- SNU PL: http://ropas.snu.ac.kr/~dreameye/PL/
- Rust: https://rinthel.github.io/rust-lang-book-ko/ch08-02-strings.html
- Ocaml:
- Haskell:
- Graph Optimization (https://pdfs.semanticscholar.org/e37b/58bb5c056fa972a0a502d46b5abcfd7da5e1.pdf)
- Dynamic Programming
- Cost Optimization
- Pattern Recognition and ML: http://norman3.github.io/prml
- Convolution Neural Network
- Recurrent Neural Network
- Graph Neural Network
- Generative Adversarial Network
- Face Emotion Detection
- Real Time Classification
- Deepfake
- Chat GPT, LLaMA
- Stable Diffusion
- PyTorch (https://news.hada.io/topic?id=5578)
- Frontend: TVM
- Backend: MLIR, CUDA
- Chiplet-based digital in-memory (https://www.techtarget.com/searchenterpriseai/news/365531813/Infrastructure-to-support-Open-AIs-ChatGPT-could-be-costly)
- SNU FriendlAI: https://medium.com/friendliai/terra-imperative-symbolic-co-execution-of-deep-learning-programs-b4205a0a3599
- TPU: https://arxiv.org/ftp/arxiv/papers/1704/1704.04760.pdf
Matrix vs Tensor vs Layer
Memory Allocation & Scheduling Optimization
DL Model Quantization (maybe not)
MCU Scheduling??
- Specific model acceleration (chatgpt, stable diffusion etc)
- Samsung, SK Hynix (https://n.news.naver.com/article/277/0005226467)
- K-Cloud Project (https://www.thelec.kr/news/articleView.html?idxno=19989)
- PIM - Process In Memory (http://www.sbiztoday.kr/news/articleView.html?idxno=12956)