A flexible and fast PyTorch toolkit for simulating training and
inference on analog crossbar arrays

A flexible and fast PyTorch toolkit for simulating training and inference on analog crossbar arrays

5 April 2021

Manuel Le Gallo

Kaoutar El Maghraoui

Vijay Narayanan

Papers citing "A flexible and fast PyTorch toolkit for simulating training and inference on analog crossbar arrays"

8 / 8 papers shown

Title
NeuroSim V1.5: Improved Software Backbone for Benchmarking Compute-in-Memory Accelerators with Device and Circuit-level Non-idealities James Read Ming-Yen Lee Wei-Hsing Huang Yuan-Chun Luo A. Lu Shimeng Yu 44 0 0 05 May 2025
Analog In-memory Training on General Non-ideal Resistive Elements: The Impact of Response Functions Zhaoxian Wu Quan Xian Tayfun Gokmen Omobayode Fagbohungbe Tianyi Chen 96 0 0 17 Feb 2025
A Realistic Simulation Framework for Analog/Digital Neuromorphic Architectures Fernando M. Quintana Maryada Pedro L. Galindo Elisa Donati Giacomo Indiveri Fernando Perez-Peña 36 0 0 23 Sep 2024
Retro-li: Small-Scale Retrieval Augmented Generation Supporting Noisy Similarity Searches and Domain Shift Generalization Gentiana Rashiti G. Karunaratne Mrinmaya Sachan Abu Sebastian Abbas Rahimi RALM 49 0 0 12 Sep 2024
Fast offset corrected in-memory training Malte J. Rasch F. Carta Omobayode Fagbohungbe Tayfun Gokmen 39 6 0 08 Mar 2023
Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators Malte J. Rasch C. Mackin Manuel Le Gallo An Chen A. Fasoli ... P. Narayanan H. Tsai G. Burr Abu Sebastian Vijay Narayanan 18 86 0 16 Feb 2023
Side-channel attack analysis on in-memory computing architectures Ziyu Wang Fanruo Meng Yongmo Park Jason K. Eshraghian Wei D. Lu 29 21 0 06 Sep 2022
Gradient-based Neuromorphic Learning on Dynamical RRAM Arrays Peng Zhou Jason K. Eshraghian Dong-Uk Choi Wei D. Lu S. Kang 19 16 0 26 Jun 2022