'Pthreads' presentation slideshows

GraphLab A New Framework for Parallel Machine Learning

GraphLab A New Framework for Parallel Machine Learning. Yucheng Low Aapo Kyrola Carlos Guestrin. Joseph Gonzalez Danny Bickson Joe Hellerstein. Exponential Parallelism. Exponentially Increasing Parallel Performance. Exponentially Increasing Sequential Performance.

769 views • 54 slides

443 views • 32 slides

Co-processing SPMD Computation on GPUs and CPUs with MapReduce Interface on Shared Memory System

625 views • 32 slides

Venkatram Ramanathan

Venkatram Ramanathan. Parallelizing a Co-Clustering Application with a Reduction Based Framework on Multi-Core Clusters. Motivation Evolution of Multi-Core Machines and the challenges Background: MapReduce and FREERIDE Co-clustering on FREERIDE Experimental Evaluation Conclusion.

307 views • 23 slides

Evaluation and Optimization of a Titanium Adaptive Mesh Refinement

Evaluation and Optimization of a Titanium Adaptive Mesh Refinement. Amir Kamil Ben Schwarz Jimmy Su. Adaptive Mesh Refinement. AMR uses hierarchy of grids, with fine grids nested inside coarse ones. Grids are refined only where extra resolution is needed.

127 views • 12 slides

Relevance of Thread Model to E mbedded and RT Systems

Relevance of Thread Model to E mbedded and RT Systems. Bina Ramamurthy bina@buffalo.edu. Topics. Reference : https :// computing.llnl.gov/tutorials/pthreads Process space vs thread space When to use threads ? Some examples in using threads: Pthread

171 views • 6 slides

Simple but slow: O(n 2 ) algorithms

Simple but slow: O(n 2 ) algorithms. Serial Algorithm Algorithm compares each particle with every other particle and checks for the interaction radius Most comparisons are outside interaction range as shown in figure OpenMP , Pthreads

130 views • 5 slides