Graph partitioning is the process of dividing a graph into smaller groups, with edges between the groups representing connections in the original graph. This reduction can make analysis and problem-solving easier. It is a challenging problem with applications in various fields, including scientific computing and circuit design. Two common examples of graph partitioning are minimum cut and maximum cut problems.
UC Berkeley
Spring 2020
The course addresses programming parallel computers to solve complex scientific and engineering problems. It covers an array of parallelization strategies for numerical simulation, data analysis, and machine learning, and provides experience with popular parallel programming tools.
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