Estimation techniques are also utilized in the hardware algorithmic design to achieve faster, simpler and more efficient architecture.
Improvements can be done in two directions: better algorithms that reduce the number of arithmetic operations required to compute a solution, and more efficient architectures in terms of speed, power consumption, memory occupancy and cost.
A more efficient x86 architecture is still an x86 architecture, and right now ARM is so prevalent in the portable computing market (mobile, tablet, embedded) that even a large bump to Intel's prospects like this would take years to propagate, during which time competitors like Nvidia (Intel co-nemesis) will continue to throw in with the non-x86 option.
The software developments used in the hybrid architectures in which reaction and deliberation are combined and coordinated have accomplished, at the present time more efficient architectures, though the solutions provided are ad-hoc.
On the other hand, the evolution of the worm nervous system and of the metabolism of the bacterium might have allowed more efficient architectures to emerge, due to the evolutionary time-scales (hundreds of millions of years or more) running much longer than the time-span of existence of the commercial Internet.
It not only provides a more efficient and regular architecture compared to ordinary higher-order feedforward networks, but also maintains the fast learning property and powerful nonlinear mapping capability while avoiding the combinatorial increase in the number of required weights.
The present study offers support for the effects of music on human brain functional networks with a trend toward a more efficient but less economical architecture.
The resulting Si/RGO architecture possessed a more efficient conducting/buffering framework for Si nanoparticles when compared to the framework of the mechanically mixed Si/RGO product.
In this paper, we propose to use Multi-Valued Decision Diagrams (mdds) as a more efficient data structure for the sdyna architecture and describe a planning algorithm and an incremental learning algorithm dedicated to this new structured representation.
The results show that the method offers a more efficient utilization of multi-GPU computer architectures.
