[hpc-announce] CALL FOR PAPERS IEEE Micro (Magazine) -- Special Issue on Artificial Intelligence at the Edge

Joseph Cavallaro cavallar at rice.edu
Tue Dec 28 23:17:35 CST 2021

IEEE Micro (Magazine)
 Special Issue on

Artificial Intelligence at the Edge


Artificial intelligence (AI) algorithms require powerful and efficient
computer architectures for two distinct tasks: training and inference. The
first is extremely compute- and memory-intensive, and in some cases can take
days or weeks to complete. The latter usually implies real-time performance.
As an increasing number of smart devices come online, performing more AI
inference at the edge (far away from the cloud), they have the power to
enable lower latency, greater privacy, better data governance, and higher
availability when compared to cloud/datacenter-based inference. Also,
training can be favored by adopting new federated learning computational
models that perform part of the training concurrently on each edge node and
merge parameters on the cloud/server later. The thorough understanding of
the interaction of hardware and software in edge architectures creates a
unique opportunity to innovate the ever-increasing energy efficiency,
performance, and usability of AI systems at the edge.


This special issue of IEEE Micro will explore academic and industrial
research on topics that combine AI and edge computing. Contributions should
relate to the design, performance, or application of microprocessors and


Topics of interest include (but are not limited to):

*	Digital or analog AI systems at the edge
*	Low-power neural processing engines
*	Energy efficiency of AI systems at the edge
*	DSL and parallel programming models for AI systems at the edge
*	FPGAs and low-power GPUs for AI at the edge
*	Customized accelerator architectures and functional unit design
*	Methods for efficient reconfigurability and adaptability at the edge
*	High-level synthesis design of customized AI engines at the edge
*	Emerging memory technologies for edge AI, such as
processing-in-memory systems
*	Computer systems abstractions to federated learning models
*	Computation and communication tradeoffs in federated learning models
*	Tools and libraries to support AI systems at the edge, such as IoT,
virtual reality/augmented reality (VR/AR) systems, and wearables
*	AI systems for big-data processing at the edge, such as
bioinformatics, genomics, digital agriculture, and weather prediction
*	Formal methods and techniques for data privacy in medical data,
finance data, etc.
*	Security implications of AI computing at the edge
*	Sensor preprocessing and platform integration
*	Techniques and analysis of quantization and network pruning
*	Real-time performance, accuracy, and system complexity constraint

Important Dates:
Submission deadline: February 15, 2022
Initial notifications: May 17, 2022
Revised papers due: June 7, 2022
Final notifications: July 12, 2022
Final versions due: July 26, 2022
Publication: September/October 2022.

Submission Guidelines:

Manuscripts should not exceed 5,000 words including references, with each
average-size figure counting as 250 words toward this limit. Please include
all figures and tables, as well as a cover page with author contact
information (name, postal address, phone, fax, and email address) and a
200-word abstract. Submitted manuscripts must not have been previously
published or be currently submitted for publication elsewhere, and all
manuscripts must be cleared for publication. All previously published papers
must have at least 30% new content compared to any conference (or other)
publication. Acceptable file formats include Microsoft Word and PDF. Please
read the Author Information page before submitting. When you are ready to
submit, go to ScholarOne Manuscripts at
https://mc.manuscriptcentral.com/micro-cs .



Contact the guest editors Gabriel Falcao and Joseph R. Cavallaro concerning
the scope of this special issue at  <mailto:micro5-22 at computer.org>
micro5-22 at computer.org, or for general questions about IEEE Micro the
Editor-in-Chief Lizy John at  <mailto:ljohn at ece.utexas.edu>
ljohn at ece.utexas.edu. For questions about the ScholarOne submission system,
contact the IEEE Micro magazine assistant at  <mailto:micro-ma at computer.org>
micro-ma at computer.org.



Joseph Cavallaro

Rice University



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