8 citations · 11 across the 4 of their papers we have counts for
4 papers
Towards Error Correction for Computing in Racetrack Memory
Preston Brazzle, Benjamin F. Morris, Evan McKinney +4
Computing-in-memory (CIM) promises to alleviate the Von Neumann bottleneck and accelerate data-intensive applications. Depending on the underlying technology and configuration, CIM…
The Landscape of Compute-near-memory and Compute-in-memory: A Research and Commercial Overview
Asif Ali Khan, João Paulo C. De Lima, Hamid Farzaneh +1
In today's data-centric world, where data fuels numerous application domains, with machine learning at the forefront, handling the enormous volume of data efficiently in terms of t…
Full-Stack Optimization for CAM-Only DNN Inference
João Paulo C. de Lima, Asif Ali Khan, Luigi Carro +1
The accuracy of neural networks has greatly improved across various domains over the past years. Their ever-increasing complexity, however, leads to prohibitively high energy deman…
C4CAM: A Compiler for CAM-based In-memory Accelerators
Hamid Farzaneh, João Paulo Cardoso de Lima, Mengyuan Li +3
Machine learning and data analytics applications increasingly suffer from the high latency and energy consumption of conventional von Neumann architectures. Recently, several in-me…