@inproceedings{abdi2023palette,
author = {Abdi, Mania and Ginzburg, Sam and Lin, Charles and Faleiro, Jose M and Goiri, Íñigo and Chaudhry, Gohar Irfan and Bianchini, Ricardo and Berger, Daniel S. and Fonseca, Rodrigo},
title = {Palette Load Balancing: Locality Hints for Serverless Functions},
organization = {ACM},
booktitle = {EuroSys},
year = {2023},
month = {May},
abstract = {Function-as-a-Service (FaaS) serverless computing enables a simple programming model with almost unbounded elasticity. Unfortunately, current FaaS platforms achieve this flexibility at the cost of lower performance for data-intensive applications compared to a serverful deployment. The ability to have computation close to data is a key missing feature. We introduce Palette load balancing, which offers FaaS applications a simple mechanism to express locality to the platform, through hints we term “colors”. Palette maintains the serverless nature of the service – users are still not allocating resources – while allowing the platform to place successive invocations related to each other on the same executing node. We compare a prototype of the Palette load balancer to a state-of-the-art locality-oblivious load balancer on representative examples of three applications. For a serverless web application with a local cache, Palette improves the hit ratio by 6x. For a serverless version of Dask, Palette improves run times by 46% and 40% on Task Bench and TPC-H, respectively. On a serverless version of NumS, Palette improves run times by 37%. These improvements largely bridge the gap to serverful implementation of the same systems},
url = {http://approjects.co.za/?big=en-us/research/publication/palette-load-balancing-locality-hints-for-serverless-functions/},
}