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VEE 2017
Sat 8 - Sun 9 April 2017 Xi'an, China
Sat 8 Apr 2017 15:00 - 15:30 at Zhu Que Room - GPUs, FPGAs, etc Chair(s): David Chisnall

Real-time 3D space understanding is becoming prevalent across a wide range of applications and hardware platforms. In order to meet the desired Quality of Service (QoS), computer vision applications tend to be heavily parallelized and exploit any available hardware accelerators. Current approaches in achieving real-time computer vision, evolve around programming languages typically associated with High Performance Computing along with binding extensions for OpenCL or CUDA execution.

Such implementations, although high performing, lack portability across the wide range of diverse hardware resources and accelerators. In this paper, we showcase how a complex computer vision application can be implemented within a managed runtime system. We discuss the complexities of achieving high-performing and portable execution across embedded and desktop configurations. Furthermore, we demonstrate that it is possible to achieve the QoS target of over 30 frames per second (FPS) by exploiting FPGA and GPGPU acceleration transparently through the managed runtime system.

Presentation Slides (CKotselidis_HeteroMREs_VEE_2017.pdf)2.74MiB

Sat 8 Apr
Times are displayed in time zone: (GMT) Azores change

14:00 - 15:30: Session 2 - GPUs, FPGAs, etc at Zhu Que Room
Chair(s): David ChisnallUniversity of Cambridge
vee-2017-Session-214:00 - 14:30
Anshuj GargIndian Institute of Technology, Bombay, Debadatta MishraIndian Institute of Technology, Bombay, Purushottam KulkarniIndian Institute of Technology, Bombay
File Attached
vee-2017-Session-214:30 - 15:00
Juan FumeroThe University of Edinburgh, Michel SteuwerThe University of Edinburgh, Lukas StadlerOracle Labs, Austria, Christophe DubachUniversity of Edinburgh
Link to publication
vee-2017-Session-215:00 - 15:30
Christos KotselidisThe University of Manchester, James ClarksonThe University of Manchester, Andrey RodchenkoThe University of Manchester, Andrew NisbetThe University of Manchester, John MawerThe University of Manchester, Mikel Luján
File Attached