Abstract:The Parallel computing platforms enable dramatic increases in computing performance by harnessing the power of Graphics Processing Units (GPUs). Their design, based on a high level of hardware parallelization achieved through a big number of processing cores, made GPUs serious competitors for CPU based processing architectures. This fact is most obvious when it comes to processing huge amount of data. Many recent studies aimed at the development of GPU based implementations for various fields such as: astronomy, medicine, image processing, data compression and others. However, very few of them aimed at achieving information retrieval improvement based on GPU. Considering this, along with the latest stage of content based information retrieval algorithms and their practical efficiency for a wide variety of applications, this paper focuses on emphasizing parallel GPGPU algorithms performances against their CPU equivalents.