Analog AI as a Service: A Cloud Platform for In-Memory ComputingKaoutar El MaghraouiKim Tranet al.2024SSE 2024
Improving the Accuracy of Analog-Based In-Memory Computing Accelerators Post-TrainingCorey Liam LammieA. Vasilopouloset al.2024ISCAS 2024
Design of Analog-AI Hardware Accelerators for Transformer-based Language Models (Invited)Geoffrey BurrSidney Tsaiet al.2023IEDM 2023
In-Memory Compute Chips with Carbon-based Projected Phase-Change Memory DevicesG.S. SyedK. Brewet al.2023IEDM 2023
Programming Weights to Analog In-Memory Computing Cores by Direct Minimization of the Matrix-Vector Multiplication ErrorJulian BuchelAthanasios Vasilopouloset al.2023IEEE JESTCS
Using the IBM Analog In-Memory Hardware Acceleration Kit for Neural Network Training and InferenceManuel Le GalloCorey Liam Lammieet al.2023APL Mach. Learn.
A 64-core mixed-signal in-memory compute chip based on phase-change memory for deep neural network inferenceManuel Le GalloRiduan Khaddam-Aljamehet al.2023Nature Electronics
Exploiting the State Dependency of Conductance Variations in Memristive Devices for Accurate In-Memory ComputingAthanasios VasilopoulosJulian Buchelet al.2023IEEE T-ED
Adversarial attacks on spiking convolutional neural networks for event-based visionJulian BüchelGregor Lenzet al.2022Frontiers in Neuroscience
Gradient descent-based programming of analog in-memory computing coresJulian BuchelA. Vasilopouloset al.2022IEDM 2022