Optimization is a term that is applied to different technical disciplines and is often overused (and sometimes misused). In the data center industry, when we speak of optimization, the meaning is to maximize performance and efficiency of a computer, cooling system, UPS gear, etc. The nuance to this meaning is an "and" statement, not an "or" statement. This example is a good demonstration that the optimization process cannot sacrifice performance for efficiency or vice versa.
One of my favorite examples of optimization is how NASA developed the space program in the 50s and 60s. NASA engineers were faced with an ultra-complex optimization problem, including not only performance and efficiency, but also mission viability and, of paramount importance, astronaut safety. While certainly trade-offs were made, it would not have been acceptable to improve efficiency at the expense of mission viability, or jeopardize astronaut safety to improve spacecraft performance. For the long-term success of their fledgling space program, NASA engineers understood the essentialness of the optimization process and baked it in to their design and testing procedures. In fact, NASA now has an entire branch dedicated to optimization, aptly named the "Multidisciplinary Design, Analysis, and Optimization Branch," located at NASA Glenn Research Center in Ohio.
So when we turn to the HP Performance Optimized Datacenter (POD), the word optimization is sandwiched between "performance" and "data center." Even the name demonstrates the preeminence of the optimization process. While certainly the POD won't be traveling into space (at least not yet), the rigor and depth of analysis to maximize performance and value, while minimizing energy use and physical footprint, is manifested in a data center that is unparalleled amongst its peers.
Having the ability to deploy a compact, high-density data center either as a stand-alone building or connected to an existing center provides great flexibility and significantly accelerates the time to the floor-ready date. The compact form factor of the POD also allows for highly efficient power and cooling systems by reducing the lengths of electrical feeders. And by supplying the cooling air directly in front of the IT equipment and containing the hot air expelled from the computers (eliminating the unintentional mixing of air streams) improves both energy efficiency and performance of computer equipment. The shorter feeder lengths and proximity of the cooling to the IT equipment also reduces cost when compared with a traditional data center.
These are just a few of the design features that exemplify the criticality of employing the optimization process. So when discussing the POD, the word optimization can be used without fear of misuse or overuse.
You might be interested to read my previous blogs about modular data centers: