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

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

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

Distributed Multigrid for Processing Huge Spherical Images

Michael KazhdanJohns Hopkins University

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 equationChallenge:At 3.3 billion pixels, thesystem size is 90 GB

Solution‡:With a streaming solver, weget a solution in 88 minuteswith a peak memory of 408MB

‡Kazhdan and Hoppe, 2008

Streaming Multigrid for Processing Large Images

Digitized Sky Survey

1790 individual 529-megapixel plates One terapixel image

Challenge:At one trilllion pixels, we would need:

27 TB of disk space26,000 minutes120 GB of memory

Streaming Poisson Solvers for Large Image Processing

Solution:With a distributed solver we can split thestorage, memory, and computation.

Distributed, Streaming Multigrid for Processing Huge Image

CPU 1 CPU 2 ... CPU P

Spherical Image Processing

Parameterize the sphere over a regular 2D domain andsolve the Poisson equation over the 2D domain

Challenges:1] Extrinsic Approach: does not accountfor distortion due to the parameterization. 2] Intrinsic Approach: defines a systemthat is inhomogenous and difficult to solve.

Solutions:1] Extrinsic Approach: choose a mapping to a2D domain that is less distorting. [Kunszt et al.] 2] Intrinsic Approach: adapt the system toaccount for the in-homogeneity.

Hierarchical structure enables the use of multigrid solvers

N

S

N

A D

B CG F

H E

N

S S

S S

Distributed, Streaming Multigrid for Processing Huge Spherical Images

2

2

2sin

1sin

sin

12

ff

fS

2

2

2

2

y

f

x

ff

dd sin

dydx

Conclusion

We will explore the implementation of distributed and streamingsolvers 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