June 8, 2020
June 15, 2020
27th IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC)
16–19 December, 2020
Submissions Due: June 15, 2020
HPC: Bora Uçar, CNRS and ENS Lyon, France
Data Science: Gagan Agrawal, Augusta University, USA
Algorithms: Kamesh Madduri, Pennsylvania State University, USA
Applications: Yogesh Simmhan, Indian Institute of Science, India
Architecture: Biswabandan Panda, IIT Kanpur, India
System Software: Marco Aldinucci, University of Torino, Italy
DATA SCIENCE TRACKS
Scalable Algorithms and Analytics: Bingsheng He, National University of Singapore
Scalable Systems and Software: Suren Byna, Lawrence Berkeley National Laboratory, USA
HiPC 2020 will be the 27th edition of the IEEE International Conference on High Performance Computing, Data, Analytics and Data Science. HiPC serves as a forum to present current work by researchers from around the world as well as highlight activities in Asia in the areas of high performance computing and data science. The meeting focuses on all aspects of high performance computing systems, and data science and analytics, and their scientific, engineering, and commercial applications.
Authors are invited to submit original unpublished research manuscripts that demonstrate current research in all areas of high performance computing, and data science and analytics, covering all traditional areas and emerging topics including from machine learning, big data analytics and blockchain. Each submission should be submitted to one of the tracks listed under the two broad themes of High Performance Computing and Data Science.
Up to two best paper awards will be given for outstanding contributed papers.
HIGH PERFORMANCE COMPUTING
Algorithms. This track invites papers that describe original research on developing new parallel and distributed computing algorithms, and related advances. Examples of topics that are of interest include (but not limited to):
* New parallel and distributed algorithms and design techniques;
* Advances in enhancing algorithmic properties or providing guarantees (e.g., fault tolerance, resilience, concurrency, data locality, communication-avoiding);
* Algorithmic techniques for resource allocation and optimization (e.g., scheduling, load balancing, resource management);
* Provably efficient parallel and distributed algorithms for advanced scientific computing and irregular applications (e.g., numerical linear algebra, graph algorithms, computational biology);
* Classical and emerging computation models (e.g., parallel/distributed models, quantum computing, neuromorphic and other bioinspired models).
Architecture. This track invites papers that describe original research on the design and evaluation of high performance computing architectures, and related advances. Examples of topics of interest include (but not limited to):
* High performance processing architectures (e.g., reconfigurable, system-on-chip, manycores, vector processors);
* Networks for high performance computing platforms (e.g., interconnect topologies, network-on-chip);
* Memory, cache and storage architectures (e.g., 3D, photonic, Processing-In-Memory, NVRAM, burst buffers, parallel I/O);
* Approaches to improve architectural properties (e.g., energy/power efficiency, reconfigurable, resilience/fault tolerance, security/privacy);
* Emerging computational architectures (e.g., quantum computing, neuromorphic and other bioinspired architectures).
Applications. This track invites papers that describe original research on the design and implementation of scalable and high performance applications for execution on parallel, distributed and accelerated platforms, and related advances. Examples of topics of interest include (but not limited to):
* Shared and distributed memory parallel applications (e.g., scientific computing, simulation and visualization applications, graph and irregular applications, data-intensive applications, science/engineering/industry applications, emerging applications in IoT and life sciences, etc.);
* Methods, algorithms and optimizations for scaling applications on peta- and exa-scale platforms (e.g., co-design of hardware and software, heterogeneous and hybrid programming);
* Hardware acceleration of parallel applications (e.g., GPUs, FPGA, vector processors, manycore);
* Application benchmarks and workloads for parallel and distributed platforms.
Systems Software. This track invites papers that describe original research on the design, implementation and evaluation of systems software for high performance computing platforms, and related advances. Examples of topics of interest include (but not limited to):
* Scalable systems and software architectures for high performance computing (e.g., middleware, operating systems, I/O services);
* Techniques to enhance parallel performance (e.g., compiler/runtime optimization, learning from application traces, profiling);
* Techniques to enhance parallel application development and productivity (e.g., Domain-Specific Languages, programming environments, performance/correctness checking and debugging);
* Techniques to deal with uncertainties, hardware/software resilience, and fault tolerance;
* Software for cloud, data center, and exascale platforms (e.g., middleware tools, schedulers, resource allocation, data migration, load balancing);
* Software and programming paradigms for heterogeneous platforms (e.g., libraries for CPU/GPU, multi-GPU clusters, and other accelerator platforms).
Scalable Algorithms and Analytics. This track invites papers that describe original research on developing scalable algorithms for data analysis at scale, and related advances. Examples of topics of interest include (but not limited to):
* New scalable algorithms for fundamental data analysis tasks (supervised, unsupervised learning, and pattern discovery);
* Scalable algorithms that are designed to address the characteristics of different data sources and settings (e.g., graphs, social networks, sequences, data streams);
* Scalable algorithms and techniques to reduce complexity of large-scale data (e.g., streaming, sublinear data structures, summarization, compressive analytics);
* Scalable algorithms that are designed to address requirements in different data-driven application domains (e.g., life sciences, business, agriculture);
* Scalable algorithms that ensure the transparency and fairness of the analysis;
* Case studies, experimental studies and benchmarks for scalable algorithms and analytics;
* Scaling and accelerating machine learning, deep learning and computer vision applications.
Scalable Systems and Software. This track invites papers that describe original research on developing scalable systems and software for handling data at scale, and related advances. Examples of topics of interest include (but not limited to):
* Design of scalable system software to support various applications (e.g., recommendation systems, web search, crowdsourcing applications, streaming applications)
* Scalable system software for various architectures (e.g., OpenPower, GPUs, FPGAs).
* Architectures and systems software to support various operations in large data frameworks (e.g., storage, retrieval, automated workflows, data organization, visualization, visual analytics, human-in-the-loop);
* Systems software for distributed data frameworks (e.g., distributed file system, virtualization, cloud services, resource optimization, scheduling);
* Standards and protocols for enhancing various aspects of data analytics (e.g., open data standards, privacy preserving and secure schemes).
IMPORTANT DATES (2020)
Abstract Submissions : June 8, 2020
Paper Submissions : June 15, 2020
Reviews for Rebuttals: August 4, 2020
Initial Submission Decisions: August 21, 2020
Revisions Due: September 22, 2020
Author Notifications: October 2, 2020
Camera Ready: October 16, 2020
Submitted papers must represent original unpublished research that is not currently under review for any other conference or journal. Papers not following these guidelines will be rejected without review and further action may be taken, including (but not limited to) notifications sent to the heads of the institutions of the authors and sponsors of the conference. Submissions received after the due date, exceeding length limit, or not appropriately structured may also not be considered. Authors may contact the Program Chair at the email address below for further information or clarification. A published proceedings will be available at the conference.
At least one author of each paper must be registered for the conference in order for the paper to be published in the proceedings. Presentation of an accepted paper at the conference in person is a requirement of publication. Any paper that is not presented at the conference will not be included in IEEE Xplore.
Authors of selected high quality papers in HiPC 2020 will be invited to submit extended versions of their papers for possible publication in a special issue of Journal of Parallel and Distributed Computing.
Submit your paper: https://easychair.org/conferences/?conf=hipc2020.
HiPC 2020 is co-sponsored by
* IEEE Computer Society Technical Committee on Parallel Processing (TCPP)
* HiPC Education Trust, India
In cooperation with:
* ACM Special Interest Group on Algorithms and Computation Theory (SIGACT);
* ACM Special Interest Group on Computer Architecture (SIGARCH);
* IFIP Working Group on Concurrent Systems;
* Manufacturers’ Association for Information Technology (MAIT);
* National Association of Software and Service Companies (NASSCOM).