# SC 2023

## Meta Info

Homepage: <https://sc23.supercomputing.org/>

Paper list: <https://dl.acm.org/doi/proceedings/10.1145/3581784>

## Papers

### Distributed Training

* EasyScale: Elastic Training with Consistent Accuracy and Improved Utilization on GPUs \[[Paper](https://doi.org/10.1145/3581784.3607054)] \[[Code](https://github.com/sUntvoOk/EasyScale_info_for_SC23)]
  * BUAA & Alibaba
* Hanayo: Harnessing Wave-like Pipeline Parallelism for Enhanced Large Model Training Efficiency \[[Paper](https://doi.org/10.1145/3581784.3607073)] \[[Code](https://github.com/MaruyamaAya/Wpipe)]
  * NUS

### GPU Sharing

* Interference-aware Multiplexing for Deep Learning in GPU Clusters: A Middleware Approach \[[Personal Notes](https://paper.lingyunyang.com/reading-notes/conference/sc-2023/iadeep)] \[[Paper](https://doi.org/10.1145/3581784.3607060)] \[[Code](https://github.com/buzy-coder/IADeep)]
  * UMacau & SIAT, CAS
  * IADeep — a cluster scheduler to co-locate DL training tasks

### Serverless Functions

* Rethinking Deployment for Serverless Functions: A Performance-first Perspective \[[Paper](https://doi.org/10.1145/3581784.3613211)] \[[Code](https://github.com/tjulym/Chiron)]
  * TJU
  * Chiron