PAMLA 2018

With more and more big data, parallel and distributed computing is increasingly more demanding for AI and machine learning practitioners. Taking advantage of parallel and distributed computing can increase the speed of AI and machine learning algorithms, and solve a big data problem with a feasible and better solution.

This workshop will bring together researchers in parallel and distributed computing, machine learning, and artificial intelligence to discuss state-of-the-art parallelization techniques for AI and machine learning algorithms, identify critical big data and AI applications demanding parallelization, and promote parallel and distributed computing among AI practitioners and domain experts.

Important Dates

Paper submission deadline : August 27, 2018 extended to September 24, 2018 (Anywhere On Earth)
Notification of acceptance : October 12, 2018
Camera-ready papers due : October 26, 2018

Objectives, scope and topics of the workshop

The program committee cordially invites any novel research ideas in (but not limited to) the following topics:

• Various parallel/distributed algorithms for AI and machine learning
• Multicore computing
• GPU-based computing
• Cluster-based distributed computing
• Cloud-based parallel computing
• Hardware-based (e.g. FPGA) parallel computing
• Parallel computing environments and tools, e.g., OpenMP, MPI
• Performance evaluation
• Tradeoff between performance and learning quality

Names and contacts of key organizers

Organization co-chairs

Quan Chen
Shanghai Jiaotong University, China
chen-quan at cs dot sjtu dot edu dot cn

Zhiyi Huang
University of Otago, New Zealand
hzy at cs dot otago dot ac dot nz

Programme Committee

• Andrew Ensor, Auckland University of Technology
• Chen Ding, University of Rochester, USA
• Qinfen Hao, ICT, Chinese Academy of Sciences, China
• Huansong Fu, Argonne National Laboratory
• Laurent Lefevre, INRIA, University of Lyon, France
• Chao Li, Shanghai Jiao Tong University
• Zechao Li, Nanjing University of Science and Technology
• Xiaoyi Lu, Ohio State University, USA
• Jean-Marc Pierson, University of Toulouse
• Min Si, Argonne National Laboratory
• Oliver Sinnen, University of Auckland, New Zealand
• Peter Strazdins, Australian National University, Australia
• Xiaoxin Tang, Shanghai University of Finance and Economics
• Bo Wu, Colorado School of Mines
• Yongwei Wu, Tsinghua University
• Hailong Yang, Beihang University
• Qing Yi, University of Colorado at Colorado Springs

Manuscript submission

Papers reporting original and unpublished research results and experience are solicited. All paper submissions will be handled electronically via EasyChair.

Papers must not exceed 8 pages in double-column ACM sigconf style. Templates for the ACM sigconf style are available at here.

Authors must register and submit their paper through the online submission system. If you have problems accessing the system, e-mail your submission to:
pamla2018 at cs dot otago dot ac dot nz

Proceedings

All accepted papers will be published in the a joint Proceedings of AI Workshops to be published by ACM (approved).

Registration

Information about registration can be found at AI 2018 website.

Contact Us

For further information regarding the workshop and paper submission, please send your request or enquiry to: pamla2018 at cs dot otago dot ac dot nz