Rendering 3D Graphics on a 32×32 RGB LED Matrix Display with a Raspberry Pi and GeeXLab
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While there is never any shortage of vendors touting their hardware acceleration tool as the silver bullet for your computing bottlenecks, it’s important to keep in mind that it is not the hardware, but the algorithm and the data set that should inform your choice, along with cost and ease of use. The fact that GPU chipmaker NVIDIA has made porting code for GPUs easier for the average bench biologist with its CUDA software technology helps the argument for considering this breed of acceleration technology.