We request a total of 110,000 Euro to purchase the hardware for building a GPU-based supercomputer at the Science Faculty of Leiden University. We propose to assemble and use a multipurpose parallel computer for scientific production and further development of GPU-accelerated algorithms. By attaching graphical processing units (GPUs) to a cluster of workstations we gain the flexibility, communication characteristics and the raw super-computer power comparable to the national supercomputer Huygens-II, at a fraction of the cost. Normally the GPUs in a computer are used for visualization only, but by programming them smartly their enormous compute power can be used to accelerate general user applications by a factor of 100 or more. The electricity used by such a computer remains comparable to that of a single PC, reducing the CO2 output per TeraFLOP by more than a factor 100 compared to a general-purpose supercomputer. By connecting several of such GPU equipped computers, we can build a low cost parallel computer which matches todays fastest supercomputers. We plan to build and use an 8-node low-latency Beowulf cluster with 4 GPUs per node, providing a total computer power of for example around 64TFLOP/s using 4~NVIDIA GTX295s. We call the computer Little Green Machine (LGM), to indicate that its footprint and power consumption are tiny compared to a regular supercomputer.