HCW 2023 Call for Papers
Heterogeneity in Computing Workshop
May 15, 2023
St. Petersburg, Florida, USA
In conjunction with the 37th IEEE International Parallel and Distributed Processing Symposium (IPDPS 2023)
Sponsored by the IEEE Computer Society
through the Technical Committee on Parallel Processing (TCPP)
Most modern computing systems are heterogeneous, either for organic reasons because components grew independently, as it is the case in desktop grids, or by design to leverage the strength of specific hardware, as it is the case in accelerated systems. In any case, all computing systems have some form of hardware or software heterogeneity that must be managed, leveraged, understood, and exploited. The Heterogeneity in Computing Workshop (HCW) is a venue to discuss and innovate in all theoretical and practical aspects of heterogeneous computing: design, programmability, efficient utilization, algorithms, modeling, applications, etc. HCW 2023 will be the thirty-second annual gathering of this workshop.
Topics of interest include but are not limited to the following areas:
Heterogeneous multicore systems and architectures: Design, exploration, and experimental analysis of heterogeneous computing systems such as Graphics Processing Units, heterogeneous systems-on-chip, Artificial Intelligence chips, Field Programmable Gate Arrays, 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.
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, off-chip, and heterogeneous network architectures: Network-on-chip (NoC) architectures and protocols for heterogeneous multicore applications; energy, latency, reliability, and security optimizations for NoCs; off-chip (chip-to-chip) network architectures and optimizations; heterogeneous networks (combination of NoC and off-chip) design, evaluation, and optimizations; large-scale parallel and distributed heterogeneous 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.
Resource management and algorithms for heterogeneous systems: Parallel algorithms for solving problems on heterogeneous systems (e.g., multicores, hybrid clusters, grids, or clouds); strategies for scheduling and allocation on heterogeneous 2D and 3D multicore architectures; static and dynamic scheduling and resource management for large-scale and parallel heterogeneous systems.
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 (e.g., throughput, latency, runtime); modeling and optimizing electricity consumption (e.g., power, energy); modeling for failure management (e.g., 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; scientific computing.
In addition to the eight topic areas listed above, we encourage submissions in the following three areas:
Heterogeneous Integration of Quantum Computing: Design, exploration, and analysis of architectures and software frameworks enabling heterogeneous integration of classical computing and quantum computing (e.g., heterogeneous quantum computers, error correction, heterogeneous applications that use both classical and quantum logic, benchmarks for heterogeneous quantum computers).
Heterogeneity and Interoperability in Software & Data Systems: Design, exploration, and analysis of architectures and software frameworks for interoperability in software and data systems (e.g., semantic frameworks, interoperability for heterogeneous Internet-of-Things systems, model-driven frameworks).
Heterogeneous Computing for Machine Learning (ML) and Deep Learning (DL): Design, exploration, benchmarking, and analysis of accelerators and software frameworks for ML and DL applications on heterogeneous computing systems.
- Abstract submission (required): February 18, 2023
- Full paper submission: February 18, 2023
- Author notification: February 28, 2023
- Camera-ready submission: March 15, 2023 (extended)
Manuscripts submitted to HCW 2023 should not have been previously published or be under review for a different workshop, conference, or journal.
Submissions must use the latest IEEE manuscript templates for conference proceedings. Submissions may not exceed a total of ten single-spaced double-column pages using 10-point size font on 8.5×11 inch pages. The page limit includes figures, tables, and references. A single-blind review process will be followed.
Files should be submitted by following the instructions at the IPDPS 2023 submission site.
It is required that all accepted papers will be presented at the workshop by one of the authors.
General Chair: Jong-Kook Kim, Korea University, Korea
Technical Program Committee Co-Chairs: Anne C. Elster and Jan Christian Meyer, Norwegian University of Science and Technology, Norway
Questions may be sent to the HCW 2023 General Chair (Jong-Kook Kim: jongkook at korea dot ac dot kr) or Technical Program Committee Co-Chairs (Anne Elster: elster at ntnu dot no and Jan Christian Meyer: jan dot christian dot meyer at ntnu dot no).
Technical Program Committee
Mohsen Amini, University of Louisiana at Lafayette, USA
Taisuke Boku, University of Tsukuba, Japan
Nick Brown, University of Edinburgh, Scotland
Louis-Claude Canon, University of Franche-Comté, France
Daniel Cordiero, University of São Paulo, Brazil
Matthias Diener, University of Illinois Urbana-Champaign, USA
Anne C. Elster, Norwegian University of Science and Technology, Norway (Co-Chair)
Mattan Erez, University of Texas at Austin, USA
Jiří Filipovič, Masaryk University, Czech Republic
Diana Göhringer, Technische Universität Dresden, Germany
Emmanuel Jeannot, INRIA, France
Krishna Kavi, University of North Texas, USA
Georgios Keramidas, Aristotle University, Greece
Joongheon Kim, Korea University, Korea
Alexey Lastovetsky, University College Dublin, Ireland
Laércio Lima Pilla, CNRS, France
Hatem Ltaief, King Abdullah University of Science and Technology, Saudi Arabia
Jan Christian Meyer, Norwegian University of Science and Technology, Norway (Co-Chair)
Burcu Mutlu, Pacific Northwest National Laboratory, USA
Tirthak Patel, Northeastern University, USA
Dana Petcu, West University of Timisoara, Romania
Sridhar Radhakrishnan, University of Oklahoma, USA
Barry Rountree, Lawrence Livermore National Laboratory, USA
Achim Streit, Karlsruhe Institute of Technology, Germany
Samuel Thibault, University of Bordeaux, France
Claire Vishik, Intel, USA
Kamesh Madduri, Pennsylvania State University, USA (Co-Chair)
Behrooz Shirazi, Washington State University, USA (Co-Chair)
H. J. Siegel, Colorado State University, USA (Past Chair)
John Antonio, University of Oklahoma, USA
David Bader, New Jersey Institute of Technology, USA
Anne Benoit, École Normale Supérieure de Lyon, France
Jack Dongarra, University of Tennessee, USA
Alexey Lastovetsky, University College Dublin, UK
Sudeep Pasricha, Colorado State University, USA
Viktor K. Prasanna, University of Southern California, USA
Yves Robert, École Normale Supérieure de Lyon, France
Erik Saule, University of North Carolina at Charlotte, USA
Uwe Schwiegelshohn, TU Dortmund University, Germany