Present Hardware-Aware Quantization for LLM Inference Optimization Research on hardware-aware quantization techniques to optimize the inference performance of large language models. Period: Apr. 2026 – Feb. 2027 Sponsor: Jeonbuk National University Implementation of Core Operation Kernels Based on Low-Level API for AI Semiconductor Support Research on implementing core operation kernels using low-level APIs to support AI semiconductors. Period: May 2026 – Nov. 2026 Sponsor: ETRI International Collaborative Research on Quantization Kernel Code Development Joint research between Jeonbuk National University and the University of Colorado on developing quantization kernel code. Period: Jun. 2026 – Aug. 2026 Sponsor: Jeonbuk National University Past Development of open-edge AI SoC hardware and software platform The compiler is based on MLIR. Period: Jun. 2023 – Dec. 2027 Sponsor: IITP Deep Learning Compiler for NPU The compiler is designed to allow state of the art compiler optimizations and code generation of neural network graphs. Period: Jan. 2018 – Dec. 2022 Sponsor: IITP SuggestBot Development of a context-based smart interaction service platform
