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Mobile clusters of single board computers: an option for providing resources to student projects and researchers.

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Parallel image computation in clusters with task-distributor.

Christian Baun1

  • 1Frankfurt University of Applied Sciences, Nibelungenplatz 1, 60318 Frankfurt am Main, Germany.

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Summary

This study presents task-distributor, a free software for parallel ray tracing on clusters using Persistence Of Vision Raytracer (POV-Ray). It enables efficient distributed computing without modifying source code or adding libraries, aiding cluster benchmarking.

Keywords:
Cluster computingMaster–worker schemePOV-RayPerformanceSpeedup

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Area of Science:

  • Computer Science
  • Parallel Computing
  • Distributed Systems

Background:

  • Ray tracing is computationally intensive and memory-demanding.
  • Distributed systems, particularly clusters, offer potential for parallelizing ray tracing tasks.
  • Benchmarking cluster performance can be achieved through computationally expensive tasks like ray tracing.

Purpose of the Study:

  • Introduce task-distributor, a novel free software solution.
  • Enable parallel execution of ray tracing tasks on distributed systems.
  • Facilitate cluster benchmarking through efficient parallel computation.

Main Methods:

  • Utilized Persistence Of Vision Raytracer (POV-Ray) for ray tracing.
  • Developed task-distributor for parallel task execution without source code modification.
  • Did not require additional message passing libraries (e.g., MPI, PVM).

Main Results:

  • Task-distributor successfully enabled parallel ray tracing on distributed systems.
  • The software achieved parallel image computation without altering POV-Ray.
  • Analysis of runtime revealed the impact of problem size and hardware on parallel application scaling.

Conclusions:

  • Task-distributor provides an accessible solution for parallel ray tracing.
  • The software simplifies the process of leveraging distributed systems for ray tracing.
  • Performance analysis offers insights into parallel application scalability in distributed environments.