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Combining load operations

Authors: Sohi, Guri;

Combining load operations

Abstract

General-purpose processors continue to proliferate, and microarchitectural innovations are going to be critical to continue improving their performance and energy efficiency. In this talk we will present a novel technique for combining multiple load instructions in order to optimize their execution. A simple technique is used to learn and predict the number of contemporaneous accesses to a region of memory and classify a particular dynamic load into a normal or a fat load. Fat loads bring in additional data into Contemporaneous Load Access Registers (CLARs), from where other contemporaneous loads could be serviced without accessing the L1 cache. Going further, many such loads (50-60%) could be processed in the register renaming stage. This results in a significant reduction in the number of L1 cache accesses, with commensurate energy savings. In several cases the reduced latency for such loads results in an earlier resolution of some mispredicted branches, and a reduction in the number of wrong-path instructions, especially loads.

Country
Spain
Related Organizations
Keywords

Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors, High performance computing, Càlcul intensiu (Informàtica)

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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!
0
Average
Average
Average
Green