  Networked embedded systems typically leverage a collection of low-power
embedded systems (nodes) to collaboratively execute applications spanning
diverse application domains (e.g., video, image processing, communication,
etc.) with diverse application requirements. The individual networked nodes
must operate under stringent constraints (e.g., energy, memory, etc.) and
should be specialized to meet varying application requirements in order to
adhere to these constraints. Phase-based tuning specializes system tunable
parameters to the varying runtime requirements of different execution phases to
meet optimization goals. Since the design space for tunable systems can be very
large, one of the major challenges in phase-based tuning is determining the
best configuration for each phase without incurring significant tuning overhead
(e.g., energy and/or performance) during design space exploration. In this
paper, we propose phase distance mapping, which directly determines the best
configuration for a phase, thereby eliminating design space exploration. Phase
distance mapping applies the correlation between the characteristics and best
configuration of a known phase to determine the best configuration of a new
phase. Experimental results verify that our phase distance mapping approach,
when applied to cache tuning, determines cache configurations within 1 % of the
optimal configurations on average and yields an energy delay product savings of
27 % on average.
