Artificial intelligence (AI), machine learning (ML), and deep learning (DL) have established themselves in a multitude of domains because of their ability to process and model unstructured input data. As these fields are becoming increasingly integrated into our daily lives, there is a significant amount of interest among the community in improving AI/ML/DL through the use of parallel and distributed computing techniques (sometimes referred to as “PDC for AI/ML/DL”) as well as to apply AI/ML/DL techniques to improve traditional parallel and distributed computing systems (sometimes referred to as “AI/ML/DL for PDC”). In this special section, we hope to bring together community research in this area into a curated selection of articles.
About TPDS special sections
TPDS has recently started a new initiative called “special sections.” Compared with regular submissions to TPDS, special sections have some differences: (1) submissions are focused on special topics of interest (similar to special issues); (2) special sections have fixed deadlines for submission and notifications; and (3) special sections have a standing committee of reviewers similar to conferences. This is the first such special section that we are planning.
The timeline for the submission and review process is as follows (all deadlines are midnight anywhere on earth (https://www.worldtimeserver.com/time-zones/aoe/).
- Submission deadline: July 1st, 2020 (no extensions)
- First-round review notification: August 5th, 2020 (5 weeks for reviews)
- Notification would be one of ACCEPT, REJECT, MAJOR REVISIONS, or MINOR REVISIONS
Round 2a (only for papers that get a minor revision in Round 1):
- Second-round submission deadline: August 19th, 2020 (2 weeks for re-submission)
- Second-round review notification: September 2nd, 2020 (2 weeks for reviews)
- Notification would be one of ACCEPT or REJECT
Round 2b (only for papers that get a major revision in Round 1):
- Second-round submission deadline: September 2nd, 2020 (4 weeks for re-submission)
- Second-round review notification: September 30th, 2020 (4 weeks for reviews)
- Notification would be one of ACCEPT, REJECT, or MINOR REVISIONS
Round 3 (only for papers that got a minor revision in Round 2b):
- Third-round submission deadline: October 14th, 2020 (2 weeks for re-submission)
- Third-round review notification: October 28th, 2020 (2 weeks for reviews)
- Notification would be one of ACCEPT or REJECT
Topics of interest
The special section is dedicated to parallel and distributed computing (PDC) techniques for AI/ML/DL. That includes both “PDC for AI/ML/DL”- and “AI/ML/DL for PDC”-oriented articles (please see the description above). Topics of interest include, but are not limited to:
- AI/ML/DL for PDC and PDC for AI/ML/DL
- Data parallelism and model parallelism
- Efficient hardware for AI, ML, and DL
- Hardware-efficient training and inference
- Performance modeling of AI/ML/DL applications
- Scalable optimization methods for AI/ML/DL
- Scalable hyper-parameter optimization
- Scalable neural architecture search
- Scalable IO for AI/ML/DL
- Systems, compilers, and languages for AI/ML/DL at scale
- Testing, debugging, and profiling AI/ML/DL applications
- Visualization for AI/ML/DL at scale
Submissions to the special section will be received as TPDS regular papers (survey and comment-style papers are not allowed). Please check submission instructions including page limit, manuscript format, and submission guidance on the TPDS Author Information page. Please note that review versions of the papers are limited to 12 pages, and overlength page charges are only for the final versions of the papers.
Similar to regular TPDS papers, you can extend previous conference papers and submit them to this special section. However, please note the following:
- All papers need to have sufficient new content (extension material). While the amount of new content is subjective and depends on the reviewer, we estimate that most reviewers expect close to 70% new material.
- Acceptance of the paper is based on the new content. Old content from previous conference papers is mainly to help reviewers understand the context.
- Old content should be clearly cited from the original source.
- Old content should be rephrased, and not copied verbatim, to avoid self-plagiarism.
Submissions are *NOT* double blind. Authors can disclose their names, and they can freely cite their previous work without referring to it in a third-party fashion.
Authors can submit papers till the deadline through ScholarOne. Once you start the submission process, in Step 1 of the process, you’ll be asked to pick a “Type” for the paper. Please pick “SS for Parallel and Distributed Computing Techniques for AL, ML and DL.”
- Pavan Balaji (Argonne National Laboratory)
- Jidong Zhai (Tsinghua University)
- Min Si (Argonne National Laboratory)
- Adrián Castelló, Universitat Jaume I de Castello, Spain
- Amelie Chi Zhou, Shenzhen University, China
- Ang Li, Pacific Northwest National Laboratory, USA
- Bin Ren, College of William and Mary, USA
- Bronis de Supinski, Lawrence Livermore National Laboratory, USA
- Dandan Song, Beijing Institute of Technology, China
- David Liu, State University of New York at Binghamton, USA
- Feng Zhang, Renmin University, China
- Guangming Tan, Institute of Computing Technology, Chinese Academy of Sciences, China
- Huansong Fu, Amazon, USA
- Jintao Meng, Shenzhen Institutes of Advanced Technologies, China
- Jorge G. Barbosa, Universidade do Porto, Portugal
- Quan Chen, Shanghai Jiaotong University, China
- Shanjiang Tang, Tianjin University, China
- Sridutt Bhalachandra, Lawrence Berkeley National Laboratory, USA
- Stefano Markidi, KTH Royal Institute of Technology, Sweden
- Sunita Chandrasekaran, University of Delaware, USA
- Xiaoyi Lu, The Ohio State University, USA
- Zhiyi Huang, University of Otago, New Zealand