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Energy and power consumption are major limitations to continued scaling ofcomputing systems. Inexactness, where the quality of the solution can be tradedfor energy savings, has been proposed as an approach to overcoming thoselimitations. In the past, however, inexactness necessitated the need for highlycustomized or specialized hardware. The current evolution of commercialoff-the-shelf(COTS) processors facilitates the use of lower-precisionarithmetic in ways that reduce energy consumption. We study these newopportunities in this paper, using the example of an inexact Newton algorithmfor solving nonlinear equations. Moreover, we have begun developing a set oftechniques we call reinvestment that, paradoxically, use reduced precision toimprove the quality of the computed result: They do so by reinvesting theenergy saved by reduced precision.

Doing Moore with Less -- Leapfrogging Moore's Law with Inexactness for Supercomputing