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https://doi.org/10.1109/hpca.2...
Article . 2005 . Peer-reviewed
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DBLP
Conference object . 2023
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Software Directed Issue Queue Power Reduction

Authors: Timothy M. Jones 0001; Michael F. P. O'Boyle; Jaume Abella 0001; Antonio González 0001;

Software Directed Issue Queue Power Reduction

Abstract

The issue logic of a superscalar processor dissipates a large amount of static and dynamic power. Furthermore, its power density makes it a hot-spot requiring expensive cooling systems and additional packaging. In this paper we present a novel software assisted approach to power reduction where the processor dynamically resizes the issue queue based on compiler analysis. The compiler passes information to the processor about the number of entries needed which limits the number of instructions dispatched and resident in the queue. This saves power without adversely affecting performance. Compared with recently proposed hardware techniques, our approach is faster, simpler and saves more power. Using a simplistic scheme we achieve 47% dynamic and 31% static power savings in the issue queue with only a 2.2% performance loss. We then show that the performance loss can be reduced to less than 1.3% with 45% dynamic and 30% static power savings, outperforming all current approaches.

Country
Spain
Keywords

Parallel processing (Electronic computers), Processament en paral·lel (Ordinadors), Program compilers, Compiladors (Programes d'ordinador), Microprocessors -- Energy consumption, Parallel architectures, Queueing theory, Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors, Microprocessadors -- Consum d'energia, :Informàtica::Arquitectura de computadors [Àrees temàtiques de la UPC], Compilers (Computer programs)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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8
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