# Background

The exponential growth of data-intensive applications has transformed industries across the globe. Fields such as artificial intelligence (AI), machine learning (ML), big data analytics, scientific simulations, virtual reality (VR), and complex rendering tasks have led to an unprecedented demand for computational power. Graphics Processing Units (GPUs), with their ability to handle parallel processing efficiently, have become essential in managing these intensive workloads.\\

Traditional access to high-performance GPU resources is often limited to large corporations and institutions due to the high costs associated with purchasing and maintaining such hardware. Small and medium-sized enterprises (SMEs), individual developers, researchers, and enthusiasts often find themselves constrained by financial and technical barriers.\\
