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Enhancing Machine Learning Speed with CUDA Barnes-Hut Implementation

This presentation outlines the use of CUDA for Barnes-Hut implementation to accelerate machine learning algorithms. We discuss the problem statement, deficiencies in prior art, our proposed solution, simulation results versus conventional methods, and improvement in execution time. The conclusion highlights the benefits of using CUDA for machine learning tasks and suggests future work for optimization.

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Enhancing Machine Learning Speed with CUDA Barnes-Hut Implementation

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Presentation Transcript

  1. Title (for ECE570 Final Project) • Who you are, etc.

  2. Outline of presentation • Problem Statement • Prior Art and their deficiencies • Solution: CUDA implementation of Barnes-Hut • Simulation results vs. conventional • Stride length improvement vs. execution time • Conclusion • Future Work

  3. Problem Statement • We need faster machine learning algorithm on blah • Previous ways: • Algortihm-1 • Algorithm-2 • DVFS

  4. Your Proposed Solution (what you did) • We propose using MapReduce for Algorithm-1 to improve efficiency • Dfgd • Sdf

  5. What things are novel/interesting

  6. Results-1 (proof of design)

  7. Results2 (proof of design)

  8. Disucssion/Conclusion (future work)

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