Fast structural variation (deletion, insertion and inversion) detection between genome of different individuals is the main goal of this project. The internship team is planning in extending new algorithms to reduce the number of false positive calls (especially for deletions) and to parallelize it using Graphics Processing Unit (GPU). The standard approach implementation of the algorithms, as a result of high computational needs, is not fast enough for every day use by health science centers (such as hospitals). Thus, using the GPU hardware which gives us the ability to highly parallelize the computation will make it more efficient. We will implement the algorithms using GPU and Compute Unified Device Architecture (CUDA, which is the compute engine of the GPUs) such that it is much faster than and more cost efficient than before.