7 citations · 12 across the 9 of their papers we have counts for
9 papers
Optimizing Routerless Network-on-Chip Designs: An Innovative Learning-Based Framework
Ting-Ru Lin, Drew Penney, Massoud Pedram +1
Machine learning applied to architecture design presents a promising opportunity with broad applications. Recent deep reinforcement learning (DRL) techniques, in particular, enable…
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…
VeriSFQ - A Semi-formal Verification Framework and Benchmark for Single Flux Quantum Technology
Alvin D. Wong, Kevin Su, Hang Sun +3
In this paper, we propose a semi-formal verification framework for single-flux quantum (SFQ) circuits called VeriSFQ, using the Universal Verification Methodology (UVM) standard. T…
BottleNet: A Deep Learning Architecture for Intelligent Mobile Cloud Computing Services
Amir Erfan Eshratifar, Amirhossein Esmaili, Massoud Pedram
Recent studies have shown the latency and energy consumption of deep neural networks can be significantly improved by splitting the network between the mobile device and cloud. Thi…
Hybrid Cell Assignment and Sizing for Power, Area, Delay Product Optimization of SRAM Arrays
Ghasem Pasandi, Raghav Mehta, Massoud Pedram +1
Memory accounts for a considerable portion of the total power budget and area of digital systems. Furthermore, it is typically the performance bottleneck of the processing units. T…
Approximate Logic Synthesis: A Reinforcement Learning-Based Technology Mapping Approach
Ghasem Pasandi, Shahin Nazarian, Massoud Pedram
Approximate Logic Synthesis (ALS) is the process of synthesizing and mapping a given Boolean network to a library of logic cells so that the magnitude/rate of error between outputs…