Real-Time Implementation and Performance Optimization of Local Derivative Pattern Algorithm on GPUs

Abstract

<p><span>Pattern based texture descriptors are widely used in Content Based Image Retrieval (CBIR) for efficient retrieval of matching images. Local Derivative Pattern (LDP), a higher order local pattern operator, originally proposed for face recognition, encodes the distinctive spatial relationships contained in a local region of an image as the feature vector. LDP efficiently extracts finer details and provides efficient retrieval however, it was proposed for images of limited resolution. Over the period of time the development in the digital image sensors had paid way for capturing images at a very high resolution. LDP algorithm though very efficient in content-based image retrieval did not scale well when capturing features from such high-resolution images as it becomes computationally very expensive. This paper proposes how to efficiently extract parallelism from the LDP algorithm and strategies for optimally implementing it by exploiting some inherent General-Purpose Graphics Processing Unit (GPGPU) characteristics. By optimally configuring the GPGPU kernels, image retrieval was performed at a much faster rate. The LDP algorithm was ported on to Compute Unified Device Architecture (CUDA) supported GPGPU and a maximum speed up of around 240x was achieved as compared to its sequential counterpart.</span></p>

CPU implementation using only logisim simulator to achieve computer architecture learning outcome

“…Thus, the learning process during the current semester will run out just to recognize many different simu lators. Some usually used simulators are: ENIA C (Electrical Nu merical Integrator and Computer) [28], VVM (Visible Virtual Machine) [29], MARS [30], Logisim [10], SPIM [31], CPU-OS simulator [32], DRAM SIM 2 [33], gem5-gpu [34] etc. Therefore, a simu lator with a specific design is needed in accordance with the Learn ing Outcome so that students are more focused on the content of the learning material.…”