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Control Speculation for Energy-Efficient Next-Generation Superscalar Processors

Summary: Control Speculation for Energy-Efficient
Next-Generation Superscalar Processors
Juan L. AragoŽn, Member, IEEE Computer Society, JoseŽ GonzaŽlez, Member, IEEE Computer Society,
and Antonio GonzaŽlez, Member, IEEE Computer Society
Abstract--Conventional front-end designs attempt to maximize the number of "in-flight" instructions in the pipeline. However, branch
mispredictions cause the processor to fetch useless instructions that are eventually squashed, increasing front-end energy and issue
queue utilization and, thus, wasting around 30 percent of the power dissipated by a processor. Furthermore, processor design trends
lead to increasing clock frequencies by lengthening the pipeline, which puts more pressure on the branch prediction engine since
branches take longer to be resolved. As next-generation high-performance processors become deeply pipelined, the amount of wasted
energy due to misspeculated instructions will go up. The aim of this work is to reduce the energy consumption of misspeculated
instructions. We propose Selective Throttling, which triggers different power-aware techniques (fetch throttling, decode throttling, or
disabling the selection logic) depending on the branch prediction confidence level. Results show that combining fetch-bandwidth
reduction along with select-logic disabling provides the best performance in terms of overall energy reduction and energy-delay
product improvement (14 percent and 10 percent, respectively, for a processor with a 22-stage pipeline and 16 percent and 13 percent,
respectively, for a processor with a 42-stage pipeline).
Index Terms--Control speculation, energy-aware systems, low-power design, processor architecture.
CONTINUING advances in semiconductor technology lead
to more powerful processors in which power dissipa-


Source: Aragón Alcaraz, Juan Luis - Departamento de Ingenieria y Tecnologia de Computadores, Universidad de Murcia


Collections: Computer Technologies and Information Sciences