[hpc-announce] CFP: iWAPT 2021 (IPDPS2021 Workshop, Deadline: Jun. 25)

[Satoshi Ohshima]

[Apologies if you receive multiple copies of this email.]

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:: iWAPT 2021 :: CALL FOR PAPERS
The 16th International Workshop on Automatic Performance Tuning
http://www.iwapt.org/2021/
  
May 21, 2021 at Portland Hilton Downtown,
Portland, Oregon USA
  
The iWAPT 2021 will be held in conjunction with IPDPS 2021.
http://www.ipdps.org/
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# Important dates

Paper submission due:	January 25, 2021 (AOE)
Author Notification:	March 1, 2021
Camera ready papers:	March 12, 2021
Conference sessions:	May 21, 2021

  
Submission site:
https://easychair.org/conferences/?conf=iwapt2021
(If you do not have an EasyChair account, please create it first.)
  
# About iWAPT
  
iWAPT (International Workshop on Automatic Performance Tuning) is a series of workshops that focus on research and techniques that address performance sustainability issues. It provides an opportunity for researchers and users of automatic performance tuning (AT) technologies to exchange ideas and experiences while applying such technologies to improve the performance of algorithms, libraries, and applications; in particular, on cutting edge computing platforms. The full-day workshops consist of invited keynote speaker presentations and 30-minute presentations of well-founded papers. Occasionally, exploratory papers are also accepted. Topics of interest include performance modeling, adaptive algorithms, autotuned numerical algorithms, libraries and scientific applications, empirical compilation, automated code generation, frameworks and theories of AT and software optimization, autonomic computing, and context-aware computing.
  
We are particularly interested in autotuning and its relationship to the
following areas (the list is not exhaustive):

* Applying machine learning to autotuning
* Machine-adaptive algorithms
* Automatic program generation
* Performance analysis and modeling
* Adaptive numerical algorithms and libraries
* Multi- and manycore systems, heterogeneous architectures challenges
* Compilation strategies (e.g. iterative and empirical compilers)
* Programming models
* Runtime systems
* Empirical search heuristics
* Power- and/or energy-aware computing
  
# Paper Submission guidelines
  
Submitted manuscripts may not exceed ten (10) single-spaced
double-column pages using 10-point size font on 8.5x11 inch pages
(IEEE conference style), including figures, tables, and references.
See style templates for details:
  
LaTex Package (ZIP):
http://www.ipdps.org/templates/IEEECS_CPS_LaTeX_Letter_2Col.zip
  
Word Template (ZIP):
http://www.ipdps.org/templates/IEEECS_CPS_8.5x11x2.zip
  
Files should be submitted by following the instructions available at the EasyChair portal.
http://www.easychair.org/conferences/?conf=iwapt2021

Authors must ensure that electronically submitted files are formatted in PDF format for 8.5x11 inch paper.
Accepted submissions will be included in the IPDPSW proceedings.
  
Submission implies the willingness of at least one of the authors to register and present the paper. The authors may use PDF eXpress, the IEEE online file converter and validation tool, to complete the final paper submission process. More details about camera-ready will also be announced when notification of the paper.

# Program Committee
  
PC Chair: Kazuhiko Komatsu, Tohoku University, Japan
PC Vice-Chair: Che-Rung Lee, National Tsing Hua University, Taiwan

# Organizing Committee
  
* General Chair: Osni Marques, LBNL, USA
* General Vice-Chair: Reiji Suda, The University of Tokyo, Japan
* PC Chair: Kazuhiko Komatsu, Tohoku University, Japan
* Finance Chair: Yusaku Yamamoto, The University of Electro-Communications, Japan
* SC liaison: Hiroyuki Takizawa, Tohoku University, Japan
* Web Chair: Hisayasu Kuroda, Ehime University, Japan
* Publicity Chair: Satoshi Ohshima, Nagoya University, Japan

# Contact
  
iwapt2021 at iwapt.org
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-- 
Satoshi OHSHIMA
e-mail: ohshima at cc.nagoya-u.ac.jp
Associate Professor
High Performance Computing Division
Information Technology Center
Nagoya University