168 citations · 477 across the 22 of their papers we have counts for
4 papers · 1 filter
EH-DNAS: End-to-End Hardware-aware Differentiable Neural Architecture Search
Qian Jiang, Xiaofan Zhang, Deming Chen +2
In hardware-aware Differentiable Neural Architecture Search (DNAS), it is challenging to compute gradients of hardware metrics to perform architecture search. Existing works rely o…
Scaling Up Hardware Accelerator Verification using A-QED with Functional Decomposition
Saranyu Chattopadhyay, Florian Lonsing, Luca Piccolboni +12
Hardware accelerators (HAs) are essential building blocks for fast and energy-efficient computing systems. Accelerator Quick Error Detection (A-QED) is a recent formal technique wh…
Being-ahead: Benchmarking and Exploring Accelerators for Hardware-Efficient AI Deployment
Xiaofan Zhang, Hanchen Ye, Deming Chen
Customized hardware accelerators have been developed to provide improved performance and efficiency for DNN inference and training. However, the existing hardware accelerators may…
F-CAD: A Framework to Explore Hardware Accelerators for Codec Avatar Decoding
Xiaofan Zhang, Dawei Wang, Pierce Chuang +3
Creating virtual avatars with realistic rendering is one of the most essential and challenging tasks to provide highly immersive virtual reality (VR) experiences. It requires not o…