[hpc-announce] [SC18] Call for Papers for the ACM/IEEE International Conference for High Performance Computing, Networking, Storage, and Analysis (Supercomputing 2018)

Torsten Hoefler htor at inf.ethz.ch
Mon Feb 12 11:54:25 CST 2018

                              CALL FOR PAPERS

  The International Conference for High Performance Computing, Networking,
                           Storage, and Analysis
                      ***  Supercomputing SC18  ***

                        Sponsored by ACM and IEEE


The Papers program at SC is the leading venue for the presentation of the
highest-quality original research, groundbreaking ideas, and compelling
insights on future trends. The conference is soliciting paper submissions
around high performance computing and other neighboring areas.


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

1. 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
- Statistical and machine learning algorithms
- Hybrid/heterogeneous/accelerated algorithms
- Network algorithms
- Numerical methods, linear and nonlinear systems
- Scheduling algorithms
- Uncertainty quantification
- Other high performance algorithms

2. 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
- Statistical and machine learning applications
- Other high performance applications

3. 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 multi-processors, GPUs, custom and
   reconfigurable logic
- Protocols (e.g., TCP, UDP and sockets), quality of service, congestion
   management and collective communication

4. 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 including many-core computing
   and accelerators in the cloud.
- Innovative methods for using cloud systems for HPC applications
- Workflow, data and resource management including dynamic resource
- Methods, systems and architectures for data stream processing
- Parallel programming models and tools at the intersection of cloud and
- Support and tuning of MapReduce/Spark and other cloud data ecosystems
   on HPC
- Scheduling, load balancing, resource provisioning, energy efficiency,
   fault tolerance and reliability
- Self-configuration, management, information services and monitoring
- Service-oriented architectures and tools for integration of clouds,
   clusters and distributed computing
- Virtualization and containerization for HPC, virtualized high
   performance I/O network interconnects, parallel and distributed file
   systems in virtual environments
- Cloud security and identity management

5. 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

6. 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
- Performance studies of HPC subsystems, such as processor, network,
   memory and I/O
- Workload characterization and benchmarking techniques

7. 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
- 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

8. 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

9. 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
- 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
- Runtime 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


Submissions open:             March 1, 2018
Abstract deadline:            March 19, 2018
Submission deadline:          March 28, 2018 (NO EXTENSIONS)
Reviews sent:                 May 14, 2018
Resubmissions deadline:       May 30, 2018
Notifications sent:           June 15, 2018
Major revision deadline:      July 13, 2018
Major revision notifications: August 10, 2018

The SC18 proceedings will be published electronically via the ACM and
IEEE Digital Libraries. Submitted manuscripts should be formatted
using the IEEE Master article template. The maximum length is 10 pages.
All papers must be in English. Please visit the SC18 website for further
instructions and the submission link.


Torsten Hoefler      ETH Zurich, Switzerland
Todd Gamblin         Lawrence Livermore National Laboratory

### qreharg rug ebs fv crryF --- http://htor.inf.ethz.ch/ ---
Torsten Hoefler           | Associate Professor
Dept. of Computer Science | ETH Zürich
Universitätsstrasse 6     | Zurich-8092, Switzerland
CAB F 75                  | Phone: +41 44 632 68 79

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