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Pérez et al., 2017 - Google Patents

Energy efficiency of load balancing for data-parallel applications in heterogeneous systems

Pérez et al., 2017

View PDF
Document ID
15962271628424510260
Author
Pérez B
Stafford E
Bosque J
Beivide R
Publication year
Publication venue
The Journal of Supercomputing

External Links

Snippet

The use of heterogeneous systems in supercomputing is on the rise as they improve both performance and energy efficiency. However, the programming of these machines requires considerable effort to get the best results in massively data-parallel applications. Maat is a …
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Classifications

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    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G06F9/505—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the load
    • G—PHYSICS
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    • G06F9/46—Multiprogramming arrangements
    • G06F9/48—Programme initiating; Programme switching, e.g. by interrupt
    • G06F9/4806—Task transfer initiation or dispatching
    • G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
    • G06F9/4881—Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G—PHYSICS
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    • G—PHYSICS
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