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Grzegorz Malewicz
Researcher at Google
Publications - 32
Citations - 4472
Grzegorz Malewicz is an academic researcher from Google. The author has contributed to research in topics: Schedule & Scheduling (computing). The author has an hindex of 16, co-authored 32 publications receiving 4178 citations. Previous affiliations of Grzegorz Malewicz include University of Alabama.
Papers
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Proceedings ArticleDOI
Pregel: a system for large-scale graph processing
Grzegorz Malewicz,Matthew H. Austern,Aart J. C. Bik,James C. Dehnert,Ilan Horn,Naty Leiser,Grzegorz Czajkowski +6 more
TL;DR: A model for processing large graphs that has been designed for efficient, scalable and fault-tolerant implementation on clusters of thousands of commodity computers, and its implied synchronicity makes reasoning about programs easier.
Proceedings ArticleDOI
Pregel: a system for large-scale graph processing - "ABSTRACT"
Grzegorz Malewicz,Matthew H. Austern,Aart J. C. Bik,James C. Dehnert,Ilan Horn,Naty Leiser,Grzegorz Czajkowski +6 more
TL;DR: The model has been designed for efficient, scalable and fault-tolerant implementation on clusters of thousands of commodity computers, and its implied synchronicity makes reasoning about programs easier.
Journal ArticleDOI
A Tool for Prioritizing DAGMan Jobs and its Evaluation
TL;DR: This paper presents the design, implementation, and evaluation of a practical scheduling tool inspired by a recently developed scheduling theory, given a DAGMan input file with interdependent jobs, that significantly outperforms currently used schedules under a wide range of system parameters.
Journal ArticleDOI
Toward a theory for scheduling dags in Internet-based computing
TL;DR: A suite of algorithms that decompose a given dag Gscr to expose its building blocks and an execution-priority relation xutri on building blocks are provided, which specify an optimal schedule for GscR.
Proceedings ArticleDOI
A Tool for Prioritizing DAGMan Jobs and Its Evaluation
TL;DR: This paper presents the design, implementation, and evaluation of a practical scheduling tool inspired by a recently developed scheduling theory, given a DAGMan input file with interdependent jobs, that significantly outperforms currently used schedules under a wide range of system parameters.