4 papers
Enhancing Finite State Machine Design Automation with Large Language Models and Prompt Engineering Techniques
Qun-Kai Lin, Cheng Hsu, Tian-Sheuan Chang
Large Language Models (LLMs) have attracted considerable attention in recent years due to their remarkable compatibility with Hardware Description Language (HDL) design. In this pa…
CIMR-V: An End-to-End SRAM-based CIM Accelerator with RISC-V for AI Edge Device
Yan-Cheng Guo and, Tian-Sheuan Chang, Chih-Sheng Lin +5
Computing-in-memory (CIM) is renowned in deep learning due to its high energy efficiency resulting from highly parallel computing with minimal data movement. However, current SRAM-…
A Low-Power Streaming Speech Enhancement Accelerator For Edge Devices
Ci-Hao Wu, Tian-Sheuan Chang
Transformer-based speech enhancement models yield impressive results. However, their heterogeneous and complex structure restricts model compression potential, resulting in greater…
VESTA: A Versatile SNN-Based Transformer Accelerator with Unified PEs for Multiple Computational Layers
Ching-Yao Chen, Meng-Chieh Chen, Tian-Sheuan Chang
Spiking Neural Networks (SNNs) and transformers represent two powerful paradigms in neural computation, known for their low power consumption and ability to capture feature depende…