HiPC 2018 will feature the 11th Student Research Symposium (SRS) on High Performance Computing, Data, and Analytics (HPC) aimed at stimulating and fostering student research, and providing an international forum to highlight student research accomplishments. The symposium will also provide exposure to students in the best practices in HPC in academia and industry.
The symposium will feature student posters and provide students with other enriching experiences, such as workshops, industry exhibits, and demos. The Conference Reception and multiple Student Symposium Poster Exhibit sessions will provide an opportunity for students to interact with HPC researchers and practitioners (and recruiters) from academia and industry.
Awards for Best Poster, sponsored by the IEEE Computer Society – Technical Committee on Parallel Processing, will be presented at the symposium. An online book containing the resumes of the students participating in the symposium will be compiled and made available to the sponsors of the HiPC 2018 conference.
Papers are solicited in all areas of high-performance computing, data, and analytics, including but not limited to topics mentioned below.
High Performance Computing
• 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
• 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
• 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
• 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
Big Data Algorithms and Analytics
• Transparent and interpretable predictive models
• Socially responsible learning
• Learning with changing the 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
Submission Platform Opens: 19 August 2018
Submission Deadline: 16 September 2018 30 September 2018
Notice of Accept/Reject Decision: 9 November 2018
Symposium Dates:17-20 December 2018
Submissions should have at least one author who is a student during any part of the calendar year 2018. Submissions may have multiple student or non-student co-authors. Submissions must mark student authors with an asterisk (*).
In order to be considered for a poster at the Student Research Symposium (SRS), authors must submit papers, not exceeding five (5) letter size (8.5in x 11in) pages, in 11 or 12 point font, single spaced, with 1” margins on all sides. Papers are to be submitted online in PDF format through Easychair here. The deadline for submissions is 16 September 2018 30 September 2018.
The papers will be used to select posters, but will NOT be published in the conference proceedings. This will provide students with the flexibility to publish an extended version of their paper at other venues, after benefiting from reviewer feedback from the symposium. Papers submitted to the symposium are expected to be reviewed by at least three independent reviewers. Papers will be judged on technical merit, quality, relevance to the symposium, and related parameters. Plagiarism is prohibited. Papers that are plagiarized will be rejected and the corresponding department and institution will be notified.
Facilities for displaying posters will be made available and the exact specifications of the poster size will be provided later. At least one student author of each paper that is accepted must register and attend the conference to present their work. Papers with no-shows will be retroactively rejected.
We expect to provide a travel scholarship to at least one student author of each accepted submission from an Indian university, subject to availability of funding. This scholarship will cover partial expenses for attending the conference. Further details on this scholarship and the application process will be provided later.
• Ashok Srinivasan, University of West Florida, USA
• Ramakrishna Upadrasta, IIT-Hyderabad, India
Contact student_symposium[at]hipc[dot]org for more details.