Hi Everyone,
In conjunction with MLCommons, we're going to be hosting a
workshop focused on performance analysis of ML workloads on
emerging hardware, which will be co-located with MLSys this
year.
For those who may be interested in submitting to the
workshop, please review the call for papers below.
Tom St. John
===================================================================
[MLBench'23] Fourth Workshop on Benchmarking Machine Learning
Workloads on Emerging Hardware
To be held with the Sixth Conference on Machine Learning and
Systems
(MLSys) on June 8, 2023
Miami,
FL, USA
==================================================================
--------
About
--------
With evolving system architectures, hardware and software
stacks,
diverse machine learning (ML) workloads, and data, it is
important to
understand how these components interact with each other.
Well-defined
benchmarking procedures help evaluate and reason the performance
gains
with ML workload-to-system mappings. We welcome all novel
submissions
in benchmarking machine learning workloads from all disciplines,
such
as image and speech recognition, language processing, drug
discovery,
simulations, and scientific applications.
Key problems that we seek to address are:
(i) which representative ML benchmarks cater to workloads seen
in
industry, national labs, and interdisciplinary sciences;
(ii) how to characterize the ML workloads based on their
interaction
with hardware;
(iii) which novel aspects of hardware, such as heterogeneity in
compute, memory, and networking, will drive their adoption;
(iv) performance modeling and projections to next-generation
hardware.
Along with selected publications, the workshop program will also
have
experts in these research areas presenting their recent work and
potential directions to pursue.
-------------------
Call for Papers
-------------------
We solicit both full papers (8-10 pages) and short/position
papers
(4-6 pages). Submissions are not double-blind (author names must
be
included). The page limit includes figures, tables, and
appendices,
but excludes references. Please use standard LaTeX or Word ACM
templates. All submissions will need to be made via EasyChair
(submission website:
https://easychair.org/conferences/?conf=mlbench23).
Each submission
will be reviewed by at least three reviewers from the program
committee. Papers will be reviewed for novelty, quality,
technical
strength, and relevance to the workshop.
-------------------
Important dates
-------------------
Submission Deadline: April 3, 2023
Acceptance Notification: April 14, 2023
Workshop date: June 8, 2023
All deadlines are at midnight anywhere on earth (AoE), and are
firm.
-----------------
Organization
-----------------
Organizing Committee
Tom St. John, OctoML (
tomstj...@gmail.com)
Murali Emani, Argonne National Laboratory (
mem...@anl.gov)
Wenqian Dong, Florida International University (
wo...@fiu.edu)
---------------------------
Program Committee
--------------------------
Oana Balmau (McGill University)
Steven Farrell (Lawrence Berkeley National Laboratory)
Srivatsan Krishnan (Harvard)
Jae W. Lee (Seoul National University)
Dong Li (UC Merced)
Qian Li (Stanford)
Sid Raskar (Argonne National Laboratory)
Karthik Swaminathan (IBM)
Dingwen Tao (Indiana University)
Yu "Emma" Wang (Google)
Bo Yuan (Rutgers)
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