From the 1 of 3 linked papers with an AI index.
3 papers
Optimizing Binary and Ternary Neural Network Inference on RRAM Crossbars using CIM-Explorer
Rebecca Pelke, José Cubero-Cascante, Nils Bosbach +5
The paper presents CIM-Explorer, a modular toolkit that compiles, maps, and simulates binary and ternary neural network inference on RRAM crossbars, enabling design‑space explorati…
Mixed-Precision Training and Compilation for RRAM-based Computing-in-Memory Accelerators
Rebecca Pelke, Joel Klein, Jose Cubero-Cascante +3
Computing-in-Memory (CIM) accelerators are a promising solution for accelerating Machine Learning (ML) workloads, as they perform Matrix-Vector Multiplications (MVMs) on crossbar a…
Evaluating the Scalability of Binary and Ternary CNN Workloads on RRAM-based Compute-in-Memory Accelerators
José Cubero-Cascante, Rebecca Pelke, Noah Flohr +3
The increasing computational demand of Convolutional Neural Networks (CNNs) necessitates energy-efficient acceleration strategies. Compute-in-Memory (CIM) architectures based on Re…