victorjcarolino / K-Means_Clustering

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K-Means

Execution Data

https://docs.google.com/spreadsheets/d/1ZcLFo0Y49qIlUCRqSpkb2Dtbx0JHtt5JW1wI-EmIYKQ/edit?usp=sharing

Description

Kmeans-Serial

  • Base code provided and referenced from https://github.com/marcoscastro/kmeans
  • Keeps track of:
    • points + what cluster they are in
    • clusters + what points are in them
  • Does the summation and mean of the cluster means at the end of each point association

Better-Kmeans-Serial

  • Updated code from the aforementioned reference
  • Keeps track of:
    • points + what cluster they are in
    • clusters + the intermediate sums from point addition and removal
  • Does the summation of points to the mean as points are iterated
    • Mean is computed sequentially at the end

Kmeans-Parallel

  • Parallelized code from the Better-Kmeans-Serial
  • Parallelization is done over the points rather than over the clusters due to a greater chance of sufficient parallel slack
  • Data contention is handled through the use of thread local storage
  • Keeps track of:
    • points + what cluster they are in
    • clusters + the intermediate sums from point addition and removal
    • thread local storage handles the summation of point additions and the number of points added to a cluster as well as the cluster switches made by points
  • The thread local storage resolves the intermediate sums to the appropriate cluster and resolves the addition or removal of points to ensure proper calculation of the mean

Datasets

  • Apple Quality
    • K: 8
    • Total Points: 3999
    • Total Features: 7
  • Beans
    • K: 17
    • Total Points: 13611
    • Total Features: 16
  • Big One
    • K: 32
    • Total Points: 100000
    • Total Features: 3
  • Birch
    • K: 100
    • Total Points: 87996
    • Total Features: 2
  • Gaussian Distribution
    • K: 9
    • Total Points: 10125
    • Total Features: 15
  • HW Set 1
    • K: 2
    • Total Points: 7
    • Total Features: 2
  • HW Set 2
    • K: 3
    • Total Points: 150
    • Total Features: 4
  • Pulsar
    • K: 2
    • Total Points: 17898
    • Total Features: 8

Running

  • To execute the program:
    • run: sh run.sh datasets/[dataset-name].txt [output-subdirectory]
    • the outputs of the execution will be found in:
      • serial: outputs/[output-subdirectory]/kmeans-serial.txt
      • better serial: outputs/[output-subdirectory]/better-kmeans-serial.txt
      • parallel: outputs/[output-subdirectory]/kmeans-parallel.txt

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