1 / 11

PSO implementation on Hadoop and standalone

PSO implementation on Hadoop and standalone. Flowchart1. Inner loop. split. Initial particles (random). Split1 of particles. gbest1. Output Total gbest. Total gbest. …. …. Inner loop. split. SplitN of particles. gbestN. outer loop. Flowchart1. Inner loop. split.

butch
Download Presentation

PSO implementation on Hadoop and standalone

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. PSO implementation on Hadoop and standalone

  2. Flowchart1 Inner loop split Initial particles (random) Split1 of particles gbest1 Output Total gbest Total gbest … … Inner loop split SplitN of particles gbestN outer loop

  3. Flowchart1 Inner loop split Initial particles (random) Split1 of particles gbest1 Output Total gbest Total gbest … … Inner loop split SplitN of particles gbestN outer loop Reduce phase Map phase

  4. Flowchart2 Inner loop Pseudo randomly initialize particles Split1 of particles gbest1 Output Total gbest Total gbest … … Inner loop SplitN of particles gbestN outer loop

  5. Flowchart2 Inner loop Pseudo randomly initialize particles Split1 of particles gbest1 HDFS Output Total gbest … … Inner loop SplitN of particles gbestN outer loop (feedback total gbest) Map phase

  6. Experiment results # of lamps : 12 targets : 5 * 1 light ranks : 16 Differ_rate : 0.0001 # of splits : 4

  7. Experiment results # of lamps : 12 targets : 5 * 1 light ranks : 16 Differ_rate : 0.0001 # of splits : 8

  8. Experiment results # of lamps : 396 targets : 90 * 33 light ranks : 16 Differ_rate : 0.0001 # of splits : 4

  9. Experiment results # of lamps : 396 targets : 90 * 33 light ranks : 16 Differ_rate : 0.0001 # of splits : 8

  10. Exchange of particles • Assume that we have an example: # of splits is 4, # of particles in each split is 2500, and we assign 2500/2(ideal) particles to exchange between splits. Under this condition , each split is responsible for emitting(pseudo randomly) 1250/4 particles to exchange. Constraints: # of particles in each split ≥ (# of splits -1)* # of splits *2

  11. Exchange of particles ID0[0…103] ID0[104…207] ID0 ID0[208…311] ID1[0…103] ID1[104…207] ID1 ID1[208…311] ID2[0…103] ID2[104…207] ID2 ID2[208…311] ID3[0…103] ID3[104…207] ID3 ID3[208…311] ID3[0…103],ID2[104…207],ID1[208…311] …… ……

More Related