Energy-Efficient Hardware Implementation of Spiking-Restricted Boltzmann Machines Using Pseudo-Synaptic SamplingHyunwoo KimSuyeon Janget al.2024Advanced Intelligent Systems
Solving Max-Cut Problem Using Spiking Boltzmann Machine Based on Neuromorphic Hardware with Phase Change MemoryYu Gyeong KangMasatoshi Ishiiet al.2024Advanced Science
Design of Analog-AI Hardware Accelerators for Transformer-based Language Models (Invited)Geoffrey BurrSidney Tsaiet al.2023IEDM 2023
An analog-AI chip for energy-efficient speech recognition and transcriptionS. AmbrogioPritish Narayananet al.2023Nature
Phase Change Memory-based Hardware Accelerators for Deep Neural NetworksGeoffrey BurrPritish Narayananet al.2023VLSI Technology 2023
Architectures and Circuits for Analog-memory-based Hardware Accelerators for Deep Neural NetworksSidney TsaiPritish Narayananet al.2023ISCAS 2023
Analog In-Memory Computing for Deep Neural Network AccelerationAndrea FasoliGeoffrey Burret al.2023MRS Spring Meeting 2023
Analog-AI: Hardware Acceleration for Deep Neural Network InferenceGeoffrey BurrSidney Tsaiet al.2023NeuMatDeCaS 2023
A Heterogeneous and Programmable Compute-In-Memory Accelerator Architecture for Analog-AI Using Dense 2-D MeshShubham JainHsinyu Tsaiet al.2023IEEE Transactions on VLSI Systems
Impact of PCM noise on the Spiking Restricted Boltzmann Machine via On-Chip Trainable PCM synapsesUicheol ShinMasatoshi Ishiiet al.2022MRS Fall Meeting 2022