Call for Abstracts
ModSim 2020
Workshop on Modeling & Simulation of Systems
and Applications
August 12-14, 2020, University of Washington
Botanic Gardens
Center for Urban Horticulture, Seattle
Workshop URL: https://www.bnl.gov/modsim2020/
Submission URL: https://easychair.org/conferences/?conf=modsim20200
EasyChair Submission
Deadline: Friday, May 10, 2020 (11:59
PM, Anywhere on Earth [AOE])
Notification of
Acceptance: Friday, May 29, 2020
To promote advancements
in modeling and simulation (ModSim) research, we are soliciting community input
in the form of abstracts. If accepted, author(s) will be invited to offer a poster and short
presentation at the annual gathering
of our community, the ModSim 2020 Workshop.
The
overarching theme for this year’s workshop is Modeling and Simulation in
the Artificial Intelligence Era. The emphasis will be on AI-driven
methodologies, tools, best practices, projects, and initiatives that aim to
address the challenges and achieve the goal of modeling performance, power, and
reliability of high-performance systems under a realistic application workload.
Abstract Submission Guidelines
There is no set word
limit for abstract submissions. However, please limit your submission to one
page. The abstract should provide an overview that adequately summarizes the
topic(s) presented and any proposed impact on ModSim research or techniques,
especially related to modeling and simulation in the era of artificial
intelligence. The following details a proposed abstract layout and points to
consider:
Abstract Title
Primary research area:
§ Artificial Intelligence
and Machine Learning Workloads and Systems
§ Modeling and
Simulation of Subsystems via Artificial Intelligence and Machine Learning
§ Advances in ModSim
Implementation
What is being modeled? (e.g., performance,
reliability, power, other)
What is the target application?
What modeling techniques are being used?
What is novel about the approach versus current
state of the art?
Are preliminary results available?
All abstracts must be
submitted through EasyChair no later than Friday May 10,
2020 (11:59 PM, AOE). Those with accepted abstracts will be notified via
e-mail on Friday, May 29, 2020.
Dr. Sudhakar Yalamanchili Award
This year, submissions
may be eligible for the inaugural Dr. Sudhakar Yalamanchili Award, which
is intended to recognize researchers for their outstanding contribution to the
field of computer modeling and simulation. Presenters will be evaluated during the
Contributed Presentation/Poster Session at the ModSim 2020 Workshop.
Learn more at the Sudha Award link.
Topic
Areas
Abstract
contributions should focus on the following topical areas of interest:
Artificial
Intelligence and Machine Learning Workloads and Systems. AI, in general,
and Machine Learning (ML), in particular, are important drivers to all forms of
computing, including large-scale data- and numerically-intensive
high-performance computing (HPC). Consequently, systems designed for AI/ML
workloads are critically important. Abstracts in this category should offer
novel approaches for AI and ML workloads, ModSim for AI/ML architectures, and
other approaches (e.g., intelligent computational steering driven by dynamic
and offline learning).
Methodologies
and Tools.
AI and ML are not only revolutionizing applications, but these techniques also
have the potential to revolutionize the way that HPC systems are designed. This
abstract category solicits submissions that adopt AI/ML techniques in system
design, such as predictive models of performance, power, or cost; approaches
that intelligently explore and recommend designs; and techniques that optimize
individual subsystems, across system layers, or the whole system with AI/ML.
Abstracts should highlight how to advance the state of the art, as well as expectations
for impacting future directions in this area.
Recent
Advances in ModSim Implementation. The rapidly increasing complexity of
systems and application workloads—along with the blending of compute, memory
devices, storage, and interconnect then further combined with application
software—translates into unprecedented challenges within the ModSim field. Submissions
in this category, not necessarily related to AI/ML, are expected to highlight
recent developments that can help overcome these significant challenges.
Possible topics include, but are not limited to, novel ModSim methodologies, emerging
areas of R&D, new projects or advances in existing projects, and new
applications of ModSim tools to real-life problems.