Simultaneously, the proposed method should use low memory and be efficient for large-scale image retrieval applications.
Lastly, the solver used for solving the Adjoint system of equations needs to be efficient for large-scale applications.
Distributed model predictive control (MPC), having been proven to be efficient for large-scale control systems, is essentially enabled by communication network connections among involved subsystems (agents).
Approaches for TEP based on optimization have not been widely used given that their high computational requirements mean that they could not be efficient for large-scale, real systems.
The computation of pairwise similarities needs to be efficient for large-scale usage.
Numerical results show that the proposed method is efficient for large-scale problems.
The results suggest that the computational effort increases very slowly with the number of particles so that the method is efficient for large-scale simulations.
The accelerated performance of the proposed 3-D model reaches 30 times of that of a single thread program, and the GPU-FVCOM implemented on a Tesla k20 device is faster than on a workstation with 20 CPU cores, which shows that the GPU-FVCOM is efficient for solving large scale sea area and high resolution engineering problems.
Besides, the straightforward implementation of pressure-based fluid structure interaction utilizing a symmetric solution strategy is validated herein to be efficient for a 3-D large scale practical usage in other finite element codes even the commercial ones to avoid using un-symmetric solvers.
It is not efficient for large scale network analysis but it provides various layout options and ways to arrange nodes in various geometric distributions.
Of these methods, AFP sequencing proves to be the most efficient for large scale identification of spotting solution in a high throughput manner.
