The design and analysis of a cache architecture for texture mapping
Proceedings of the 24th annual international symposium on Computer architecture
Prefetching in a texture cache architecture
HWWS '98 Proceedings of the ACM SIGGRAPH/EUROGRAPHICS workshop on Graphics hardware
Resample hardware for 3D graphics
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Computer and Robot Vision
SIGGRAPH '83 Proceedings of the 10th annual conference on Computer graphics and interactive techniques
Media Processing Applications on the Imagine Stream Processor
ICCD '02 Proceedings of the 2002 IEEE International Conference on Computer Design: VLSI in Computers and Processors (ICCD'02)
Graphics for the masses: a hardware rasterization architecture for mobile phones
ACM SIGGRAPH 2003 Papers
Fast image segmentation and smoothing using commodity graphics hardware
Journal of Graphics Tools - Special on hardware-accelerated rendering techniques
iPACKMAN: high-quality, low-complexity texture compression for mobile phones
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Efficient video decoding on GPUs by point based rendering
GH '06 Proceedings of the 21st ACM SIGGRAPH/EUROGRAPHICS symposium on Graphics hardware
High-quality mipmapping texture compression with alpha maps for graphics processing units
IEEE Transactions on Multimedia
IEEE Transactions on Multimedia
Variable bit rate GPU texture decompression
EGSR'11 Proceedings of the Twenty-second Eurographics conference on Rendering
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In order to increase the capability of mobile GPUs in image/video processing, a multi-purpose configurable filtering unit (CFU), which is a new configurable unit for image filtering on stream processing architecture, is proposed in this paper. CFU is located in the texture unit of a GPU and can efficiently execute many kinds of filtering operations by directly accessing multi-bank texture cache and specially-designed data-paths. The following programmabilities are supported in our proposed CFU. First, different sampling point windows can be selected by programmers. Besides, the arithmetic type of the filter can be chosen. Not only original texture filtering functions and finite impulse response (FIR) filters, morphological operations in computer vision are also embedded in CFU. Furthermore, the weighting coefficients of FIR filters and morphological operations can be defined by programmers. Simulation results show that in average, compared with conventional texture unit, 25.35% of processing time in H.264/AVC motion compensation and 58.6% of processing time in video segmentation can be reduced with the assistance of CFU.