  Energy and power consumption are major limitations to continued scaling of
computing systems. Inexactness, where the quality of the solution can be traded
for energy savings, has been proposed as an approach to overcoming those
limitations. In the past, however, inexactness necessitated the need for highly
customized or specialized hardware. The current evolution of commercial
off-the-shelf(COTS) processors facilitates the use of lower-precision
arithmetic in ways that reduce energy consumption. We study these new
opportunities in this paper, using the example of an inexact Newton algorithm
for solving nonlinear equations. Moreover, we have begun developing a set of
techniques we call reinvestment that, paradoxically, use reduced precision to
improve the quality of the computed result: They do so by reinvesting the
energy saved by reduced precision.
