  General-purpose Computing on Graphics Processing Units (GPGPU) has been
introduced to many areas of scientific research such as bioinformatics,
cryptography, computer vision, and deep learning. However, computing models in
the High-energy Physics (HEP) community are still mainly centred around
traditional CPU resources. Tasks such as track fitting, particle
reconstruction, and Monte Carlo simulation could benefit greatly from a
high-throughput GPGPU computing model, streamlining bottlenecks in analysis
turnover. This technical note describes the basis of an implementation of an
integrated GPU discovery mechanism in GRID middleware to facilitate GPGPU.
