, Japan Science and Technology Agency, (Japan) Sándor Laki, Eötvös Loránd University, (Hungary) Stanislav Lange, NTNU, (Norway) Adrien Lebre, Inria, IMT Atlantique, LS2N, (France) Yuan Luo, Google, (USA) Vasilis Maglaris, National Technical University of Athens, (Greece) Charif Mahmoudi, Siemens, (USA) Giovanni Merlino, University of Messina, (Italy) Takashi Miyamura, NTT, (Japan) Abderrahmen Mtibaa, University of Missouri St. Louis, (USA) Augusto Neto, Federal University of Rio Grande do Norte (UFRN), (Brazil) Kenichi Ogaki, KDDI Corporation, (Japan) Christos Papadopoulos, University of Memphis, (USA) Chrysa Papagianni, University of Amsterdam, (The Netherlands) Symeon Papavassiliou, National Technical University of Athens, (Greece) Craig Partridge, Colorado State University, (USA) Dung Phung, le CNAM, (France) Ioannis Psaras, Protocol Labs, (United Kingdom (Great Britain)) Muntasir Raihan Rahman, Microsoft, (USA) Byrav Ramamurthy, University of Nebraska-Lincoln, (USA) Muhammad Taqi Raza, University of Arizona, (USA) Gianluca Reali, University of Perugia, (Italy) Bessem Sayadi, Nokia Bell-Labs, (France) Muge Sayit, Ege University, (Turkey) Anant Shah, EdgeCast, (USA) Alex Sim, Lawrence Berkeley National Laboratory, (USA) Paulo Simões, University of Coimbra, (Portugal) Bruno Sousa, University of Coimbra, (Portugal) Luca Valcarenghi, Scuola Superiore Sant'Anna, (Italy) Giacomo Verticale, Politecnico di Milano, (Italy) Lin Wang, VU Amsterdam, (The Netherlands) Huijun Wu, Twitter, (USA) Yufeng Xin, University of North Carolina, (USA) Meng Yu, Roosevelt University, (USA) Tianzhu Zhang, Nokia Bell Labs, (France) Mohamed Faten Zhani, École de Technologie Supérieure (ÉTS Montreal), University of Quebec, (Canada) Zhiming Zhao, University of Amsterdam, (The Netherlands) Michael Zink, University of Massachusetts Amherst, (USA)

1 0

ReWOrDS. deadline re-alignment (14 July 2022)
by Lofstead, Gerald F II 28 Jun '22

28 Jun '22

Deadline shifted to 14 July 2022 to better align with other eScience deadlines. rewords22: 2nd Workshop on Reproducible Workflows, Data Management, and Security Salt Lake City, UT, United States, October 11-14, 2022 Conference website https://sites.google.com/view/rewords22/home Submission link https://easychair.org/conferences/?conf=rewords22 Submission deadline 14 July 2022 Topics: reproducibility for big data/ai workflows data management tools and techniques provenance management techniques and tools reproducibility efforts and techniques This workshop explores innovations and experiences around developing portable, general, reproducible workflows while paying attention to providing open data with verifiable authenticity while protecting privacy, where needed. We are looking for community discussion and participation on the above topics plus the following. First, component packaging via containers and virtual machines, automation scripting, deployment, portability builds, and system support for these and other relevant activities. Second, provenance collection, exploration, and tracking are key for a well-documented scientific output. Third, issues with managing large data sets and workflow intermediate data, particularly those intended to manage publicly accessed data for use and reuse are encouraged. Finally, new techniques and technologies that address portability and reproducibility requirements, such as those required for peer reviewed publication, are also requested. Submission Guidelines All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome: Full papers describing emerging and future computational workloads are combining traditional HPC applications with tools and techniques from the scale out data analytics and machine learning community. Getting these technologies to co-exist and interoperate to advance scientific discovery is a daunting task with few known good solutions. In general, constructing these workflows has the potential to create pitfalls and incompatibilities that limit adoption. Formalizing the steps necessary for an application or data processing pipeline is increasingly popular and necessary. Requirements for reproducibility artifacts for publishing venues are also driving this formalization. The processes and infrastructure to accomplish these requirements are frequently bespoke or custom for a particular research area. All of these formalization activities can be described as workflow systems. Existing off-the-shelf tools address a distributed environment fairly well, but are not complete solutions and do not address the scale up community much, if at all. Complicating managing workflows are the tasks of managing data both during workflow execution and then afterwards as well as offering authentication and data security for shared data sets. With some data, such as climate simulation output, being subject to intense scrutiny, it becomes crucial to offer open data that can be verified as authentic by means of encrypted creator identities, and accessible only to people with a need to know. Sharing and analyzing the data knowing it is authentic while protecting the privacy of the creators is essential for reliable open science, while protecting the identity of the scientists performing the work. This workshop seeks to explore ideas and experiences on what kinds of infrastructure developments can improve upon the state of the art. Explorations of component packaging via containers and virtual machines, automation scripting, deployment, portability builds, and system support for these and other relevant activities are key infrastructure. Provenance collection, exploration, and tracking are key for a well documented scientific output. Using existing systems to achieve these goals via experiences are important for developing best practices that span application domains. Data privacy techniques such as multi-party encryption and differential privacy are important as well. Issues with managing large data sets and workflow intermediate data, particularly those intended to manage publicly accessed data for use and reuse are encouraged. New techniques and technologies that address reproducibility requirements are also requested. We seek work on all of these, and related, topics as well as position and experience papers looking to drive conversation for practitioners and researchers in these spaces. This workshop contributes by sharing experiences and exploring the various technological infrastructure needs to support effective, convenient workflow systems and application composition structures and approaches across a broad spectrum of HPC environments from clusters to supercomputers to cloud systems. Paper submission guidelines: Papers should be formatted in IEEE format following eScience formatting rules and can be 5 pages not including references. The format of the paper should be of double column text using single spaced 10 point size on 8.5 x 11 inch pages, as per IEEE 8.5 x 11 manuscript guidelines. Templates are available from this link. List of Topics Position and Experience papers related to scientific applications and platforms on related topics (particularly the topics listed below) Big Data or AI workflow systems like Spark, Hadoop, and Tensorflow in conjunction with data management and reproducibility efforts and techniques Front end systems for configuring or controlling workflows Data management tools and techniques Privacy preserving methods to enable data sharing Workflow engines designed to simplify workflow construction for end users Provenance management and collection techniques and tools Application-specific workflow implementations Mechanisms to support combining multiple application components into a composite application or workflow Software engineering tools and techniques to support workflow creation, execution, and use Reproducibility supporting infrastructure In situ analytics or visualization support for workflows System software/OS features to enable workflow tools and application composition Programming support for assembling workflows or connecting application components Reusable components intended as either ''glue'' between workflow components or for analysis or other processing Storage (both disk and in compute area) support for buffering between components Programming support for addressing data format/contents mismatch Programming support for resource management Program Committee Claire Bowen (Urban Institute) Juliana Freire (Reprozip) Loïc Pottier: (ISI) Rafael Ferreira Da Silva (ISI) Jakob Lüttgau: (UTK) Tom Peterka (ANL) Jay Jay Billings (Amazon) Margo Seltzer (Harvard) Hariharan Devarajan (LLNL) Dmitry Duplyakin (NREL) Organizing committee Jay Lofstead (Sandia) Jai Dayal (Intel) Anthony Kougkas (IIT) Paula Olaya (UTK) Contact All questions about submissions should be emailed to mailto:[email protected]

1 0

CFP: [AI4S] The 3rd Workshop on Artificial Intelligence and Machine Learning for Scientific Applications at SC'22
by Murali Emani 28 Jun '22

28 Jun '22

======================================================================== [AI4S]: The 3rd Workshop on Artificial Intelligence and Machine Learning for Scientific Applications To be held in conjunction with SC22 Monday, 14 November 2022, 1:30pm - 5pm CST Kay Bailey Hutchison Convention Center, Dallas, TX, USA Website: https://ai4s.github.io/ ======================================================================== -------------- Overview -------------- The purpose of this workshop is to bring together computer scientists and domain scientists from academia, government, and industry to share recent advances in the use of AI/ML to various scientific applications, introduce new scientific application problems to the broader community, and stimulate tools and infrastructures to support the application of AI/ML in scientific applications.The workshop will be organized as a series of plenary talks based on peer-reviewed paper submissions accompanied by keynotes from distinguished researchers in the area and a panel discussion. We encourage participation and submissions from universities, industry, and DOE National Laboratories. Artificial intelligence (AI)/machine learning (ML) is a game-changing technology that has shown tremendous advantages and improvements in algorithms, implementation, and applications. We have seen many successful stories of applying AI/ML to scientific applications, such as predicting extreme weather events, identifying exoplanets in trillions of sky pixels, and accelerating numerical solvers in fluid simulation. However, there are a number of problems remaining to be studied to enhance the usability of AI/ML to scientific applications. For example, how to systematically and automatically apply AI/ML to scientific applications? How to incorporate domain knowledge (e.g., conservation laws, invariants, causality and symmetries) into AI/ML models? How to make the models interpretable and robust for HPC? How to make AI/ML more approachable to the HPC community? Addressing the above problems will bridge the gap between AI/ML and scientific applications and enable wider employment of AI/ML in HPC. --------------------- Call for Papers --------------------- We solicit research papers in the following topic areas, but not be limited to: - Innovative AI/ML models to analyze, accelerate, or improve performance of scientific applications in terms of execution time and simulation accuracy; - Innovative methods to incorporate complex constraints imposed by physical principles to scientific applications; - Innovative methods to completely or partially replace first-order computation with efficient AI/ML models; - Tools and infrastructure to improve the usability of AI/ML to scientific applications; - Performance characterization and study on the possibility of using AI/ML to specific scientific applications; - Workflow of applying AI/ML to scientific applications; - Innovative methods to make AI models interpretable and robust for scientific applications. ------------------ Submissions ----------------- Authors are invited to submit manuscripts in English structured as technical papers up to 6 pages, letter size (8.5in x 11in) and including figures, tables, and references. Submissions not conforming to these guidelines may be returned without review. Your paper should be formatted using IEEE conference format which can be found from https://www.ieee.org/conferences/publishing/templates.html. All manuscripts will be peer-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 organizers for more information. Papers should be submitted electronically at: https://submissions.supercomputing.org, SC22 Workshop: AI4S'22: Workshop on Artificial Intelligence and Machine Learning for Scientific Applications". The final papers are planned to be published through IEEE. Published proceedings will be included in the IEEE Xplore digital library. ----------------------- Important Dates: ----------------------- Submission Deadline: August 2, 2022 (AoE) Notification of acceptance: September 8, 2022 Camera Ready: September 23, 2022 Workshop: November 14, 2022 -------------- Organizers -------------- Gokcen Kestor, Pacific Northwest National Laboratory Dong Li, University of California, Merced Murali Krishna Emani, Argonne National Laboratory ---------------------------- Program Committee --------------------------- Debbie Bard, Lawrence Berkeley National Laboratory Kevin Barker, Pacific Northwest National Laboratory Aparna Chandramowlishwaran, University of California, Irvine Wenqian Dong, University of California, Merced Yao Fehlis, AMD Research Olexandr Isayev, Carnegie Mellon University Jiawen Liu, Facebook Brian C Van Essen, Lawrence Livermore National Laboratory Natalia Vassilieva, Cerebras Venkatram Vishwanath, Argonne National Laboratory Laurent White, AMD Research Best Regards, Murali

1 0

PPoPP 2023: Call for Workshops and Tutorials
by shigangli.cs＠gmail.com 28 Jun '22

28 Jun '22

PPoPP 2023 will host a variety of high-quality workshops and tutorials, allowing their participants to learn about popular and new tools and technologies, to meet and discuss research questions with their peers, to mature new and exciting ideas, and to build up communities and start new collaborations. PPoPP workshops and tutorials complement the main tracks of the conference. Workshops provide meetings in a smaller and more specialized setting, and cultivate new ideas and concepts for the future, optionally recorded in formal proceedings. We are soliciting proposals for workshops and tutorials within the general scope of PPoPP. We encourage members of the community to submit proposals for workshops/tutorials that bring together researchers and practitioners to share their tools, technologies, latest results and to discuss work in progress and new directions. Workshops and tutorials will be held prior to the main conference, on Saturday-Sunday, February 25-26, 2023 and may be half a day or a full day in length. Please note that attendees of CC-2023, CGO 2023 and HPCA 2023 will also be able to register for these workshops and tutorials. Submissions Please submit proposals to the PPoPP 2023 Workshops and Tutorials Chair, Zoran Budimlić (mailto:[email protected]). Workshop and tutorial proposals will be evaluated on an ongoing basis. Early submissions are encouraged and will be evaluated immediately. Please note that for workshops that wish to publish accepted submissions in the ACM Digital Library http://www.sigplan.org/Resources/Guidelines/Workshops/ apply. Such workshops also require approval by the SIGPLAN executive committee. The key dates are as follows: • Proposal submission deadline: September 16, 2022 (AoE) • Final notification of acceptance: September 30, 2022 • Workshop/tutorial dates: February 25-26, 2023 Proposals All proposals must include the following information in a pdf file (2-3 pages): • Workshop program o Sample call for papers, including workshop title, scope, format and the main topics of the workshop o Invited or keynote speakers (if any) o Panel discussion (if any) o Organizers' bio and affiliation, and a tentative list of PC members o For each PC member: affiliation, country of affiliation, professional status/seniority o Whether or not accepted submissions will be published in the ACM Digital Library. • Tutorial program o The title and abstract of the tutorial o An outline of tutorial content and objectives o Prerequisite knowledge o Special requirements (if any) o A biography of the tutorial organizers and relevant experiences on the topic • The expected number of participants and duration of the workshop/tutorial, i.e., half day or full day • Advertisement: how do you plan to solicit participation to your workshop/tutorial (e.g., via social media, workshop/tutorial website, mailing lists etc.) • Information on past workshops/tutorials (number of attendees/submissions) on the same topic held with this or other conferences (if any). All workshop/tutorial proposals will be evaluated by a committee comprising the following members of the PPoPP 2023 organizing committee. • Zoran Budimlić (Workshops and Tutorials Chair), Texas A&M University • Milind Kulkarni (Program Co-Chair), Purdue University • Sriram Krishnamoorthy (Program Co-Chair), Pacific Northwest National Laboratories • Maryam Mehri Dehnavi (General Chair), University of Toronto For workshops that wish to publish accepted papers in the ACM Digital Library we will handle the approval process with SIGPLAN on behalf of the workshop organizers. Please refer to http://www.sigplan.org/Resources/Guidelines/Workshops/ for SIGPLAN-approved workshops. For more information, please contact the Workshops and Tutorials Chair, Zoran Budimlić (mailto:[email protected]).

1 0