- Studying: Deep learning training acceleration with Vulkan, SystemVerilog
- Building: AI acceleration for FPGA env & vulkan-supported devices
- Learning: Parallel Programming & Operating Systems.
- Collaborating: Vulkan, SIMD parallel optimization and Memory optimization projects.
Student building AI accelerators. HW: FPGA/SystemVerilog. SW: C++/CUDA. Optimizing Transformer inference via SIMD, cache, & quantization for edge devices.
- south Korea
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06:29
(UTC +09:00)
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Driver-drowsiness-detection
Driver-drowsiness-detection PublicDriver Drowsiness Detection with YOLOv8 and Facial Features Combat driver fatigue with this deep learning-powered system that utilizes YOLOv8 to detect open and closed eyes, accurately assessing dr…
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NPU-FPGA-Transformer-Accelerator-KV260
NPU-FPGA-Transformer-Accelerator-KV260 PublicA Transformer(gemma3N E4B LLM)accelerator based on a 2D (Floating-Point) Systolic Array, bitShift-only-Adder, architecture and dynamic multi channel memory management optimization techniques design…
SystemVerilog 4
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