3 papers
cs.AR2024
PIMCOMP: An End-to-End DNN Compiler for Processing-In-Memory Accelerators
Xiaotian Sun, Xinyu Wang, Wanqian Li +2
Various processing-in-memory (PIM) accelerators based on various devices, micro-architectures, and interfaces have been proposed to accelerate deep neural networks (DNNs). How to d…
quant-ph2024
SuperEncoder: Towards Universal Neural Approximate Quantum State Preparation
Yilun Zhao, Bingmeng Wang, Wenle Jiang +4
Numerous quantum algorithms operate under the assumption that classical data has already been converted into quantum states, a process termed Quantum State Preparation (QSP). Howev…
cs.AR2024
PIMSIM-NN: An ISA-based Simulation Framework for Processing-in-Memory Accelerators
Xinyu Wang, Xiaotian Sun, Yinhe Han +1
Processing-in-memory (PIM) has shown extraordinary potential in accelerating neural networks. To evaluate the performance of PIM accelerators, we present an ISA-based simulation fr…