This Tips and Techniques article focuses on the relative performance of Maple's various modes for floating-point computations. The example used here is the computation of a particular Newton fractal, which is easily parallelizable. We compute an image representation for this fractal under several computational modes, using both serial and multithreaded computation schemes.
This article is a follow up to a previous Tips and Techniques, evalhf, Compile, hfloat and all that, which discusses functionality differences amongst Maple's the different floating-point computation modes available in Maple.
