Conference Information
SC 2017 : International Conference for High Performance Computing, Networking, Storage, and Analysis
Submission Date:
Notification Date:
Conference Date:
Denver, Colorado, USA
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Conference Location
Call For Papers
SC17, the premier annual international Conference on high-performance computing, networking, storage and analysis, will be held in Denver, CO, USA, November 12-17, 2017. 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 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, fluid dynamics, mechanics and physics
    • Computation and data enabled 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 and novel memory architectures
    • Parallel and scalable system architectures
    • Power-efficient, high-availability, stream, vector, embedded and reconfigurable architectures, and emerging technologies
    • Processor architecture, chip multiprocessors, GPUs, cache, and memory subsystems
    • Protocols (e.g., TCP, UDP and sockets), quality of service, congestion management and collective communication

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

Topics include:

    Compute and storage cloud architectures
    • Data management and scientific applications
    • Problem-solving environments and portals
    • Programming models and tools for computing on clouds and grids
    • Quality of service and service-level agreement management
    • Scheduling, load balancing, workflows and resource provisioning
    • Security and identity management
    • Self-configuration, management, information services and monitoring
    • Service-oriented architectures and tools for integration of clouds, clusters and distributed computing
    • Virtualization and overlays

    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
    • I/O performance tuning, benchmarking and middleware
    • Next-generation storage systems and media
    • Parallel file, storage and archival systems
    • Provenance
    • Reliability and fault tolerance in HPC storage
    • Scalable storage, metadata and data management
    • Storage networks
    • Storage systems for data intensive computing
    • Visualization and image processing

    Performance: Cross-cutting aspects of large-scale performance, including power and/or resilience, that typically span multiple areas of expertise and are crucial factors in the design of scalable high-performance computing systems.

Topics include:

    Analysis, modeling or simulation for performance, power and/or resilience
    • Empirical measurement of performance, power and/or resilience on real-world systems
    • Methodologies and formalisms for performance, power and/or resilience
    • Methodologies, metrics and workloads for performance, power and/or resilience analysis and tools
    • Performance, power and/or resilience analysis beyond execution time and flop/s
    • Performance, power and/or resilience studies of HPC subsystems, such as processor, network, memory and I/O
    • Tools, code instrumentation and instrumentation infrastructure for measurement and monitoring of performance, power and/or resilience
    • Workload characterization and benchmarking

    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:

    Compiler analysis and optimization; program transformation
    • Parallel application frameworks
    • Parallel programming languages, libraries, models and notations
    • Runtime systems
    • Solutions for parallel programming challenges (e.g., interoperability, memory consistency, determinism, race detection, work stealing or load balancing)
    • Tools for parallel program development (e.g., debuggers and integrated development environments)

    State of the Practice: All aspects related to the pragmatic practices of HPC, including infrastructure, services, facilities and large-scale application executions. Submissions that develop best 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 to wider applicability should be explored.

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

    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
    • 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
Last updated by Dou Sun in 2017-01-29
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