Intensity modulated radiation therapy (IMRT) is a highly effective cancer treatment technique that accurately delivers radiation to cancerous tissues while preserving the surrounding healthy organs. In this work, we present a method to exploit multicore servers to address IMRT Radiation Therapy plans (RP) problems. Our method uses a gradient descent algorithm to optimize the generalized Equivalent Uniform Dose parameters, and employs high-performance computing techniques such as parallelization and batching to speed up the computation. To evaluate our proposal, we conducted extensive benchmarking on three distinct multicore platforms with varying micro-architectures, assessed across different batch sizes and thread configurations. The results showcase that our method provides substantial computational speed improvements while consistently generating high-quality RP that conform to clinical constraints, albeit at a high computational cost. The parallelization schemes outlined in this work attain substantial speedups while still delivering clinically feasible plans, ultimately resulting in time savings and reduced workload for medical planners.