[hpc-announce] [Call for Paper] MTSA'23: Workshop on Memory Technologies, Systems, and Applications (DEADLINE EXTENDED)

Ivy Peng ivybopeng at gmail.com
Sun Jul 30 04:12:23 CDT 2023

Call for Paper - - DEADLINE EXTENDED
MTSA'23: Workshop on Memory Technologies, Systems, and Applications
(Previously MCHPC: Workshop on Memory Centric High-Performance Computing)
Co-located at SC23 - Denver, Colorado, USA - November 13th
Website:  https://passlab.github.io/mtsa/mtsa2023/
The growing disparity between compute and memory speed, known as the memory
wall problem, has been one of the most critical and long-standing
challenges in the computing industry. The prevalence of heterogeneous
computing, the ongoing expansion of the memory hierarchy, and the advent of
disaggregated architectures have considerably expanded the scope of this
problem. Computer architecture, operating systems, storage systems,
performance models, tools, and applications themselves are being enhanced
or even redesigned to address the performance, programmability, and energy
efficiency challenges of the increasingly complex and heterogeneous memory
systems. Exploring the intersection of these research areas will enable
cohesive and synergistic development and collaboration on the future of
memory technologies, systems, and applications. MTSA’23: Workshop on Memory
Technologies, Systems, and Applications aims to bring together researchers
from industry, government labs, and academia concerned with the challenges
of efficiently using existing and emerging memory systems.
Topics of Interests include:
 + Software, hardware, and co-design approaches for processing-in-memory
and near-memory computing technologies.
 + All aspects of emerging memory technologies, including disaggregated
memory, cache-coherent interconnects e.g., CXL, heterogeneous memory, etc.
 + Programming interfaces or language extensions for emerging memory
technologies and systems
 + Compiler, runtime, and system techniques for efficient memory-centric
 + OS, storage and file systems, and I/O systems support for existing and
emerging memory technologies, especially supporting the blurred boundary
between memory and storage.
 + Tools, modeling, evaluation, and case study of memory system behavior
and its impact on application performance
 + Application development and optimization for new memory architecture and
 + Energy and power efficiency in memory technologies.
Important Dates

Submission Deadline -- August 16, 2023
Notifications -- September 06, 2023
Camera Ready Papers -- September 29, 2023, including Copyright Form
Workshop -- November 13, 2023

Authors are invited to submit manuscripts in English structured as 8
2-column pages (U.S. letter – 8.5”x11”), excluding the bibliography, using
the ACM Proceedings Template (
https://www.acm.org/publications/proceedings-template). Latex users, please
use the “sigconf” option (use of the “review” option is recommended but not
required). Word authors can use the “Interim Layout”. The workshop
encourages submitters to include reproducibility information, using
Reproducibility Initiative for SC'23 Technical Papers as guideline. All
manuscripts will be peer-reviewed and judged on correctness, originality,
technical strength, and significance, quality of presentation, and interest
and relevance to the workshop attendees. There will be one round of
single-blind reviews with potential for acceptance with minor revisions
before the camera ready submission. Papers should be submitted
electronically at this direct link or at
https://submissions.supercomputing.org, choose "submit" and then "SC23
Workshop: MTSA'23: Workshop on Memory Technologies, Systems, and
Applications". The final papers will be published in the SC Workshops
Proceedings volume. Copyright procedures will follow those of the SC
Workshops Proceedings.

Program Committee

Tyler Allen, University of North Carolina at Charlotte
Ron Brightwell, Sandia National Laboratories
Ivy Peng, KTH Royal Institute of Technology
Tom Deakin, University of Bristol
Maya Gokhale, Lawrence Livermore National Laboratory
Kyle Hale, Illinois Institute of Technology
Alice Koniges, University of Hawai'i, Maui High Performance Computing Center
Seyong Lee, Oak Ridge National Laboratory
Dong Li, University of California, Merced
Chunhua Liao, Lawrence Livermore National Laboratory
Stephen L. Olivier, Sandia National Laboratories
Jie Ren, College of William and Mary
Yonghong Yan, University of North Carolina at Charlotte
Onkar Patil, IBM Corporation

Tyler Allen (University of North Carolina at Charlotte, USA)
Ivy Peng (KTH Royal Institute of Technology, Sweden)
Ron Brightwell (Sandia National Laboratory, USA)
Maya Gokhale (Lawrence Livermore National Laboratory, USA)

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