scholarly journals LU-GPU: Efficient Algorithms for Solving Dense Linear Systems on Graphics Hardware

2005 ◽  
Author(s):  
N. Galoppo ◽  
N.K. Govindaraju ◽  
M. Henson ◽  
D. Manocha
Keyword(s):  
Linear Systems ◽  
Efficient Algorithms ◽  
Graphics Hardware

Efficient Bitmap Resemblance Under Translations

1997 ◽  
Vol 07 (01n02) ◽  
pp. 57-74
Author(s):  
Klara Kedem ◽  
Daniel Cohen
Keyword(s):  
Approximation Algorithm ◽  
Hausdorff Distance ◽  
Efficient Algorithms ◽  
Graphics Hardware ◽  
Point Sets ◽  
The Third ◽  
Speed Up

We present three efficient algorithms for resemblance between two bitmaps. Two of the algorithms are rasterized approximations, based on existing algorithms which compute the exact minimum Hausdorff distance between point sets under translation. The minimum Hausdorff distance is a min – max – min distance. We convert this operation into an and – or – and operation. This conversion, together with the fact that we encode distances into bits in the words of the pixel plane, of standard graphics hardware, contribute to the speed-up of our rasterized algorithms. The third algorithm is faster than the first two rasterized algorithms, and combines speed-up ideas from both. The performance of our rasterized algorithm is compared to an existing rasterized approximation algorithm for bitmap resemblance. We compare runtimes of these algorithms, parametrized by the size of the bitmap, the density of black bits in the bitmap and other parameters. Our results are summarized in tables and show that our algorithm is faster.

Tidal Flow: A Fast and Teachable Maximum Flow Algorithm

2018 ◽  
Vol 12 ◽  
pp. 25-41
Author(s):  
Matthew C. FONTAINE
Keyword(s):  
Computer Science ◽  
Tidal Flow ◽  
Maximum Flow ◽  
Efficient Algorithms ◽  
Science Students ◽  
Flow Algorithm ◽  
Maximum Flows

Among the most interesting problems in competitive programming involve maximum flows. However, efficient algorithms for solving these problems are often difficult for students to understand at an intuitive level. One reason for this difficulty may be a lack of suitable metaphors relating these algorithms to concepts that the students already understand. This paper introduces a novel maximum flow algorithm, Tidal Flow, that is designed to be intuitive to undergraduate andpre-university computer science students.

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