8 citations · 30 across the 6 of their papers we have counts for
6 papers
tubGEMM: Energy-Efficient and Sparsity-Effective Temporal-Unary-Binary Based Matrix Multiply Unit
Prabhu Vellaisamy, Harideep Nair, Joseph Finn +7
General Matrix Multiplication (GEMM) is a ubiquitous compute kernel in deep learning (DL). To support energy-efficient edge-native processing, new GEMM hardware units have been pro…
Unsupervised Clustering of Time Series Signals using Neuromorphic Energy-Efficient Temporal Neural Networks
Shreyas Chaudhari, Harideep Nair, José M. F. Moura +1
Unsupervised time series clustering is a challenging problem with diverse industrial applications such as anomaly detection, bio-wearables, etc. These applications typically involv…
A Custom 7nm CMOS Standard Cell Library for Implementing TNN-based Neuromorphic Processors
Harideep Nair, Prabhu Vellaisamy, Santha Bhasuthkar +1
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 proces…
Direct CMOS Implementation of Neuromorphic Temporal Neural Networks for Sensory Processing
Harideep Nair, John Paul Shen, James E. Smith
Temporal Neural Networks (TNNs) use time as a resource to represent and process information, mimicking the behavior of the mammalian neocortex. This work focuses on implementing TN…
On the Real-time Vehicle Placement Problem
Abhinav Jauhri, Carlee Joe-Wong, John Paul Shen
Motivated by ride-sharing platforms' efforts to reduce their riders' wait times for a vehicle, this paper introduces a novel problem of placing vehicles to fulfill real-time pickup…
Space-Time Graph Modeling of Ride Requests Based on Real-World Data
Abhinav Jauhri, Brian Foo, Jerome Berclaz +4
This paper focuses on modeling ride requests and their variations over location and time, based on analyzing extensive real-world data from a ride-sharing service. We introduce a g…