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: This email address is being protected from spambots. You need JavaScript enabled to view it.)

Tom St. John, Tesla Inc. (Email:  This email address is being protected from spambots. You need JavaScript enabled to view it.)

Murali Emani, Argonne National Laboratory/ALCF (Email: This email address is being protected from spambots. You need JavaScript enabled to view it.)

 

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Program Committee:

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TBA