[hpc-announce] [Call for papers] Workshop on Benchmarking Machine Learning Workloads @ ISPASS’20

[Murali Emani]

MLBench: Workshop on Benchmarking Machine Learning Workloads
To be held along with IEEE International Symposium on Performance
Analysis of Systems and Software (ISPASS)
April 5th, 2020

https://sites.google.com/g.harvard.edu/mlbench/home

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About:
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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.

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Submissions:
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We solicit short/position papers (2-4 pages) as well as longer-full
papers (4-6 pages). Submitting a paper to the workshop will not
prevent you from submitting the paper in the future to a conference;
there are no official proceedings. So, the workshop provides an ideal
ground for getting early feedback on your work!

The page limit includes figures, tables, and appendices, but excludes
references. Please use standard IEEE LaTeX or Word templates
(https://www.ieee.org/conferences/publishing/templates.html). All
submissions will need to be made via EasyChair
(https://easychair.org/my/conference?conf=mlbench20).

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. All accepted papers
will be made available online and selected papers will be invited to
submit extended versions to a journal after the workshop.

Submissions are not double blind (author names must be included).

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Deadlines:
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Paper submission deadline: March 1, 2020
Author Notification: March 9, 2020
Camera-ready papers due: March 23, 2020
(All deadlines are at midnight EST, and are firm.)

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Organizing Committee:
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Vijay Janapa Reddi, Harvard University (Email: vj at eecs.harvard.edu)
Tom St. John, Tesla Inc. (Email:  tomstjohn617 at gmail.com)
Murali Emani, Argonne National Laboratory/ALCF (Email: memani at anl.gov)

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Program Committee:
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TBA