HiPC 2018 - 25th IEEE International Conference on High Performance Computing, Data, and Analytics (HiPC 2018)
Date2018-12-17 - 2018-12-20
Deadline2018-06-15
VenueBengaluru, India
Keywords
Websitehttps://www.hipc.org
Topics/Call fo Papers
2018 marks the Silver Anniversary of HiPC as we broaden the technical program to specifically include topics related to data science. The conference has a history of attracting participation from reputed researchers from all over the world and receives strong industry support from companies operating globally and also established in India. In addition to the two days of industry exhibits, the sponsoring partners to the conference hold industry symposiums to bring together providers and users of HPC in a forum for presenting state-of-the-art in HPC platforms and technologies, for discussing best practices, and for exchanging experiences. In the last couple years, HiPC has added workshops to its technical program and along with a Student Research Symposium and academic Birds-of-a-Feather sessions, and the conference makes room for a broad list of topics to be addressed by these events including:
Algorithms:
- Design of Parallel and Distributed Algorithms
- Algorithmic Techniques to Improve Energy and Power Efficiency
- Quantum and Bio-Inspired Algorithms
- Resilient and Fault Tolerant Algorithms
- Parallel algorithms for Numerical Linear Algebra
- Concurrent Algorithms and Data Structures
- Load Balancing, Scheduling and Resource Management
- Parallel Graph Algorithms
- Algorithms for Combinatorial Scientific Computing
- Parallel Algorithms for Computational Biology
- Streaming Algorithms
Architectures:
- Interconnection Networks and Architectures
- Cache/Memory Architecture for High Performance Computing
- High Performance/Scalable Storage Systems
- Power-Efficient and Reconfigurable Architectures
- Quantum and Bio-Inspired Architectures
- Software Support and Advanced Micro-architecture Techniques
- Resilient and Fault Tolerant Architectures
Applications:
- Big Data Computing and Applications
- Cross-Cutting Methods such as Co-Design of Parallel Algorithms, Software, and Architectures
- Emerging Applications such as Biotechnology, IoT, and Nanotechnology
- Hardware Acceleration for Parallel Applications
- Parallelism in Scientific Data Visualization and Visual Analytics
- Scientific/Engineering/Industrial Applications and Workloads
- Scalable Machine Learning and Data Mining Applications
- Scalable Graph and other Irregular Applications
- Design of Simulation Applications and Peta- and Exascale Applications
Systems Software:
Big Data Analytics Systems and Software Architectures
Compiler Technologies for High-Performance Computing
Exascale Computing, Cloud Platforms, Data Center Architectures and Services
Parallel Languages, Programming Environments, and Performance Assessment
Operating Systems for Scalable High -Performance Computing
Hybrid Parallel Programming with GPUs and Accelerators
Dealing with Uncertainties, Resilient/Fault-Tolerant Systems
DATA SCIENCE:
Big Data Algorithms and Analytics
- Transparent and interpretable predictive models
- Socially responsible learning
- Learning with changing environment, domain adaptation
- Learning with structured input and output
- Model evolution
- Large-scale Graph and network modeling and analytics
- Stream data analytics
- Model evolution
- Unsupervised learning
Big Data Systems and Software
- Data science applications in healthcare, education, social science, business, transportation, energy, telecommunications, science, and humanities
- Social mining analytics and applications
- Visual analytic systems and software using large-scale data
- Web search and recommendation systems
- Social impact systems using big data
- Privacy preserving big data software
- Massive, cross-media, streaming systems
- Human-in-the-loop systems
- Crowdsourcing and collective intelligence applications
- Large-scale data science for the social good
One or more best paper awards will be given for outstanding contributed papers.
Authors of selected high quality papers in HiPC 2018 will be invited to submit an extended version of their papers for possible publication in a special issue of Journal of Parallel and Distributed Computing.
PROGRAM CHAIRS
- Olivier Beaumont, Inria, France (High Performance Computing)
- Srinivas Aluru, Georgia Institute of Technology, USA (Data Science)
PROGRAM VICE-CHAIRS
- Algorithms: Ananth Kalyanaraman Washington State University
- Applications: Yogish Sabharwal, IBM Research – India
- Architecture: Abdou Guermouche, University of Bordeaux
- System Software: Judith Hill, Oak Ridge National Laboratory
- Big Data Algorithms and Analytics: Jun (Luke) Huan, University of Kansas
- Big Data Systems and Software: Lisa Singh, Georgetown University
---
Full information detailing what/where to submit is available on the HiPC Website at www.hipc.org as well as notices and plans for other conference events including workshops and programs for students and industry.
---
GENERAL CO-CHAIRS
Chiranjib Sur, Shell India
Yinglong Xia, Huawei Research, USA
VICE GENERAL CO-CHAIRS
Kishore Kothapalli, IIIT-Hyderabad, India
Anand Panangadan, California State University, Fullerton, USA
INDUSTRY LIAISON CO-CHAIRS
Rama Govindaraju, Google, USA
Jigar Halani, Nvidia, India
Vivek Yadav, FullStackNet, India
WORKSHOPS CO-CHAIRS
Manish Parashar, Rutgers University, USA
Anthony Simonet, Rutgers University, USA
TUTORIAL CHAIR
Saumil Merchant, Shell, India
STUDENT RESEARCH SYMPOSIUM CO-CHAIRS
Kishore Kothapalli, IIIT-Hyderabad, India
Madhura Purnaprajna, Amrita University, India
Ashok Srinivasan, Florida State University, USA
INDUSTRY, RESEARCH & USER SYMPOSIUM CO-CHAIRS
R. Badrinath, Ericcson, India
Rajeev Muralidhar, Intel, India
STEERING COMMITTEE CHAIR
Viktor K. Prasanna, University of Southern California, USA
LOCAL ARRANGEMENTS CO-CHAIRS
Rajeev Muralidhar, Intel, India
Thondiyil Venugopalan, India
---
HiPC 2018 SPONSORSHIP
---
•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)
•FIP Working Group on Concurrent Systems
•Manufacturers' Association for Information Technology (MAIT)
•National Association of Software and Service Companies (NASSCOM)
Algorithms:
- Design of Parallel and Distributed Algorithms
- Algorithmic Techniques to Improve Energy and Power Efficiency
- Quantum and Bio-Inspired Algorithms
- Resilient and Fault Tolerant Algorithms
- Parallel algorithms for Numerical Linear Algebra
- Concurrent Algorithms and Data Structures
- Load Balancing, Scheduling and Resource Management
- Parallel Graph Algorithms
- Algorithms for Combinatorial Scientific Computing
- Parallel Algorithms for Computational Biology
- Streaming Algorithms
Architectures:
- Interconnection Networks and Architectures
- Cache/Memory Architecture for High Performance Computing
- High Performance/Scalable Storage Systems
- Power-Efficient and Reconfigurable Architectures
- Quantum and Bio-Inspired Architectures
- Software Support and Advanced Micro-architecture Techniques
- Resilient and Fault Tolerant Architectures
Applications:
- Big Data Computing and Applications
- Cross-Cutting Methods such as Co-Design of Parallel Algorithms, Software, and Architectures
- Emerging Applications such as Biotechnology, IoT, and Nanotechnology
- Hardware Acceleration for Parallel Applications
- Parallelism in Scientific Data Visualization and Visual Analytics
- Scientific/Engineering/Industrial Applications and Workloads
- Scalable Machine Learning and Data Mining Applications
- Scalable Graph and other Irregular Applications
- Design of Simulation Applications and Peta- and Exascale Applications
Systems Software:
Big Data Analytics Systems and Software Architectures
Compiler Technologies for High-Performance Computing
Exascale Computing, Cloud Platforms, Data Center Architectures and Services
Parallel Languages, Programming Environments, and Performance Assessment
Operating Systems for Scalable High -Performance Computing
Hybrid Parallel Programming with GPUs and Accelerators
Dealing with Uncertainties, Resilient/Fault-Tolerant Systems
DATA SCIENCE:
Big Data Algorithms and Analytics
- Transparent and interpretable predictive models
- Socially responsible learning
- Learning with changing environment, domain adaptation
- Learning with structured input and output
- Model evolution
- Large-scale Graph and network modeling and analytics
- Stream data analytics
- Model evolution
- Unsupervised learning
Big Data Systems and Software
- Data science applications in healthcare, education, social science, business, transportation, energy, telecommunications, science, and humanities
- Social mining analytics and applications
- Visual analytic systems and software using large-scale data
- Web search and recommendation systems
- Social impact systems using big data
- Privacy preserving big data software
- Massive, cross-media, streaming systems
- Human-in-the-loop systems
- Crowdsourcing and collective intelligence applications
- Large-scale data science for the social good
One or more best paper awards will be given for outstanding contributed papers.
Authors of selected high quality papers in HiPC 2018 will be invited to submit an extended version of their papers for possible publication in a special issue of Journal of Parallel and Distributed Computing.
PROGRAM CHAIRS
- Olivier Beaumont, Inria, France (High Performance Computing)
- Srinivas Aluru, Georgia Institute of Technology, USA (Data Science)
PROGRAM VICE-CHAIRS
- Algorithms: Ananth Kalyanaraman Washington State University
- Applications: Yogish Sabharwal, IBM Research – India
- Architecture: Abdou Guermouche, University of Bordeaux
- System Software: Judith Hill, Oak Ridge National Laboratory
- Big Data Algorithms and Analytics: Jun (Luke) Huan, University of Kansas
- Big Data Systems and Software: Lisa Singh, Georgetown University
---
Full information detailing what/where to submit is available on the HiPC Website at www.hipc.org as well as notices and plans for other conference events including workshops and programs for students and industry.
---
GENERAL CO-CHAIRS
Chiranjib Sur, Shell India
Yinglong Xia, Huawei Research, USA
VICE GENERAL CO-CHAIRS
Kishore Kothapalli, IIIT-Hyderabad, India
Anand Panangadan, California State University, Fullerton, USA
INDUSTRY LIAISON CO-CHAIRS
Rama Govindaraju, Google, USA
Jigar Halani, Nvidia, India
Vivek Yadav, FullStackNet, India
WORKSHOPS CO-CHAIRS
Manish Parashar, Rutgers University, USA
Anthony Simonet, Rutgers University, USA
TUTORIAL CHAIR
Saumil Merchant, Shell, India
STUDENT RESEARCH SYMPOSIUM CO-CHAIRS
Kishore Kothapalli, IIIT-Hyderabad, India
Madhura Purnaprajna, Amrita University, India
Ashok Srinivasan, Florida State University, USA
INDUSTRY, RESEARCH & USER SYMPOSIUM CO-CHAIRS
R. Badrinath, Ericcson, India
Rajeev Muralidhar, Intel, India
STEERING COMMITTEE CHAIR
Viktor K. Prasanna, University of Southern California, USA
LOCAL ARRANGEMENTS CO-CHAIRS
Rajeev Muralidhar, Intel, India
Thondiyil Venugopalan, India
---
HiPC 2018 SPONSORSHIP
---
•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)
•FIP Working Group on Concurrent Systems
•Manufacturers' Association for Information Technology (MAIT)
•National Association of Software and Service Companies (NASSCOM)
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- Adorning our new biosphere: how to love the postcarbon world
- 13th International Conference on Law, Economics, Business and Corporate Social Responsibilities
- 14th DUBAI International Conference on Biological, Agricultural, Environmental & Medical Sciences
- 11th International Conference on Computer, Electrical and Electronics Engineering & Technology
Last modified: 2018-04-22 15:01:30