Parallelization of the Kriging Algorithm in Stochastic Simulation with GPU Accelerators

3D realtime modeling places a heavy load on CPU. This paper presents a new method on 3D visualization in reservoir modeling system by using the computation power of modern programmable graphics hardware (GPU). The proposed scheme is devised to achieve parallel processing of massive reservoir logging data. By taking advantage of the GPU's parallel processing capability, moreover, the performance of our scheme is discussed in comparison with that of the implementation entirely running on CPU. Experimental results clearly show that the proposed parallel processing can remarkably accelerate the data clustering task. Especially, although data-transferring from GPU to CPU is generally costly, acceleration by GPU is significant to save the total execution time of data-clustering, and significantly alleviates the computing load on CPU.