1) gHull - http://www.comp.nus.edu.sg/~tants/gHull.html

- They haven't released the source code till now.

3) Graham Scan algorithm for convex hull also seemed quite popular for parallelizing

- Chris Harrison's page on the same algorithm is helpful; also has a sequential-version source-code.

4) Mathematica's page on CUDA convex hulls

5) Optimal Multi-Core Convex Hull

Among most of the above algorithms I think that QuickHull is the most amenable for parallelization.

- They haven't released the source code till now.

2) Parallelizing Two Dimensional Convex Hull on NVIDIA GPU and Cell BE, by IIIT Hydrabad folks.

- They specifically focus on CUDA.

3) Graham Scan algorithm for convex hull also seemed quite popular for parallelizing

- Chris Harrison's page on the same algorithm is helpful; also has a sequential-version source-code.

4) Mathematica's page on CUDA convex hulls

5) Optimal Multi-Core Convex Hull

6) Doing QuickHull on GPU - NVIDIA research summit poster here

- That's a research paper.

- Source Code: No idea

Among most of the above algorithms I think that QuickHull is the most amenable for parallelization.

Why didn't you mentioned the CUDA HULL algrithm. It achieves up to 40 times acceleration to QuickHull?

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