Grid computing seeks to aggregate computing resources which are geographically distributed or heterogeneous and leverage on resources one don't own for oneself computational intensive applications. The procedure to generate the look-up table (LUT), which is very commonly used for aerosol remote sensing retrieval, is computational intensive even though the aims to take it are mainly to speedup the retrieval computation. This work focuses on realization of the compute-intensive look-up table generation on GCP-ARS (Grid Computation Platform for Aerosol Remote Sensing), which is one grid middleware we are developing based on Condor system. We discuss our approach to parameterization, task partitioning, generated methodology, and the collection of result. Experimental results obtained using Condor-pool consisted of commodity PCs are discussed.