High Performance Computing power consumption
With changing political and even social environments driving demand for the latest “run-faster, jump-higher” processing wares, GPUs – combined with GPPs, DSPs, and/or FPGAs – just might make the “miracle” supercomputing system a reality. Variables to consider include power consumption, compute power, life-cycle extension, and physical environment.
The world of high-performance computing is particularly challenging, as new flavors of sophisticated sensors, complex cameras, and even changing political or social environments drive demand for the latest and greatest “run-faster, jump-higher” processing wares. Advanced computations, which include Software-Defined Radio, cryptography, and other types of arithmetic-intensive algorithms, are valued in R&D endeavors. And great progress has been made by using supercomputers, computer grids, clusters, clouds, gangs, and other forms of networked or otherwise connected compute nodes for such work. This is all well and good, until one wants to use this technology in real-world applications, particularly in military deployed environments such as unmanned vehicles or soldier-worn computers, where power consumption requirements – and certainly the weather – come into play.
Consider, for example, the real-world environment of a helicopter brownout, where billows of dust or sand caused by the helicopter rotors during takeoff and landing obstruct visual cues necessary for operational safely. Real-time synthetic vision systems deployed on the aircraft might assist pilots in these situations, but these systems must be designed to operate within the power budgets for the aircraft. It would be terrific if deployed high-performance computing requirements were simply solved with a one-size-fits-all system that was intrinsically power-efficient for any application and deployable in any environment.
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