Workshop on Accelerators and Hybrid Exascale Systems
January 8, 2016
Submitted by Antonio J. Peña
http://www.mcs.anl.gov/events/workshops/ashes/2016
The 6th International Workshop on Accelerators and Hybrid Exascale Systems (AsHES)
in conjunction with IPDPS 2016
Chicago, Illinois, USA
May 23, 2016
IMPORTANT DATES:
Paper Submission: Jan 08, 2016
Paper Notification: Feb 18, 2016
Camera-Ready: Feb 25, 2016
Current and emerging systems are deployed with heterogeneous architectures and
accelerators of more than one type (e.g. GPGPU, Intel® Xeon Phi(tm), FPGA)
along with hybrid processors of both lightweight and heavyweight cores (e.g
APU, big.LITTLE). Such architectures also comprise hybrid memory systems
equipped with stacked/hierarchical memory and non-volatile memory in addition
to regular DRAM. Programming such a system can be a real challenge along with
locality, scheduling, load balancing, concurrency and so on.
This workshop focuses on understanding the implications of accelerators and
heterogeneous designs on the hardware systems, porting applications,
performing compiler optimizations, and developing programming environments
for current and emerging systems. It seeks to ground accelerator research through
studies of application kernels or whole applications on such systems, as well
as tools and libraries that improve the performance and productivity of
applications on these systems.
The goal of this workshop is to bring together researchers and practitioners
who are involved in application studies for accelerators and other
heterogeneous systems, to learn the opportunities and challenges in future
design trends for HPC applications and systems.
Topics of interest for workshop submissions include (but are not limited to):
– Strategies for programming heterogeneous systems using high-level models
such as OpenMP, OpenACC, low-level models such as OpenCL, CUDA;
– Methods and tools to tackle challenges in scientific computing at extreme
scale;
– Strategies for application behavior characterization and performance
optimization for accelerators;
– Techniques for optimizing kernels for execution on GPGPU, Intel(R) Xeon
Phi(tm), and future heterogeneous platforms;
– Models of application performance on heterogeneous and accelerated HPC
systems;
– Compiler Optimizations and tuning heterogeneous systems including
parallelization, loop transformation, locality optimizations, Vectorization;
– Implications of workload characterization in heterogeneous and accelerated
architecture design;
– Benchmarking and performance evaluation for accelerators;
– Tools and techniques to address both performance and correctness to assist
application development for accelerators and heterogeneous processors;
– System software techniques to abstract application domain-specific
functionalities for accelerators.
SUBMISSION GUIDELINES:
Papers should present original research and should provide sufficient
background material to make them accessible to the broader community.
Submissions will be judged based on relevance, significance, originality,
correctness and clarity.
Submitted manuscripts may not exceed 10 single-spaced double-column pages
using 10-point size font on 8.5×11 inch pages (IEEE conference style),
including figures, tables, and references. See the style templates for latex
or word for details.
Submission site: https://easychair.org/conferences/?conf=ashes2016
ORGANIZING COMMITTEE:
General Chair:
James Dinan, Intel Corporation
Program Co-Chairs
Wenguang Chen, Tsinghua University, China
Sunita Chandrasekaran, University of Delaware, USA
Antonio J. Peña, Barcelona Supercomputing Center, Spain
Program Committee:
Sangmin Seo, Argonne National Laboratory, USA
Piotr Luszczek, University of Tennessee Knoxville, USA
Anthony Danalis, University of Tennessee, USA
Gabriele Jost, Intel Corporation, USA
Jeff Hammond, Intel Labs, USA
Seeyong Lee, Oak Ridge National Laboratories, USA
John Lidel, Texas Tech University, USA
James Beyer, Cray Inc., USA
Kamesh Madduri, The Pennsylvania State University, USA
Mahantesh M Halappanavar, Pacific Northwest National Laboratory, USA
Stephen Olivier, Sandia Nationl Lab, USA
Guido Juckeland, TU Dresden, Germany
Matthias Muller, TU Aachen, Germany
Barry Rountree, Lawrence Livermore National Laboratory, USA
Hennry Jin, NASA, USA
Dong Li, University of Calfornia, Merced, USA
Khaled Hamidouche, The Ohio State University, USA
Huimin Cui, Institute of Computing Technology, CAS
Xipeng Shen, North Carolina State University, USA
Bronis de Supinski, Lawrence Livermore National Laboratory, USA
Hao Wang, Virginia Tech, USA
Naoya Maruyama, RIKEN AICS
Siva Kumar Sastry Hari, NVIDIA Corporation, USA
Guangyu Sun, Peking University, China
Sriram Krishnamoorthy, Pacific Northwest National Laboratory, USA
Nacho Navarro, UPC- Univesity Politecnica de Catalunya, Spain
Kelly Shaw, University of Richmond, USA
Yongpeng Zhang, Stone Ridge Technology, USA
Fangfang Xia, Argonne National Laboratory, USA
Steering Committee:
Pavan Balaji, Argonne National Laboratory, USA
Yunquan Zhang, Chinese Academy of Sciences, China
Satoshi Matsuoka, Tokyo Institute of Technology, Japan
Jiayuan Meng, Argonne National Laboratory, USA
Xiaosong Ma, Qatar Computing Research Institute, Qatar
Barbara Chapman, University of Houston, USA
Guang R. Gao, University of Delaware, USA
Xinmin Tian, Intel, USA
Michael Wong, IBM, Canada