Heterogeneous computing systems comprise growing numbers of increasingly more diverse computing resources that can be local to one another or geographically distributed. The opportunity and need for effectively utilizing heterogeneous computing resources has given rise to the notions of cluster computing, grid computing, and cloud computing. HCW encourages paper submissions from both the research and industry communities presenting novel ideas on theoretical and practical aspects of computing in heterogeneous computing environments.

Submission Guidelines

HCW 2018 invites authors to submit full papers representing original, unpublished, work in all areas of heterogeneous computing that are not concurrently under review elsewhere. All submissions will be reviewed by the Program Committee. Please see the Call for Papers for more details.

Submitted manuscripts may not exceed a total of 12 single-spaced double-column pages using 10-point size font on 8.5×11 inch pages (IEEE conference style – see templates below), including figures, tables, references.

See IEEE conference style templates for details:
LaTex Package (ZIP)
Word Template (ZIP)

Authors should submit a PostScript (level 2), PDF, or Word file that will print on a PostScript printer. Electronic submission is done through EasyChair. Submit HCW 2019 papers through EasyChair.

Papers submitted to HCW 2019 should not have been previously published or be under review for a different workshop, conference or journal. Submission is a definite commitment for at least one of the authors to register and present the paper if it is accepted. Acceptance is conditional on the author(s) implementing the suggestions of the reviewers.

Camera-ready Papers
The HCW camera-ready paper page limit is set to 12 pages, following IEEE IPDPS proceedings style (the same as the submitted IEEE conference style). Please refer to the IEEE IPDPS web page for deadlines and information about how to submit the camera ready paper.

List of Topics

• Heterogeneous multicore systems and architectures: Design, exploration, and experimental analysis of heterogeneous computing systems such as GPGPUs, heterogeneous systems-on-chip (SoC), accelerator systems (e.g., Xeon Phi), FPGAs, big.LITTLE, and application-specific architectures.

  Heterogeneous parallel and distributed systems: Design and analysis of computing grids, cloud systems, hybrid clusters, datacenters, geo-distributed computing systems, and supercomputers.

  Algorithms for heterogeneous systems: Parallel algorithms for solving problems on heterogeneous systems (multicores, hybrid clusters, grids or clouds); strategies for scheduling and allocation on heterogeneous 2D and 3D multicore architectures; scheduling and resource management for large-scale and parallel heterogeneous systems.

  Deep-memory hierarchies: Design and analysis of memory hierarchies with SRAM, DRAM, Flash/SSD and HDD technologies; NUMA architectures; cache coherence strategies; novel memory systems such as phase-change RAM, magnetic (e.g., STT) RAM, 3D Xpoint/crossbars, and memristors.

  On-chip and off-chip network architectures: Network-on-chip (NoC) architectures and protocols for heterogeneous multicores and heterogeneous applications; energy, latency, reliability, and security optimizations for NoCs; off-chip (chip-to-chip) network architectures and optimizations; large scale parallel and distributed network design, evaluation, and optimizations.

  Programming models and tools: Programming paradigms and tools for heterogeneous systems; middleware and runtime systems; performance-abstraction tradeoff; interoperability of heterogeneous software environments; workflows; dataflows.

  Modeling, characterization, and optimizations: Performance models and their use in the design of parallel and distributed algorithms for heterogeneous platforms, characterizations and optimizations for improving the time to solve a problem (throughput, latency, runtime), modeling and optimizing electric consumption (power, energy); modeling for failure management (fault tolerance, recovery, reliability); modeling for security in heterogeneous platforms.

  Applications on heterogeneous systems: Case studies; confluence of Big Data systems and heterogeneous systems; data-intensive computing; deep learning; scientific computing.

Committees

Technical Program Committee

• John Antonio, University of Oklahoma, USA (TPC Chair)
• Mohsen Amini, University of Louisiana Lafayette, USA (Publicity Chair)
• Ioana Banicescu, Mississippi State University, USA
• Louis-Claude Canon, Université de Franche-Comté, France
• Florina M. Ciorba, University of Basel, Switzerland
• Daniel Cordeiro, University of São Paulo, Brazil
• Matthias Diener, University of Illinois at Urbana-Champaign, USA
• Ryan Friese, Pacific Northwest National Laboratory, USA
• Domingo Gimenez, University of Murcia, Spain
• Nicolas Grounds, MSCI, Inc., USA
• Krishna Kavi, University of North Texas, USA
• Alexey Lastovetsky, University College Dublin, Ireland
• Hatem Ltaief, KAUST, Saudi Arabia
• Dana Petcu, West University of Timisoara, Romania
• Sridhar Radhakrishnan, University of Oklahoma, USA
• Achim Streit, Karlsruhe Institute of Technology, Germany
• François Tessier, Swiss National Supercomputing Center, Switzerland
• Samuel Thibault, LaBRI, Université Bordeaux, France
• Devesh Tiwari, Northeastern University, USA

Steering Committee

• Behrooz Shirazi, Washington State University, USA, Chair
• John Antonio, University of Oklahoma, USA
• Francine Berman, Rensselaer Polytechnic Institute, USA
• Jack Dongarra, University of Tennessee, USA
• Jerry Potter, Colorado State University, USA
• Viktor K. Prasanna, University of Southern California, USA
• Yves Robert, Ecole Normale Superieure de Lyon, France
• H. J. Siegel, Colorado State University, USA
• Vaidy Sunderam, Emory University, USA
• Uwe Schwiegelshohn, TU Dortmund University, Germany

Contact

All questions about submissions should be emailed to John Antonio, antonio at ou dot edu

Sponsors

IEEE Computer Society

Office of Naval Research