[Storage-research-list] CfP: 29th IEEE International Conference on High Performance Computing, Data & Analytics (HiPC 2022)

[Anand Panangadan]

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Authors are invited to submit original unpublished research manuscripts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
Topics for papers include, but are not limited to the topics given under
the categories below.

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., 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: 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, 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: 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 DATA SCIENCE
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 (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: 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 (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

Steering committee chair:
- Viktor K. Prasanna, University of Southern California, 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
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