57 citations · 83 across the 9 of their papers we have counts for
4 papers · 1 filter
An Experimental Study of Reduced-Voltage Operation in Modern FPGAs for Neural Network Acceleration
Behzad Salami, Erhan Baturay Onural, Ismail Emir Yuksel +6
We empirically evaluate an undervolting technique, i.e., underscaling the circuit supply voltage below the nominal level, to improve the power-efficiency of Convolutional Neural Ne…
On the Resilience of Deep Learning for Reduced-voltage FPGAs
Kamyar Givaki, Behzad Salami, Reza Hojabr +6
Deep Neural Networks (DNNs) are inherently computation-intensive and also power-hungry. Hardware accelerators such as Field Programmable Gate Arrays (FPGAs) are a promising solutio…
TauRieL: Targeting Traveling Salesman Problem with a deep reinforcement learning inspired architecture
Gorker Alp Malazgirt, Osman S. Unsal, Adrian Cristal Kestelman
In this paper, we propose TauRieL and target Traveling Salesman Problem (TSP) since it has broad applicability in theoretical and applied sciences. TauRieL utilizes an actor-critic…
Low-Precision Floating-Point Schemes for Neural Network Training
Marc Ortiz, Adrián Cristal, Eduard Ayguadé +1
The use of low-precision fixed-point arithmetic along with stochastic rounding has been proposed as a promising alternative to the commonly used 32-bit floating point arithmetic to…