Global illumination using photon maps
Proceedings of the eurographics workshop on Rendering techniques '96
Improved Query Matching Using kd-Trees: A Latent Semantic Indexing Enhancement
Information Retrieval
Using k-d Trees to Improve the Retrieval Step in Case-Based Reasoning
EWCBR '93 Selected papers from the First European Workshop on Topics in Case-Based Reasoning
Photon mapping on programmable graphics hardware
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
KD-tree acceleration structures for a GPU raytracer
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Realistic Image Synthesis Using Photon Mapping
Realistic Image Synthesis Using Photon Mapping
Photon Mapping Parallel Based on Shared Memory System
CGIV '09 Proceedings of the 2009 Sixth International Conference on Computer Graphics, Imaging and Visualization
Accelerating the photon mapping algorithm and its hardware implementation
ASAP '11 Proceedings of the ASAP 2011 - 22nd IEEE International Conference on Application-specific Systems, Architectures and Processors
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Photon mapping is a kind of rendering techniques which enables depicting complicated light concentrations for 3D graphics. Searching kd-tree of photons with k-near neighbor search (k-NN) requires a large amount of computations. As k-NN search includes high degree of parallelism, the operation can be accelerated by GPU and recent multi-core microprocessors. However, memory access bottleneck will limit their computation speed. Here, as an alternative approach, an FPGA implementation of k-NN search operation in kd-tree is proposed. In the proposed design, we maximized the effective throughput of the block RAM by connecting multiple Query Modules to both ports of RAM. Furthermore, an implementation of the discovery process of the max distance which is not depending on the number of Estimate-Photons is proposed. Through the implementation on Spartan6, Virtex6 and Virtex7, it appears that 26 fundamental modules can be mounted on Virtex7. As a result, the proposed module achieved the throughput of approximately 282 times as that of software execution at maximum.