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SC 2016 : The International Conference for High Performance Computing, Networking, Storage and Analysis


Conference Series : Conference on High Performance Computing (Supercomputing)
When Nov 13, 2016 - Nov 18, 2016
Where Salt Lake City, Utah, USA
Abstract Registration Due Mar 27, 2016
Submission Deadline Apr 3, 2016
Notification Due Jun 15, 2016
Categories    high performance computing   data analytics   parallel algorithms   performance modelling

Call For Papers

SC16, the premier annual international Conference on high-performance computing, networking, storage and analysis, will be held in Salt Lake City, UT, USA, November 13-18, 2016. The Technical Papers Program at SC is the leading venue for presenting the highest-quality original research, from the foundations of HPC to its emerging frontiers. The Conference Committee solicits submissions of excellent scientific merit that introduce new ideas to the field and stimulate future trends on topics such as applications, systems, parallel algorithms, data analytics and performance modeling. SC also welcomes submissions that make significant contributions to the “state-of-the-practice” by providing compelling insights on best practices for provisioning, using and enhancing high-performance computing systems, services, and facilities.

Technical Paper Topic Areas

Submissions will be considered on any topic related to high-performance computing including, but not limited to, the nine topical areas below.

Algorithms: The development, evaluation and optimization of scalable, general-purpose, high-performance algorithms.

Topics include:

Algorithmic techniques to improve energy and power efficiency
Algorithmic techniques to improve load balance
Data-intensive parallel algorithms
Discrete and combinatorial problems
Fault-tolerant algorithms
Graph algorithms
Hybrid/heterogeneous/accelerated algorithms
Network algorithms
Numerical methods, linear and nonlinear systems
Scheduling algorithms
Uncertainty quantification
Other high-performance algorithms

Applications: The development and enhancement of algorithms, models, software and problem solving environments for domain-specific applications that require high-performance resources.

Topics include:

Bioinformatics and computational biology
Computational earth and atmospheric sciences
Computational materials science and engineering
Computational astrophysics/astronomy, chemistry, and physics
Computational fluid dynamics and mechanics
Computation and data enabled social science
Computational design optimization for aerospace, energy, manufacturing and industrial applications
Computational medicine and bioengineering
Use of uncertainty quantification techniques
Other high-performance applications

Architecture and Networks: All aspects of high-performance hardware including the optimization and evaluation of processors and networks.

Topics include:

Innovative hardware/software co-design
Interconnect technologies (e.g., InfiniBand, Myrinet, Ethernet and Routable PCI), switch/router architecture, network topologies, on-chip or optical networks and network fault tolerance
Software defined networks
Memory systems, novel memory architectures, caches
Parallel and scalable system architectures
Power-efficient, resilient, highly-available, stream, vector, embedded and reconfigurable architectures, and emerging technologies
Processor architecture, chip multiprocessors, GPUs, custom and reconfigurable logic
Protocols (e.g., TCP, UDP and sockets), quality of service, congestion management and collective communication

Clouds and Distributed Computing: All software aspects of clouds and distributed computing that are related to high-performance computing systems, including software architecture, configuration, optimization and evaluation.

Topics include:

Compute and storage cloud architectures
Data management
Problem-solving environments
Programming models and tools
Management of Quality of service and service-level agreements
Scheduling, load balancing, resource provisioning, and energy efficiency
Self-configuration, management, information services and monitoring
Service-oriented architectures and tools for integration of clouds, clusters and distributed computing
Multitenancy, virtualization, and overlays
Security and identity management

Data Analytics, Visualization and Storage: All aspects of data analytics, visualization and storage related to high-performance computing systems.

Topics include:

Databases and scalable structured storage for HPC
Data mining, analysis and visualization for modeling and simulation
Ensemble analysis and visualization
I/O performance tuning, benchmarking and middleware
Scalable storage, next-generation storage systems and media
Parallel file, storage and archival systems
Provenance, metadata and data management
Reliability and fault tolerance in HPC storage
Scalable storage, metadata and data management
Storage networks
Storage systems for data intensive computing
Data science
Visualization and image processing

Performance Measurement, Modeling, and Tools: Novel methods and tools for measuring, evaluating, and/or analyzing performance. “Performance” may be broadly construed to include any number of metrics, such as execution time, energy, power, or potential measures of resilience. Submissions in this area are encouraged to show the applicability and reproducibility of their results by means such as sensitivity analysis, performance modeling, or code snippets.

Topics include:

Analysis, modeling, or simulation methods
Empirical measurement techniques on real-world systems
Scalable tools and instrumentation infrastructure for measurement, monitoring, and/or visualization of performance
Novel, broadly applicable performance optimization techniques
Methodologies, metrics, and formalisms for performance analysis and tools
Performance studies of HPC subsystems, such as processor, network, memory and I/O
Workload characterization and benchmarking techniques

Programming Systems: Technologies that support parallel programming for large-scale systems as well as smaller-scale components that will plausibly serve as building blocks for next-generation high-performance computing architectures.

Topics include:

Programming language techniques for reducing energy and data movement (e.g., precision allocation, use of approximations, tiling)
Solutions for parallel programming challenges (e.g., interoperability, memory consistency, determinism, race detection, work stealing or load balancing)
Parallel application frameworks
Tools for parallel program development (e.g., debuggers and integrated development environments)
Program analysis, synthesis, and verification to enhance cross-platform portability, maintainability, result reproducibility, resilience (e.g., combined static and dynamic analysis methods, testing, formal methods)
Compiler analysis and optimization; program transformation
Parallel programming languages, libraries, models and notations
Runtime systems as they interact with programming systems

State of the Practice: All aspects related to novel but at the same time pragmatic practices of HPC that allow for results that are far superior with respect to time-, energy-, or cost-to-solution. These include infrastructure, services, facilities and large-scale application executions. Submissions that develop best end-to-end practices, optimized designs or benchmarks are of particular interest. Although concrete case studies within a conceptual framework often serve as the basis for accepted papers, how the experience generalizes is particularly encouraged.

Topics include:

Bridging of cloud data centers and supercomputing centers
Comparative system benchmarking over a wide spectrum of workloads
Deployment experiences of large-scale infrastructures and facilities
Facilitation of “big data” associated with supercomputing
Long-term infrastructural management experiences
Pragmatic resource management strategies and experiences
Procurement, technology investment and acquisition best practices
Quantitative results of education, training and dissemination activities
User support experiences with large-scale and novel machines
Infrastructural policy issues, especially international experiences
Software engineering best practices for HPC

System Software: Operating system (OS), runtime system and other low-level software research & development that enables allocation and management of hardware resources for high-performance computing applications and services.

Topics include:

Alternative and specialized parallel operating systems and runtime systems
Approaches for enabling adaptive and introspective system software
Communication optimization
Distributed shared memory systems
System support for global address spaces
Enhancements for attached and integrated accelerators
Interactions between the OS, runtime, compiler, middleware, and tools
Parallel/networked file system integration with the OS and runtime
Resource management
Run-time and OS management of complex memory hierarchies
System software strategies for controlling energy and temperature
Support for fault tolerance and resilience
Virtualization and virtual machines

Important Dates
Submissions Open: February 16, 2015
Abstracts Submissions Close: March 27, 2016, end of day AoE (firm deadline)
Full submissions Close: April 3, 2016 (a traditional one week extension will be given until April 10, 2016, end of day AoE no further extensions will be granted)
Review Rebuttal Period: TBD
Notification Sent: June 15, 2016

Web Submissions:
Email Contact:

SC16 Technical Papers Chair:
Lois Curfman McInnes, Argonne National Laboratory

SC16 Technical Papers Vice-Chair:
Richard Vuduc, Georgia Institute of Technology

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