M
Mark Grondona
Researcher at Lawrence Livermore National Laboratory
Publications - 6
Citations - 1464
Mark Grondona is an academic researcher from Lawrence Livermore National Laboratory. The author has contributed to research in topics: Scheduling (computing) & Job scheduler. The author has an hindex of 6, co-authored 6 publications receiving 1132 citations.
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Book ChapterDOI
SLURM: Simple Linux Utility for Resource Management
TL;DR: A new cluster resource management system called Simple Linux Utility Resource Management (SLURM) is described in this paper, designed to be flexible and fault-tolerant and can be ported to other clusters of different size and architecture with minimal effort.
Proceedings ArticleDOI
Scalable I/O-Aware Job Scheduling for Burst Buffer Enabled HPC Clusters
Stephen Herbein,Dong H. Ahn,Don Lipari,Thomas R. W. Scogland,Marc D. Stearman,Mark Grondona,Jim Garlick,Becky Springmeyer,Michela Taufer +8 more
TL;DR: Novel batch job scheduling techniques that reduce I/O contention for underprovisioned PFSes are proposed, which increases the amount of science performed by scientific workloads and integrates into Flux, a next-generation resource and job management framework.
Proceedings ArticleDOI
Flux: A Next-Generation Resource Management Framework for Large HPC Centers
TL;DR: This paper details the design of Flux and describes and evaluates the initial prototyping effort of the key run-time components, showing that the run- time prototype provides strong and predictable scalability.
Proceedings ArticleDOI
Flux: Overcoming Scheduling Challenges for Exascale Workflows
Dong H. Ahn,Ned Bass,Albert Chu,Jim Garlick,Mark Grondona,Stephen Herbein,Joseph Koning,Tapasya Patki,Thomas R. W. Scogland,Becky Springmeyer,Michela Taufer +10 more
TL;DR: Flux is presented, a novel, hierarchical RJMS infrastructure that addresses the key scheduling challenges of modern workflows in a scalable, easy-to-use, and portable manner and can support workflows that can often feature non-traditional execution patterns.
Journal ArticleDOI
Flux: Overcoming scheduling challenges for exascale workflows
Dong H. Ahn,Ned Bass,Albert Chu,Jim Garlick,Mark Grondona,Stephen Herbein,Helgi I. Ingólfsson,Joseph Koning,Tapasya Patki,Thomas R. W. Scogland,Becky Springmeyer,Michela Taufer +11 more
TL;DR: Evaluation of Flux on some of the emerging workflow efforts at Lawrence Livermore National Laboratory indicates that the approach can significantly address major workflow scheduling challenges: job throughput, co-scheduling, job coordination and communication and portability challenges.