Description

Computational accelerators such as GPUs, FPGAs and many-core accelerators can dramatically improve the performance of computing systems and catalyze highly demanding applications. Many scientific and commercial applications are beginning to integrate computational accelerators in their code. However, programming accelerators for high performance remains a challenge, resulting from the restricted architectural features of accelerators compared to general purpose CPUs.
Moreover, software must conjointly use conventional CPUs with accelerators to support legacy code and benefit from general purpose operating system services. The objective of this topic is to provide a forum for exchanging new ideas and findings in the domain of accelerator-based computing. We encourage submissions in all areas related to accelerators: architecture, languages, compilers, libraries, runtime, debugging and profiling tools, algorithms, and applications.

Focus

• New accelerator architectures
• Language, Compilers, and Runtime environments for accelerator programming
• Programing clusters of accelerators
• Tools for debugging, profiling, and optimizing programs on accelerator
• Hybrid applications using several accelerator and/or CPUs
• Parallel algorithms for accelerators
• Models and benchmarks for accelerators
• Manual optimization and auto-tuning
• Library support for accelerators

Topic Committee

Global chair
Naoya Maruyama, RIKEN Advanced Institute for Computational Science, Japan

Local chair
Leif Kobbelt, RWTH Aachen University, Germany

Further members
Pavan Balaji, Argonne National Laboratory, USA
Nikola Puzovic, Barcelona Supercomputing Center, Spain
Samuel Thibault, University of Bordeaux, France
Kun Zhou, Zhejiang University, China