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The advent of relatively cheap general purpose graphics processing units (GPUs) is having a huge impact on scientific computing. This is opening the door to high performance fuzzy computing (HPFC) to the masses, due to the low cost and the possibility to have GPUs on desktop computers at home. Furthermore, even mobile HPFC seems imminent, provided that your laptop is equipped with a general purpose GPU. Very recently another innovation has occurred: the availability of libraries for high level GPU programming. By using them, the programmer avoids the necessity of having detailed knowledge of the GPU's hardware architecture. The availability of such facility on Matlab (today among the most used rapid prototyping software) is also opening the door to the rapid prototyping of high performance applications, in general, and to the rapid prototyping of HPFC, in particular. In this work we show how to speed up an existing Matlab software prototype (which computes spatial maps for supporting decision making during maritime operations) with little effort. By delegating the GPU Matlab library to take care of low level optimizations, we not only save time, but also build rapidly prototyped software that is portable over different GPU hardware types.