Highlights of Parallel Computing
Orlando, Florida. June 16-19, 2023
to be held in conjunction with ACM Symposium on Parallelism in Algorithms and Architectures (SPAA’23)
also part of ACM FCRC
With recent advances in hardware, parallelism is becoming increasingly ubiquitous, and work on parallelism now regularly appears at dozens of conferences and communities. Motivated by the now ubiquitous nature of parallelism, we believe it is an opportune time to host a workshop focused on the Highlights of Parallel Computing (HOPC) at SPAA.
In this workshop which will be co-located with SPAA, participants will present talks on recent papers on parallel computing (both theory and practice) that did not appear at SPAA to the SPAA community. This will be an opportunity for the SPAA community to interact with researchers who (perhaps) do not usually submit their work to SPAA, and vice versa.
Although SPAA is conference focusing on theory, historically it has also been placing a strong emphasis on research which combines theory and practice. This workshop aims to proivde a unique platform for both theoretians and practitioners to discuss how to implement practically efficient parallel algorithms based on theoretical results, as well as to understand what theory is needed in practical large-scale applications.
The scope of HOPC consists of any interesting work on parallel computing that was accepted to a publication venue up to 3 years before the date of this conference (i.e., June 2020 onward). We especially welcome papers published during the pandemic years. For more information, please see the Call For Papers page.
|Poster Presentation||June 16 (SPAA Reception)|
|Oral Presentation||June 16|
If an author has any questions, please contact Laxman Dhulipala (laxman AT umd DOT edu) or Yihan Sun (yihans AT cs DOT ucr DOT edu).
Laxman Dhulipala, University of Maryland, College Park
Yihan Sun, University of California, Riverside
- Michael Bender, Stony Brook University
- Laxman Dhulipala, University of Maryland, College Park
- Phil Gibbons, Carnegie Mellon University
- Yan Gu, UC Riverside
- Quanquan Liu, Northwestern University
- Prashant Pandey, University of Utah
- Yihan Sun, UC Riverside
- Helen Xu, Lawrence Berkeley National Laboratory