Search Results for "speedup"

Add prefix ThreadsX. to functions from Base to get some speedup, if supported. The reduce-based functions support any collections that implement SplittablesBase.jl interface including arrays, Dict, Set, and iterator transformations. In particular, these functions support iterator comprehension. ThreadsX.jl is aiming at providing API compatible with Base functions to easily parallelize Julia programs.

Package JuliaCall is an R interface to Julia, which is a high-level, high-performance dynamic programming language for numerical computing. Below is an image for Mandelbrot set. JuliaCall brings more than 100 times speedup of the calculation.

...However if you have a large number of images (several hundrets or more than thousand) and control points, PTOptimizer typically needs much time (up to several days) for the optimization of the parameters. fastPTOptimizer decreases the processing time for large panoramas (a speedup factor of 100 or more can be achieved). This is possible by exploiting the sparseness of the mathematical optimization problem. The original PTOptimizer uses the well proven Levenberg Marquardt optimizer lmdif from the minpack software. fastPTOptimizer uses a "sparse" optimizer lmdif_sparse that uses the SuiteSparse library.

.... */ // N - - - | speed == STOPPED // - - Y - | speed == SLOW // - N - Y | speed == FAST // ______|___________________ // X - X - | Stop(); // - - - X | SlowDown(); // - X - - | SpeedUp(); //END_TABLE: