30th IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC) December 18-21, 2023 Goa, India https://hipc.org/ HiPC 2023 will be the 30th 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 Authors are invited to submit original unpublished research manuscripts that demonstrate current research in all areas of high performance computing, and data science and analytics, covering all traditional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. High Performance Computing tracks: Algorithms. This track invites papers that describe original research on developing new parallel and distributed computing algorithms, and related advances. Examples of topics that are of interest include (but not limited to): - New parallel and distributed algorithms and design techniques; - Advances in enhancing algorithmic properties or providing guarantees; - Algorithmic techniques for resource allocation and optimization; - Provably efficient parallel and distributed algorithms for advanced scientific computing and irregular applications; - Classical and emerging computation models. Architecture. This track invites papers that describe original research on the design and evaluation of high performance computing architectures, and related advances. Examples of topics of interest include (but not limited to): - High performance processing architectures; - Networks for high performance computing platforms; - Memory, cache and storage architectures; - Approaches to improve architectural properties; - Emerging computational architectures. Applications. This track invites papers that describe original research on the design and implementation of scalable and high performance applications for execution on parallel, distributed and accelerated platforms, and related advances. Examples of topics of interest include (but not limited to): - Shared and distributed memory parallel applications; - Methods, algorithms, and optimizations for scaling applications on peta- and exa-scale platforms; - Hardware acceleration of parallel applications; - Application benchmarks and workloads for parallel and distributed platforms. Systems Software. This track invites papers that describe original research on the design, implementation, and evaluation of systems software for high performance computing platforms, and related advances. Examples of topics of interest include (but not limited to): - Scalable systems and software architectures for high-performance computing; - Techniques to enhance parallel performance; - Techniques to enhance parallel application development and productivity; - Techniques to deal with uncertainties, hardware/software resilience, and fault tolerance; - Software for cloud, data center, and exascale platforms; - Software and programming paradigms for heterogeneous platforms. Scalable Data Science tracks: Scalable Algorithms and Analytics. This track invites papers that describe original research on developing scalable algorithms for data analysis at scale, and related advances. Examples of topics of interest include (but not limited to): - New scalable algorithms for fundamental data analysis tasks (supervised, unsupervised learning, data (pre-)processing and pattern discovery); - Scalable algorithms that are designed to address the characteristics of different data sources and settings; - Scalable algorithms and techniques to reduce the complexity of large-scale data; - Scalable algorithms that are designed to address requirements in different data-driven application domains; - Scalable algorithms that ensure the transparency and fairness of the analysis; - Case studies, experimental studies, and benchmarks for scalable algorithms and analytics; - Scaling and accelerating machine learning, deep learning, and computer vision applications. Scalable Systems and Software. This track invites papers that describe original research on developing scalable systems and software for handling data at scale and related advances. Examples of topics of interest include (but not limited to): - New parallel and distributed algorithms and design techniques; - Design of scalable system software to support various applications; - Scalable system software for various architectures; - Architectures and systems software to support various operations in large data frameworks; - Systems software for distributed data frameworks; - Standards and protocols for enhancing various aspects of data analytics. Important dates - Abstract Submission: 30 June, 2023 - Paper Submission: 7 July, 2023 - Reviews to Authors: 25 August, 2023 - Rebuttal Period: 26 August-1 September, 2023 - 1st Round Author Notification: 22 September, 2023 - Revised Paper Submission: 14 October, 2023 - Final Author Notification: 28 October, 2023 General Co-Chairs - Chiranjib Sur, Shell, India - Neelima Bayyapu, Manipal Institute of Technology, India Vice General Co-Chairs - Sanmukh Rao Kuppannagari, Case Western Reserve University, USA - Vivek Yadav, International Institute of Information Technology, Bangalore, India Program Co-Chairs - High Performance Computing: Yogish Sabharwal, IBM Research, India - Scalable Data Science: Gerald F Lofstead II, Sandia National Laboratories, USA Program Vice-Chairs HPC Tracks - Algorithms: Jee Choi, University of Oregon, USA - Applications: Preeti Malakar, IIT Kanpur, India - Architecture: Saurabh Gupta, AMD, India - System Software: Daniele De Sensi, Sapienza University of Rome, Italy Scalable Data Science Tracks - Scalable Algorithms and Analytics: Venkat Chakaravarthy, IBM Research, India - Scalable Systems and Software: Lena Oden, Argonne National Laboratory, USA Steering Committee Chair - Viktor K. Prasanna, University of Southern California, USA Please see the following site for details: https://hipc.org/