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Title: Wavelet Transforms using VTK-m

Abstract

These are a set of slides that deal with the topics of wavelet transforms using VTK-m. First, wavelets are discussed and detailed, then VTK-m is discussed and detailed, then wavelets and VTK-m are looked at from a performance comparison, then from an accuracy comparison, and finally lessons learned, conclusion, and what is next. Lessons learned are the following: Launching worklets is expensive; Natural logic of performing 2D wavelet transform: Repeat the same 1D wavelet transform on every row, repeat the same 1D wavelet transform on every column, invoke the 1D wavelet worklet every time: num_rows x num_columns; VTK-m approach of performing 2D wavelet transform: Create a worklet for 2D that handles both rows and columns, invoke this new worklet only one time; Fast calculation, but cannot reuse 1D implementations.

Authors:
 [1];  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
OSTI Identifier:
1329546
Report Number(s):
LA-UR-16-27385
DOE Contract Number:  
AC52-06NA25396
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; Computer Science

Citation Formats

Li, Shaomeng, and Sewell, Christopher Meyer. Wavelet Transforms using VTK-m. United States: N. p., 2016. Web. doi:10.2172/1329546.
Li, Shaomeng, & Sewell, Christopher Meyer. Wavelet Transforms using VTK-m. United States. doi:10.2172/1329546.
Li, Shaomeng, and Sewell, Christopher Meyer. Tue . "Wavelet Transforms using VTK-m". United States. doi:10.2172/1329546. https://www.osti.gov/servlets/purl/1329546.
@article{osti_1329546,
title = {Wavelet Transforms using VTK-m},
author = {Li, Shaomeng and Sewell, Christopher Meyer},
abstractNote = {These are a set of slides that deal with the topics of wavelet transforms using VTK-m. First, wavelets are discussed and detailed, then VTK-m is discussed and detailed, then wavelets and VTK-m are looked at from a performance comparison, then from an accuracy comparison, and finally lessons learned, conclusion, and what is next. Lessons learned are the following: Launching worklets is expensive; Natural logic of performing 2D wavelet transform: Repeat the same 1D wavelet transform on every row, repeat the same 1D wavelet transform on every column, invoke the 1D wavelet worklet every time: num_rows x num_columns; VTK-m approach of performing 2D wavelet transform: Create a worklet for 2D that handles both rows and columns, invoke this new worklet only one time; Fast calculation, but cannot reuse 1D implementations.},
doi = {10.2172/1329546},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Sep 27 00:00:00 EDT 2016},
month = {Tue Sep 27 00:00:00 EDT 2016}
}

Technical Report:

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