# Systems for ML

## ML Lifecycle

* [Data Processing](https://paper.lingyunyang.com/paper-list/systems-for-ml/data-processing)
* [Deep Learning Training](https://paper.lingyunyang.com/paper-list/systems-for-ml/deep-learning-training)
* [Resource Scheduler](https://paper.lingyunyang.com/paper-list/systems-for-ml/resource-scheduler)
* [Model Serving](https://paper.lingyunyang.com/paper-list/systems-for-ml/model-serving)
* [Deep Learning Compiler](https://paper.lingyunyang.com/paper-list/systems-for-ml/deep-learning-compiler)
* [Deep Learning Framework](https://paper.lingyunyang.com/paper-list/systems-for-ml/deep-learning-framework)
* [Cloud-Edge Collaboration](https://paper.lingyunyang.com/paper-list/systems-for-ml/cloud-edge-collaboration)

## Various Workloads

* [Large Language Model (LLM)](https://paper.lingyunyang.com/paper-list/systems-for-ml/llm)
* [Diffusion Models](https://paper.lingyunyang.com/paper-list/systems-for-ml/diffusion-models)
* [Deep Learning Recommendation Model (DLRM)](https://paper.lingyunyang.com/paper-list/systems-for-ml/dlrm)
* [Mixture of Experts (MoE)](https://paper.lingyunyang.com/paper-list/systems-for-ml/moe)
* [Hyper-Parameter Tuning (HPO)](https://paper.lingyunyang.com/paper-list/systems-for-ml/hpo)
* [Reinforcement Learning (RL)](https://paper.lingyunyang.com/paper-list/systems-for-ml/rl)