25 citations · 26 across the 2 of their papers we have counts for
4 papers
Tree-based machine learning performed in-memory with memristive analog CAM
Giacomo Pedretti, Catherine E. Graves, Can Li +5
Tree-based machine learning techniques, such as Decision Trees and Random Forests, are top performers in several domains as they do well with limited training datasets and offer im…
PANTHER: A Programmable Architecture for Neural Network Training Harnessing Energy-efficient ReRAM
Aayush Ankit, Izzat El Hajj, Sai Rahul Chalamalasetti +7
The wide adoption of deep neural networks has been accompanied by ever-increasing energy and performance demands due to the expensive nature of training them. Numerous special-purp…
Analog content addressable memories with memristors
Can Li, Catherine E. Graves, Xia Sheng +4
A content-addressable-memory compares an input search word against all rows of stored words in an array in a highly parallel manner. While supplying a very powerful functionality f…
PUMA: A Programmable Ultra-efficient Memristor-based Accelerator for Machine Learning Inference
Aayush Ankit, Izzat El Hajj, Sai Rahul Chalamalasetti +8
Memristor crossbars are circuits capable of performing analog matrix-vector multiplications, overcoming the fundamental energy efficiency limitations of digital logic. They have be…