Internal:GPU Usage: Difference between revisions

From crtc.cs.odu.edu
Jump to navigation Jump to search
← Older edit
Spyridon97 (talk | contribs)
CNF, external, internal
2,385 edits
m Spyridon97 moved page PODM Refactoring to Internal:PODM Refactoring
Spyridon97 (talk | contribs)
CNF, external, internal
2,385 edits
 
(2 intermediate revisions by the same user not shown)
Line 1: Line 1:
=Code Changes=
# Choose a specific C++ coding style✔
# Use C++17 standard✔
# Remove the CGAL library by replacing its predicates with the following one which is way faster: (TODO)
## Benchmark: [https://crtc.cs.odu.edu/Internal:4D_Predicates_Benchmark PCK vs CGAL Predicates Benchmark]
## Paper: [https://hal.inria.fr/hal-01225202 Predicate Construction Kit Paper]
## Code:  [https://gforge.inria.fr/frs/?group_id=5833 Predicate Construction Kit Code]
# Remove Boost library by replacing its threads with std::thread (ask Christos for Barrier). (TODO)
# Update ITK to the newest version (TODO)
# Keep only useful Defines
## For PODM3D✔
## For PODM4D✔
=Abstractions=
# Combine 3D and 4D PODM versions into one abstract program, in which the user will choose what he wants to use.
## Create namespaces for each PODM which will help to create a templated PODM wrapper✔
## Template the common code of each PODM for 3-4 dimensions (or even more or less) (TODO)
# Decouple Contentions managers and Load Balancing from the Meshing Procedure (TODO)
# Add PDR (TODO)
# Add Smoothing (TODO)
=Explore Usage of GPU=
=Explore Usage of GPU=
# For “itkSignedMaurerParallelDistanceMapImageFilter” code:
# For “itkSignedMaurerParallelDistanceMapImageFilter” code:

Latest revision as of 16:20, 30 April 2020

Explore Usage of GPU

  1. For “itkSignedMaurerParallelDistanceMapImageFilter” code:
    1. Understand the code by reading the Parallel N-Dimensional Exact Signed Euclidean Distance Transform paper
    2. Study if it’s beneficial to convert it in order to use GPUs. See the papers:
      1. A Multigrain Delaunay Mesh Generation Method for Multicore SMT-based Architectures, (TODO)
      2. Algorithm, Software, and Hardware Optimizations for Delaunay Mesh Generation on Simultaneous Multithreaded Architectures (TODO)
  2. For Predicates:
    1. Based on ACCELERATING THE EXACT EVALUATION OF GEOMETRIC PREDICATES WITH GPUS (TODO)
    2. Based on GPredicates - GPU Implementation of Robust and Adaptive Floating-Point Predicates for Computational Geometry (TODO)
Retrieved from "https://crtc.cs.odu.edu/index.php?title=Internal:GPU_Usage&oldid=5806"