Locality-aware and load-balanced static task scheduling for MapReduce
نویسندگان
چکیده
منابع مشابه
Load-balanced and locality-aware scheduling for data-intensive workloads at extreme scales
Data driven programming models such as many-task computing (MTC) have been prevalent for running data-intensive scientific applications. MTC applies over-decomposition to enable distributed scheduling. To achieve extreme scalability, MTC proposes a fully distributed task scheduling architecture that employs as many schedulers as the compute nodes to make scheduling decisions. Achieving distribu...
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Modern computer architectures expose an increasing number of parallel features supported by complex memory access and communication structures. Currently used task scheduling techniques perform poorly since they focus solely on balancing computation load across parallel features and remain oblivious to locality properties of support structures. We contribute with locality-aware task scheduling ...
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ژورنال
عنوان ژورنال: Future Generation Computer Systems
سال: 2019
ISSN: 0167-739X
DOI: 10.1016/j.future.2018.06.035