6 papers
Mean field optimal Core Allocation across Malleable jobs
Zhouzi Li, Mor Harchol-Balter, Benjamin Berg
Modern data centers and cloud computing clusters are increasingly running workloads composed of malleable jobs. A malleable job can be parallelized across any number of cores, yet…
BOA Constrictor: Squeezing Performance out of GPUs in the Cloud via Budget-Optimal Allocation
Zhouzi Li, Cindy Zhu, Arpan Mukhopadhyay +2
The past decade has seen a dramatic increase in demand for GPUs to train Machine Learning (ML) models. Because it is prohibitively expensive for most organizations to build and mai…
Asymptotically Optimal Scheduling of Multiple Parallelizable Job Classes
Benjamin Berg, Benjamin Moseley, Weina Wang +1
Modern computing workloads are often composed of parallelizable jobs. A parallelizable job can be completed more quickly when run on additional servers. However, each job can only…
Improving Nonpreemptive Multiserver Job Scheduling with Quickswap
Zhongrui Chen, Adityo Anggraito, Diletta Olliaro +4
Modern data center workloads are composed of multiserver jobs, computational jobs that require multiple servers in order to run. A data center server can run many multiserver jobs…
Improving Multiresource Job Scheduling with Markovian Service Rate Policies
Zhongrui Chen, Isaac Grosof, Benjamin Berg
Modern cloud computing workloads are composed of multiresource jobs that require a variety of computational resources in order to run, such as CPU cores, memory, disk space, or har…
Improving Multiresource Job Scheduling with Markovian Service Rate Policies
Zhongrui Chen, Isaac Grosof, Benjamin Berg
Modern cloud computing workloads are composed of multiresource jobs that require a variety of computational resources in order to run, such as CPU cores, memory, disk space, or har…