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Florin Dinu

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Related publications (4)

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Hawk: Hybrid Datacenter Scheduling

Anne-Marie Kermarrec, Willy Zwaenepoel, Pamela Isabel Delgado Borda, Florin Dinu

This paper addresses the problem of efficient scheduling of large clusters under high load and heterogeneous workloads. A heterogeneous workload typically consists of many short jobs and a small number of large jobs that consume the bulk of the cluster's r ...

USENIX Association2015

Don't cry over spilled records: Memory elasticity of data-parallel applications and its application to cluster scheduling

Willy Zwaenepoel, Syed Mohammad Aunn Raza, Calin Iorgulescu, Florin Dinu

Understanding the performance of data-parallel workloads when resource-constrained has significant practical importance but unfortunately has received only limited attention. This paper identifies, quantifies and demonstrates memory elasticity, an intrinsi ...

The USENIX Association2017

Kairos: Preemptive Data Center Scheduling Without Runtime Estimates

Willy Zwaenepoel, Diego Didona, Florin Dinu, Pamela Isabel Delgado Borda

The vast majority of data center schedulers use task runtime estimates to improve the quality of their scheduling decisions. Knowledge about runtimes allows the schedulers, among other things, to achieve better load balance and to avoid head-of-line blocki ...

2018

Job-aware Scheduling in Eagle: Divide and Stick to Your Probes

Willy Zwaenepoel, Diego Didona, Florin Dinu, Pamela Isabel Delgado Borda

We present Eagle, a new hybrid data center scheduler for data-parallel programs. Eagle dynamically divides the nodes of the data center in partitions for the execution of long and short jobs, thereby avoiding head-of-line blocking. Furthermore, it provides ...

ACM2016