Optimizing Sorting Algorithms Using Ubiquitous Multi-core Massively Parallel GPGPU Processors

While developing naive code is uncomplicated, optimizing extremely parallel algorithms requires deep understanding of the core architecture. Recent years have witnessed a phenomenal growth in the computational capabilities and applications of GPUs. High performance of modern Graphics Processing Units may be used not only for graphics related application but also for general computing. Out of the vast applications which require parallel computing, some broadly classified are real-world applications like scientific computing, numerical simulations, healthcare, energy, data-analysis, etc. All of these applications involve wide data-intensive tasks, often subject to time constraints and space complexity. One of the fundamental issues in computer science is ordering a list of items. Bitonic sort is one of the most basic computing problems which also play a very important role in plenty of algorithms commonly used in graphics applications, such as visibility ordering or collision detection. This paper makes use of the parallel property of GPU and accelerates the function of bitonic sort which in itself is designed explicitly for parallel networks.