no code implementations • 2 Apr 2024 • Shanmuga Venkatachalam, Harideep Nair, Prabhu Vellaisamy, Yongqi Zhou, Ziad Youssfi, John Paul Shen
In this paper, we propose a small CNN model with 4 layers that is very amenable for edge AI deployment and realtime gait recognition.
1 code implementation • 16 May 2022 • Harideep Nair, Prabhu Vellaisamy, Santha Bhasuthkar, John Paul Shen
Recent works have proposed a microarchitecture framework for implementing TNNs and demonstrated competitive performance on vision and time-series applications.
no code implementations • 27 May 2021 • Harideep Nair, John Paul Shen, James E. Smith
Temporal Neural Networks (TNNs) are spiking neural networks that use time as a resource to represent and process information, similar to the mammalian neocortex.
no code implementations • 18 Feb 2021 • Shreyas Chaudhari, Harideep Nair, José M. F. Moura, John Paul Shen
Unsupervised time series clustering is a challenging problem with diverse industrial applications such as anomaly detection, bio-wearables, etc.
no code implementations • 10 Dec 2020 • Harideep Nair, Prabhu Vellaisamy, Santha Bhasuthkar, John Paul Shen
A set of highly-optimized custom macro extensions is developed for a 7nm CMOS cell library for implementing Temporal Neural Networks (TNNs) that can mimic brain-like sensory processing with extreme energy efficiency.
no code implementations • 27 Aug 2020 • Harideep Nair, John Paul Shen, James E. Smith
The TNN microarchitecture framework is embodied in a set of characteristic equations for assessing the total gate count, die area, compute time, and power consumption for any TNN design.
1 code implementation • 17 Jun 2019 • Sai Vineeth Kalluru Srinivas, Harideep Nair, Vinay Vidyasagar
This will potentially enhance the ``hardware awareness" and help us find a neural network architecture that is optimal in terms of accuracy, latency and energy consumption, given a target device (Raspberry Pi in our case).