Topic 12 - Accelerator Computing for Advanced Applications



Global Chair
Raphael Y. de Camargo
Federal University of ABC, Brasil, Center for Mathematicis, Computation and Cognition

Local Chair
Christian Plessl
Paderborn University, Germany

Pedro Diniz
INESC-ID, Lisboa, Portugal

Holger Fröning
University of Heidelberg, Germany

Francisco D. Igual
Universidad Complutense de Madrid, Spain

Miriam Leeser
Northern Eastern University, USA

Andy Nisbet
University of Manchester, UK




Hardware accelerators of various kinds offer a potential for achieving massive performance in applications that can leverage their high degree of parallelism and customization. Examples include graphics processors (GPUs), manycore co-processors, as well as more customizable devices, such as FPGA-based systems, and streaming data-flow architectures.

The research challenge for this topic is to explore new directions for actually realizing this potential. We encourage submissions in all areas related to accelerators: architectures, algorithms, languages, compilers, libraries, runtime systems, coordination of accelerators and CPU, and debugging and profiling tools. Application-related submissions that contribute new insights into fundamental problems or solution approaches in this domain are welcome as well, including big data, data analytics, and computational science/engineering.


  • New accelerator architectures
  • Programming models, languages, compilers, and runtime environments for accelerators
  • Tools for debugging, profiling, and optimizing programs on accelerators
  • Hybrid and heterogeneous computing mixing several, possibly different types of accelerators, and/or CPUs
  • Parallel algorithms and applications for accelerators, even beyond what is considered suitable for current accelerator architectures
  • Performance modeling and benchmarks for accelerators
  • Library support for accelerators
  • Power-aware/energy efficient solutions for accelerators



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