Website: www.cogarchworkshop.org
===== ABOUT =====
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. In more recent years, a new trend towards very large AI models has been gaining traction: Foundation Models. Large Foundation Models with billions or trillions of parameters exhibit astonishing emergent skills, especially in fields like natural language processing, vision, and human-machine interaction. Examples like BERT (110M parameters), GPT-2 (1.5B parameters), GPT-3 (175B parameters), BLOOM (176B parameters), and Wu Dao (1.75T parameters!) indicate that the size of these models will keep growing rapidly and substantially in the foreseeable future. This results in all sorts of challenges, especially with respect to provisioning the computing resources needed for training and inferencing, and calls for thorough co-design across algorithms, models, software, and hardware systems.
In this context, this edition of the CogArch workshop aims at bringing together the necessary know-how to address co-designed hardware-software architectures from a holistic point of view, tackling all their design considerations from the algorithms to platforms in all the different fields that large-scale cognitive systems will soon occupy, from natural language processing and speech to other applications like protein folding, drug discovery, computer vision or even music generation.
The CogArch workshop already had six 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.
===== CALL FOR PAPERS =====
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. Recent years have witnessed the emergence of AI at a very large scale: Foundation Models. Large Foundation Models with billions or trillions of parameters exhibit astonishing emergent skills, especially in fields like natural language processing, vision, content creation, and human-machine interaction. The unprecedented number of parameters in these models, though, generates all sorts of new challenges, especially with respect to provisioning the computing resources needed for training and inferencing, and calls for thorough co-design across algorithms, models, software, and hardware systems.
The CogArch workshop solicits formative ideas and new product offerings in the general space of AI systems that covers all the design aspects of cognitive systems, with particular focus this year on large-scale Foundation Models.
Topics of interest include (but are not limited to):
– Hardware support for state-of-the-art AI models
– Hardware-software co-design and acceleration of AI models
– Parallelization strategies for AI models (e.g. transformers)
– Accelerators and micro-architectural support for AI
– Reliability and safety considerations, and security against adversarial attacks in cognitive architectures
– Techniques for improving energy efficiency of AI applications, and battery life extension and endurance in mobile AI architectures
– AI/ML for fast system modeling and AI/ML as design methodology
– Leveraging 2.5D/3D chiplet designs, wafer scaling and other heterogeneous integration techniques for designing scalable architectures for Foundation Models
– Privacy-preserving inference on AI models
– Prototype demonstrations in specific application domains: e.g., natural language processing and speech, protein folding, drug discovery, computer vision,
code generation, music making, as well as applications of interest to defense and homeland security
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 main conference) indicating the type of submission: regular presentation or prototype demonstration. Submissions should be submitted to the following link by April 7th, 2023.
If you have questions regarding submission, please contact us: info@cogarchworkshop.org
===== CALL FOR PROTOTYPE DEMONSTRATIONS =====
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 techniques.
– 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 systems.
– 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.
===== IMPORTANT DATES =====
– Paper submission deadline: April 7th, 2023
– Notification of acceptance: May 1st, 2023
– Workshop date: June 18th, 2023