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Chris Kachris
Assistant Professor, Edge AI, Accelerated Computing
Chris Kachris is an Assistant Professor in the Department of Electrical and Electronics Engineering at the University of West Attica. He specializes in various advanced topics within electrical engineering, including:
- Machine Learning on Embedded Systems
- Hardware Accelerators (FPGAs)
- Reconfigurable Computing
- Edge AI & Cloud Computing
- Computer Architecture
Education
Kachris holds a Ph.D. in Electrical and Computer Engineering from Delft University of Technology (2007) and has a Master’s and Diploma in Electronic and Computer Engineering from the Technical University of Crete (2003, 2001).
Research and Projects
His research interests are reflected in several projects he has led or contributed to, including:
- MORPHEMIC: Focused on modeling and orchestrating heterogeneous resources for cloud applications (EU project, 2020-2023).
- VINEYARD: A project aimed at integrated hardware accelerators for data centers (EU project, 2016-2018).
- CloudAccel: Concentrated on hardware acceleration of machine learning applications in the cloud (Greece project, 2017-2019).
- Other notable projects include ASTRON, COCONUT, and CHRON, which explore advanced networking and optical technologies.
Publications
Kachris has also supervised various research works, including studies on accelerated large language models and computer vision applications for parking spot detection.
Contact Information
He is based at the Ancient Olive Grove Campus of the University of West Attica, located in Egaleo, Greece. His contact details include a phone number and email address available through the university's website.
For more professional insights, Kachris maintains a LinkedIn profile under the username "kachris" where he shares updates related to his research and professional activities .12
Highlights
Justin Drake just presented Accseal ZK acceleration ASIC at #zksummit11 with 5x more energy efficient than GPUs.
The question is should zk asic vendors try to sell the asics or should they provide also the front end services as Groq did?
If you are interested on Hardware accelerated LLMs here is the presentation I just gave to Unify paper reading session.
FPGA, GPUs, ASIC and In-memory architectures compared!
Thanks Daniel Lenton, Vaatsalya Shrivastava for the invitation. https://lnkd.in/dFAyhdVD
check the full paper here: https://lnkd.in/dG6d2mej
