The Department of Computer Science of Federal University of Minas Gerais – DCC/UFMG and Khronos Chapter Brazil have been working together to spread and strengthen industrial and scientific use of Khronos’ standards, most notably OpenCL and OpenGL.
On March 12th a talk was held with students and researchers of the Computer Vision laboratory – VeRLAB to present benefits of using GPGPU through OpenCL to accelerate CV algorithms.
Machine learning and computer vision have become a reality in people’s daily life through smart wearables (smart glasses, watches phones), vehicles capable of recognizing traffic signs, biometric systems and many others. These technologies increase safety and comfort when using such machines and are currently object of active research. However, development of better algorithms and the possibility of executing them in mobile devices under acceptable time frames and lower energy consumption still remain as open challenges.
This presentation covers topics on how GPU parallel processing allows performance and energy efficiency increases when executing algorithms whose inputs are images. Accelerations up to 800x may be obtained by intelligent use of appropriate parallel algorithms suited to SIMD architectures, explicit cache management and use of texture samplers.
- Download Presentation (Portuguese only)
- Source code: OpenCL implementation of disparity map
- Source code: OpenCL optical flow
- Demonstration: Generalized Hough Transform
Video: Generalized Hough Transform
Video: Dynamic shader:
Video: Heat transfer simulation