My research focuses on adapting artificial intelligence approaches into traditional systems.
My research focuses on adapting artificial intelligence approaches into traditional systems.
Hwijoon Lim, Wei Bai, Yibo Zhu, Youngmok Jung and Dongsu Han
Hyunho Yeo, Chan Ju Chong, Youngmok Jung, Juncheol Ye and Dongsu Han
Jaehong Kim, (CO-First)Youngmok Jung, Hyunho Yeo, Juncheol Ye and Dongsu Han
Hyunho Yeo, Youngmok Jung, Jaehong Kim, Jinwoo Shin, and Dongsu Han
- Developed a short read alignment tool that is the first to leverage learned indices to find exact match of
short substring (0-300 length) in the long reference DNA (6 billion length for human genome).
- Achieved up to 3.45x speedup in throughput over state-of-the-art algorithm by reducing the number
of instructions by 4.60x, memory accesses by 8.77x, and LLC misses by 2.21x, while ensuring
identical output.
- Implemented new APIs in C++ WebRTC open-source code from Google; 1) to obtain decoded and
encoded frames with the frame timestamp. 2) to control and obtain bandwidth information in the
WebRTC.
- Used Python wrapper (CPython) to integrate the newly added API to the LiveNAS system.
- Developed the LiveNAS system which involves; 1) Online training and inferencing super-resolution
DNN model during the live video stream. 2) Transmitting training data over RTP. 3) Controlling bandwidth allocation
- Implemented NS-3 simulation code[C++] for RDMA protocol and TLT.
- Managed switch configuration which involves priority-flow-control, Shared Buffer Pool size, and Packet
Color.
- Developed an integrated-ABR (adaptive bit-rate) controller code[Python,Tensorflow] based on Reinforcement Learning (actor-critic framework of A3C).
- Developed simulation code for video delivery to train RL model and measure user QoE (Quality of Experience).
- Implemented evaluation code to run 5,832 hours of real-time video streaming in Google Cloud in just a few days.