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Distributed Multigrid for Processing Huge Spherical Images Michael Kazhdan Johns Hopkins University.

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Presentation on theme: "Distributed Multigrid for Processing Huge Spherical Images Michael Kazhdan Johns Hopkins University."— Presentation transcript:

1 Distributed Multigrid for Processing Huge Spherical Images Michael Kazhdan Johns Hopkins University

2 Solution Streaming Pass 1 Streaming Pass 2 Constraints Poisson Solvers for Large Image Processing 3.3 Gigapixels composited from 643 photographsFitting a scalar field to gradients by solving the Poisson equation Challenge : At 3.3 billion pixels, the system size is 90 GB Solution ‡ : With a streaming solver, we get a solution in 88 minutes with a peak memory of 408MB ‡ Kazhdan and Hoppe, 2008 Streaming Multigrid for Processing Large Images

3 Digitized Sky Survey 1790 individual 529-megapixel plates  One terapixel image Challenge : At one trilllion pixels, we would need: 27 TB of disk space 26,000 minutes 120 GB of memory Streaming Poisson Solvers for Large Image Processing Solution : With a distributed solver we can split the storage, memory, and computation. Distributed, Streaming Multigrid for Processing Huge Image CPU 1CPU 2... CPU P

4 Spherical Image Processing Parameterize the sphere over a regular 2D domain and solve the Poisson equation over the 2D domain Challenges : 1] Extrinsic Approach: does not account for distortion due to the parameterization. 2] Intrinsic Approach: defines a system that is inhomogenous and difficult to solve. Solutions : 1] Extrinsic Approach: choose a mapping to a 2D domain that is less distorting. [Kunszt et al.] 2] Intrinsic Approach: adapt the system to account for the in-homogeneity. Hierarchical structure enables the use of multigrid solvers N S N A D BC GF H E N SS SS Distributed, Streaming Multigrid for Processing Huge Spherical Images

5 Conclusion We will explore the implementation of distributed and streaming solvers capable of processing planar and spherical imagery. Distributed, Streaming Multigrid for Processing Huge Spherical Images Computational Scope : Processing terapixel imagery on large networked clusters Processing gigapixel imagery on multi-core machines Processing megapixel imagery on the GPU. Theoretical Scope : Solve the homogenous Poisson equation Incorporate non-trivial boundary conditions Extend to inhomogenous systems via alg. multigrid Empirical Scope : Image processing Video processing Level sets Incompressible fluids Atmospherical dynamics


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