[hpc-announce] CFP: CogArch 2022: 6th Workshop on Cognitive Architectures (Co-located with HPCA)

David Trilla Rodriguez1 david.trilla at ibm.com
Fri Nov 26 18:30:05 CST 2021

CogArch 2022: 6th Workshop on Cognitive Architectures (Co-located with 

Website: www.cogarchworkshop.org


Artificial Intelligence (AI) and Machine Learning (ML) techniques have 
become the de facto solution to drive human progress and more 
specifically, automation. In the last years, the world’s economy has been 
gravitating towards the AI/ML domain (from industrial and scientific 
perspectives) and the expectation of growth is not withering away. 
Additionally, these trends have been further exacerbated by the ongoing 
global COVID-19 pandemic, which paralyzed the world’s economy and made 
evident the need for even more automation to provide safer and more 
reliable services and also to aid in the agile discovery of life-saving 
drugs and vaccines — all this with appropriate security and data privacy 
elements in place. To support those kinds of applications, "cognitive" 
(AI/ML) architectures are designed and deployed to materialize advances in 
the aforementioned fields. However, although the newest cognitive designs 
are improving by the day, the number of challenges ahead for these systems 
is still overwhelming. With existing solutions reaching functional 
maturity, design considerations are now pivoting to new aspects like 
energy scaling, reliable operation, safe guarantees or even security and 
data-privacy properties. Specifically, when it comes to security and data 
privacy in the AI/ML context, Homomorphic Encryption (HE) has emerged as a 
highly promising approach. HE is arguably the holy grail of data-secure 
computing as it provides security and privacy guarantees by allowing 
computation on encrypted private data without the need for decryption. 
This is particularly enticing for applications in the medical sciences, 
natural language processing, autonomous and connected vehicles, as well as 
traditional domains such as banking systems, where HE could drastically 
reduce the frequency of data breaches, thus guaranteeing privacy of highly 
sensitive user data.

In this context, this edition of the CogArch workshop aims at bringing 
together the necessary know-how to design cognitive architectures from a 
holistic point of view, tackling all their design considerations from the 
algorithms to platforms in all the different fields that cognitive 
architectures will soon occupy, from autonomous cars to critical tasks in 
avionics, finance, space travel or even personalized medicine. This year's 
edition, in addition, solicits contributions on the security and 
data-privacy preserving aspects of AI/ML and related application domains.

The CogArch workshop already had five successful editions, bringing 
together experts and knowledge on the most novel design ideas for 
cognitive systems. This workshop capitalizes on the synergy between 
industrial and academic efforts in order to provide a better understanding 
of cognitive systems and key concepts of their design.


Hardware and software design considerations are gravitating towards AI 
applications, as those have been proven extremely useful in a wide variety 
of fields, from edge computing in autonomous cars, to cloud-based 
computing for personalized medicine. The recent years have brought about a 
boom in start-ups and novel platforms that constantly offer improvements 
in performance and accuracy for the aforementioned applications. As this 
kind of cognitive architectures evolve, system designers must incorporate 
many different considerations, with security and data privacy being the 
key ones today. The emergence of different security and data privacy 
approaches for AI/ML applications, including but not limited to the use of 
Homomorphic Encryption (HE) techniques, is also leading to a very diverse 
set of (hardware and software) design decisions and solutions.

The CogArch workshop solicits formative ideas and new product offerings in 
this general space that covers all the design aspects of cognitive 
systems, with particular focus this year on the security and data privacy 
considerations of AI/ML.

Topics of interest include (but are not limited to):
- Hardware support for state-of-the-art (post-quantum) encryption 
- Hardware-software co-design and acceleration of homomorphic encryption 
- Demonstration of side-channel or adversarial attacks on AI systems 
and/or potential solutions, including hardware support for mitigation of 
these attacks
- Prototype demonstrations of state-of-the-art secure AI systems
- System-level techniques to accelerate end-to-end execution (inference 
and/or training) of secure AI computation
- Secure algorithms in support of cognitive reasoning: recognition, 
intelligent search, diagnosis, inference and informed decision-making.
- Swarm intelligence and distributed architectural support; brain-inspired 
and neural computing architectures.
- Prototype demonstrations of state-of-the-art cognitive computing 
- Accelerators and micro-architectural support for artificial 
- Cloud-backed autonomics and mobile cognition: architectural and OS 
support thereof.
- Resilient design of distributed (swarm) mobile AI architectures.
- Reliability and safety considerations, and security against adversarial 
attacks in mobile AI architectures.
- Techniques for improving energy efficiency, battery life extension and 
endurance in mobile AI architectures.
- Case studies and real-life demonstrations/prototypes in specific 
application domains: e.g. smart homes, connected cars and UAV-driven 
commercial services, architectures in support of AI for healthcare 
applications, such as medical imaging, drug discovery and smart 
diagnostics, as well as applications of interest to defense and homeland 

The workshop shall consist of regular presentations and/or prototype 
demonstrations by authors of selected submissions. In addition, it will 
include invited keynotes by eminent researchers from industry and academia 
as well as interactive panel discussions to kindle further interest in 
these research topics. Submissions will be reviewed by a workshop Program 
Committee, in addition to the organizers.

Submitted manuscripts must be in English of up to 2 pages (with same 
formatting guidelines as the main conference) indicating the type of 
submission: regular presentation or prototype demonstration. Submissions 
should be submitted to the following link by December 24th, 2021 (
https://easychair.org/my/conference?conf=cogarch22). If you have questions 
regarding submission, please contact us: info at cogarchworkshop.org


CogArch will feature a session where researchers can showcase innovative 
prototype demonstrations or proof-of-concept designs in the cognitive 
architecture space. Examples of such demonstrations may include (but are 
not limited to):

- Custom ASIC or FPGA-based demonstrations of machine learning, cognitive 
or neuromorphic architectures.
- Innovative implementations of state-of-the-art cognitive 
algorithms/applications, and the underlying software-hardware co-design 
- Demonstration of end-to-end cognitive systems comprising of edge devices 
backed by a cloud computing infrastructure.
- Novel designs showcasing the adoption of emerging technologies for the 
design of cognitive systems.
- Tools or frameworks to aid analysis, simulation and design of cognitive 

Submissions for the demonstration session may be made in the form of a 
2-page manuscript highlighting key features and innovations of the 
prototype demonstration. Proposals accepted for demonstration during the 
workshop can be accompanied by a poster/short presentation. Authors should 
explicitly indicate that the submission is for prototype demonstration at 
submission time.


Paper submission deadline: December 24th, 2021
Notification of acceptance: January 21st, 2022
Workshop date: February 12th or 13th, 2022 (TBD)


Roberto Gioiosa, Pacific Northwest National Laboratory
David Trilla, IBM Research
Subhankar Pal, IBM Research
Saransh Gupta, IBM Research
Augusto Vega, IBM Research
Karthik Swaminathan, IBM Research
Alper Buyuktosunoglu, IBM Research
Pradip Bose, IBM Research
Nir Drucker, IBM Research


info at cogarchworkshop.org

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