  The upgraded LHCb detector, due to start datataking in 2022, will have to
process an average data rate of 4~TB/s in real time. Because LHCb's physics
objectives require that the full detector information for every LHC bunch
crossing is read out and made available for real-time processing, this
bandwidth challenge is equivalent to that of the ATLAS and CMS HL-LHC software
read-out, but deliverable five years earlier. Over the past six years, the LHCb
collaboration has undertaken a bottom-up rewrite of its software
infrastructure, pattern recognition, and selection algorithms to make them
better able to efficiently exploit modern highly parallel computing
architectures. We review the impact of this reoptimization on the energy
efficiency of the real-time processing software and hardware which will be used
for the upgrade of the LHCb detector. We also review the impact of the decision
to adopt a hybrid computing architecture consisting of GPUs and CPUs for the
real-time part of LHCb's future data processing. We discuss the implications of
these results on how LHCb's real-time power requirements may evolve in the
future, particularly in the context of a planned second upgrade of the
detector.
