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 Authors are invited to submit original unpublished research manuscripts that demonstrate current research in all areas of high performance computing, and data science and analytics, covering all traditional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 CALL FOR WORKSHOP PROPOSALS https://hipc.org/call-for-workshop-proposals/ Complementing the main technical program, HiPC workshops serve to broaden the technical scope of the conference in emerging areas of high performance computing, networking, data analytics, and their applications. Held on the first day of the conference, HiPC workshops will typically be half-day events (3 - 3.5hrs) although proposals for full-day (6 - 7 hrs) workshops will also be considered. Workshops should have contributed papers in their program, and can have invited talks, poster sessions, and panel discussions as part of their technical program. Workshop organizers are responsible for preparing the call for papers to their workshops and also peer-review all submissions in accordance with the conference and IEEE guidelines. Papers accepted for presentation at the HiPC 2022 workshops will be included in the workshops volume of the conference proceedings with a separate ISBN (HiPCW 2022) and will be distributed online; unless the workshop organizers want it otherwise. Post-conference, papers presented at the conference and eligible for inclusion will be made available to the IEEE Xplore Digital Library. Workshop Themes The topics of the proposed workshop should complement those listed in the main conference call for papers. Each workshop should be centered around a coherent theme or topic related to HPC and/or scalable data science; We particularly encourage workshop themes that relate to emerging areas and/or emerging application contexts of societal value (e.g., agriculture, energy, sustainability, workforce development). What/Where to Submit Potential HiPC workshop organizers should submit a workshop proposal that contains the items listed below. The proposal should also specify steps to be taken to develop a high-quality program committee and attract high-quality submissions to place the workshop(s) in a competitive international landscape. In case, submitting a full day workshop, the organizers should explain how they will attract sufficient participation to develop a full day program of peer-reviewed papers. Proposals to organize a workshop at HiPC 2022 should include: - Description: title; topics to be addressed; goals; relevance and significance to the main conference. - Names, affiliations and contact information for organizers, along with prior experience in organizing such events, if any. - Plans for soliciting submissions, and the process for selecting papers to be presented at the workshop and included in the workshop proceedings. - Tentative names of Keynote/ invited speakers - Tentative program outline, identifying key elements such as panels, discussion sessions, poster sessions, invited talks, etc. - Tentative list of PC members to be recruited - A detailed timeline of the peer-review process The proposal should not exceed three pages and should be submitted as a pdf file to the HiPC Workshops Chairs at workshops@hipc.org. For additional information about organizing an HiPC workshop, see the FAQs sheet on the website: https://hipc.org/call-for-workshop-proposals/ Deadlines and Important Dates - Workshop proposal submissions: June 15, 2022 - Workshop proposal notifications: Jul 15, 2022 - Workshop Website and CFP: Aug 1, 2022 Workshop Co-Chairs - V. Krishna Nandivada, IIT Madras - Ananth Kalyanaraman, Washington State University