3 papers
cs.LG2026
Learning to Score: Tuning Cluster Schedulers through Reinforcement Learning
Martin Asenov, Qiwen Deng, Gingfung Yeung +1
Efficiently allocating incoming jobs to nodes in large-scale clusters can lead to substantial improvements in both cluster utilization and job performance. In order to allocate inc…
cs.DC2024
Serverless Cold Starts and Where to Find Them
Artjom Joosen, Ahmed Hassan, Martin Asenov +5
This paper releases and analyzes a month-long trace of 85 billion user requests and 11.9 million cold starts from Huawei's serverless cloud platform. Our analysis spans workloads f…
cs.LG2024
DAM: Towards A Foundation Model for Time Series Forecasting
Luke Darlow, Qiwen Deng, Ahmed Hassan +5
It is challenging to scale time series forecasting models such that they forecast accurately for multiple distinct domains and datasets, all with potentially different underlying c…