With the processing power of GPUs (i.e. the graphics chip located on the video card) increasing everyday – to the point that they are more powerful than regular CPUs for math calculations – it's been discussed for quite some time now if GPUs couldn't be used as a CPU for processing regular programs. The idea, known as GPGPU (General-Purpose Computation on GPUs), is to throw to the GPU calculations that would otherwise be done by the CPU in order to increase performance. The problem is how to do this, as a programmer would have to know how to program to a specific GPU in order to make a program that could use the system GPU, and this program wouldn't work with a different GPU. To solve this issue nVidia launched a free C compiler to their GeForce 8800 series, called CUDA. With CUDA any programmer can easily compile their programs written in C to use the power of the system GPU to process their program. Going one step further, nVidia launched a series of "video cards" called Tesla. These "video cards" feature GeForce 8800 GPUs but they do not produce video: they are targeted to be used as CPUs, processing programs. In this article we will tell you everything you need to know about Tesla, including a lot of pictures of Tesla solutions.