1997 · 345 citations · 6 references
EngineeringEnergy EfficiencyPower Optimization (Eda)Computer ArchitectureEnergy DissipationLow-power CachesSystems EngineeringThermodynamicsParallel ComputingDetailed SimulatorPower-aware DesignWeb CachePower-aware ComputingElectrical EngineeringComputer EngineeringCachingEnergySignal ProcessingEnergy ManagementConventional CachesPower-efficient Computing
The paper develops analytical models to estimate energy dissipation in conventional and low‑power cache architectures. The models use runtime cache statistics and stochastic signal distributions, and are validated against the CAPE simulator. The models achieve ≤2% error for conventional caches but over‑predict low‑power cache dissipation by up to 30%, likely due to correlated signals and locality effects.
We present detailed analytical models for estimating the energy dissipation in conventional caches as well as low energy cache architectures. The analytical models use the run time statistics such as hit/miss counts, fraction of read/write requests and assume stochastical distributions for signal values. These models are validated by comparing the power estimated using these models against the power estimated using a detailed simulator called CAPE (CAache Power Estimator). The analytical models for conventional caches are found to be accurate to within 2% error. However, these analytical models over-predict the dissipations of low-power caches by as much as 30%. The inaccuracies can be attributed to correlated signal values and locality of reference, both of which are exploited in making some cache organizations energy efficient.
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