Conference Information
SC 2016 : International Conference for High Performance Computing, Networking, Storage, and Analysis
Submission Date:
Notification Date:
Conference Date:
Salt Lake City, Utah, USA
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Conference Location
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

New this Year:

Double-Blind Review: SC16 will use a double-blind review process, which is a change from prior years. Details will appear on the SC16 website by March 1, 2016.

Reproducibility Initiative: As part of a major initiative that aims to increase the level of reproducibility and replicability of results, SC16 invites authors of technical papers to volunteer to publish their methodology, code and data with the paper, if their paper is accepted to SC16. Details will appear on the SC16 website by March 1, 2016.
Last updated by Dou Sun in 2016-02-23
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