4 papers
Structured Testbench Generation for LLM-Driven HDL Design and Verification-Oriented Data Curation
En-Ming Huang, Yu-Hung Kao, Ren-Hao Deng +10
Automated testbench generation has become a critical bottleneck in large language model (LLM)-driven Register Transfer Level (RTL) workflows, where large numbers of candidate desig…
MDM: Manhattan Distance Mapping of DNN Weights for Parasitic-Resistance-Resilient Memristive Crossbars
Matheus Farias, Wanghley Martins, H. T. Kung
Manhattan Distance Mapping (MDM) is a post-training deep neural network (DNN) weight mapping technique for memristive bit-sliced compute-in-memory (CIM) crossbars that reduces para…
Efficient Reprogramming of Memristive Crossbars for DNNs: Weight Sorting and Bit Stucking
Matheus Farias, H. T. Kung
We introduce a novel approach to reduce the number of times required for reprogramming memristors on bit-sliced compute-in-memory crossbars for deep neural networks (DNNs). Our ide…
Sorted Weight Sectioning for Energy-Efficient Unstructured Sparse DNNs on Compute-in-Memory Crossbars
Matheus Farias, H. T. Kung
We introduce (SWS): a weight allocation algorithm that places sorted deep neural network (DNN) weight sections on bit-sliced compute-in-memory (…