1 code implementation • 17 Jan 2024 • Lei Xun, Jonathon Hare, Geoff V. Merrett
In this thesis, we proposed a combined method, a system was developed for DNN performance trade-off management, combining the runtime trade-off opportunities in both algorithms and hardware to meet dynamically changing application performance targets and hardware constraints in real time.
no code implementations • 17 Jan 2024 • Lei Xun, Mingyu Hu, Hengrui Zhao, Amit Kumar Singh, Jonathon Hare, Geoff V. Merrett
Distributed inference is a popular approach for efficient DNN inference at the edge.
no code implementations • 17 Jul 2021 • Hishan Parry, Lei Xun, Amin Sabet, Jia Bi, Jonathon Hare, Geoff V. Merrett
The new reduced design space results in a BLEU score increase of approximately 1% for sub-optimal models from the original design space, with a wide range for performance scaling between 0. 356s - 1. 526s for the GPU and 2. 9s - 7. 31s for the CPU.
1 code implementation • 8 May 2021 • Lei Xun, Long Tran-Thanh, Bashir M Al-Hashimi, Geoff V. Merrett
Machine learning inference is increasingly being executed locally on mobile and embedded platforms, due to the clear advantages in latency, privacy and connectivity.
no code implementations • 8 May 2021 • Lei Xun, Long Tran-Thanh, Bashir M Al-Hashimi, Geoff V. Merrett
Compared to the existing works, our approach can provide up to 2. 36x (energy) and 2. 73x (time) wider dynamic range with a 2. 4x smaller memory footprint at the same compression rate.
1 code implementation • 8 May 2021 • Wei Lou, Lei Xun, Amin Sabet, Jia Bi, Jonathon Hare, Geoff V. Merrett
However, the training process of such dynamic DNNs can be costly, since platform-aware models of different deployment scenarios must be retrained to become dynamic.