In recent years, there has been an expedited trend in embracing bold and radical innovation of computer architectures, aiming at the continuation of computing performance improvement despite the slowed-down physical device scaling. One new frontier in the field of computing architecture is about AI (Artificial Intelligence) hardware, including AI hardware accelerators and neuromorphic computing processors. AI hardware has undergone a transformation from general-purpose computing to domain-specific computing (especially for deep learning applications), from Von Neumann architecture to non-Von Neumann architecture, etc. While the main focus nowadays is still functional implementation, the testability and dependability of these new architectures need to be addressed before the mainstream adoption of any emerging technology.
This special issue seeks original manuscripts that will cover innovative research proposing solutions for the testability and dependability challenges in the following fields: AI hardware accelerators and Neuromorphic computing.
This special issue is organized by Fei Su, Intel Corporation, USA; Chunsheng Liu, Alibaba Inc., USA; and Haralampos-G. Stratigopoulos, Sorbonne Université, CNRS, LIP6, France.
More information about the issue and related submission guidelines can be found here. The article submission deadline is on April 15, 2021. |
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