353 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Hewlett Packard Enterprise (Ireland)IE11 papers
- Hewlett-Packard (United States)US10 papers
- Nanyang Technological UniversitySG6 papers
- Forschungszentrum JülichDE5 papers
- Stanford UniversityUS5 papers
- Georgia Institute of TechnologyUS4 papers
- RWTH Aachen UniversityDE4 papers
- The University of Texas at AustinUS4 papers
- University of California, BerkeleyUS4 papers
- Aalto UniversityFI3 papers
- Carnegie Mellon UniversityUS3 papers
- Centre National de la Recherche ScientifiqueFR3 papers
5 papers · 1 filter
Accelerating Hybrid XORCNF Boolean Satisfiability Problems Natively with In-Memory Computing
Haesol Im, Fabian Böhm, Giacomo Pedretti +14
The Boolean satisfiability (SAT) problem is a computationally challenging decision problem central to many industrial applications. For SAT problems in cryptanalysis, circuit desig…
Parallel Tempering-Inspired Distributed Binary Optimization with In-Memory Computing
Xiangyi Zhang, Fabian Böhm, Elisabetta Valiante +7
In-memory computing (IMC) has been shown to be a promising approach for solving binary optimization problems while significantly reducing energy and latency. Building on the advant…
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…
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…