4 citations · 7 across the 8 of their papers we have counts for
11 papers
NullaNet Tiny: Ultra-low-latency DNN Inference Through Fixed-function Combinational Logic
Mahdi Nazemi, Arash Fayyazi, Amirhossein Esmaili +3
While there is a large body of research on efficient processing of deep neural networks (DNNs), ultra-low-latency realization of these models for applications with stringent, sub-m…
A Tunable Robust Pruning Framework Through Dynamic Network Rewiring of DNNs
Souvik Kundu, Mahdi Nazemi, Peter A. Beerel +1
This paper presents a dynamic network rewiring (DNR) method to generate pruned deep neural network (DNN) models that are robust against adversarial attacks yet maintain high accura…
SynergicLearning: Neural Network-Based Feature Extraction for Highly-Accurate Hyperdimensional Learning
Mahdi Nazemi, Amirhossein Esmaili, Arash Fayyazi +1
Machine learning models differ in terms of accuracy, computational/memory complexity, training time, and adaptability among other characteristics. For example, neural networks (NNs…
Pre-defined Sparsity for Low-Complexity Convolutional Neural Networks
Souvik Kundu, Mahdi Nazemi, Massoud Pedram +2
The high energy cost of processing deep convolutional neural networks impedes their ubiquitous deployment in energy-constrained platforms such as embedded systems and IoT devices.…
Energy-Aware Scheduling of Task Graphs with Imprecise Computations and End-to-End Deadlines
Amirhossein Esmaili, Mahdi Nazemi, Massoud Pedram
Imprecise computations provide an avenue for scheduling algorithms developed for energy-constrained computing devices by trading off output quality with the utilization of system r…
Modeling Processor Idle Times in MPSoC Platforms to Enable Integrated DPM, DVFS, and Task Scheduling Subject to a Hard Deadline
Amirhossein Esmaili, Mahdi Nazemi, Massoud Pedram
Energy efficiency is one of the most critical design criteria for modern embedded systems such as multiprocessor system-on-chips (MPSoCs). Dynamic voltage and frequency scaling (DV…