# Spot Instances

* SpotServe: Serving Generative Large Language Models on Preemptible Instances ([ASPLOS 2024](https://paper.lingyunyang.com/reading-notes/conference/asplos-2024)) \[[Personal Notes](https://paper.lingyunyang.com/reading-notes/conference/asplos-2024/spotserve)] \[[Paper](https://arxiv.org/abs/2311.15566)] \[[Code](https://github.com/Hsword/SpotServe)]
  * CMU & PKU & CUHK
* Can't Be Late: Optimizing Spot Instance Savings under Deadlines ([NSDI 2024](https://paper.lingyunyang.com/reading-notes/conference/nsdi-2024)) \[[Paper](https://www.usenix.org/conference/nsdi24/presentation/wu-zhanghao)] \[[Trace](https://github.com/skypilot-org/spot-traces)]
  * UC Berkeley
  * **Outstanding Paper**
* Parcae: Proactive, Liveput-Optimized DNN Training on Preemptible Instances ([NSDI 2024](https://paper.lingyunyang.com/reading-notes/conference/nsdi-2024)) \[[Paper](https://www.usenix.org/conference/nsdi24/presentation/duan)] \[[Slides](https://www.usenix.org/system/files/nsdi24_slides-duan.pdf)] \[[Code](https://github.com/JF-D/Parcae)]
  * CUHK & ByteDance & CMU & UCLA & Microsoft