> For the complete documentation index, see [llms.txt](https://paper.lingyunyang.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://paper.lingyunyang.com/reading-notes/conference/ipdps-2022/dgsf.md).

# DGSF: Disaggregated GPUs for serverless functions

## Meta Info

Presented in [IPDPS 2022](https://ieeexplore.ieee.org/document/9820659).

## Understanding the paper

### TL;DR

This paper presents **DGSF**, a platform that transparently enables serverless functions to use GPUs through CUDA APIs.

### GPU disaggregation challenges

* Support API transparency.
* Hide the latency of communication with remote GPUs.
* Load-balancing access to heavily shared GPUs.

### Implementation

* The prototype uses OpenFaaS v0.21.1 as serverless platform.
* Assume all functions are invoked *without a cold start*.

### Evaluation

* The cost of API remoting?
* The impact of DGSF's optimization?
* Utilization increase and performance gains when consolidating functions?
* The overhead of migration?