'Data decomposition' presentation slideshows

Multi-Tasking Models and Algorithms

Multi-Tasking Models and Algorithms. General Concepts (Part I). Outline for Multi-Tasking Models. Note : Items in black are in this slide set (Part I). Preliminaries Common Decomposition Methods Characteristics of Tasks and Interactions Mapping Techniques for Load Balancing

909 views • 77 slides

Lecture 2 The Art of Concurrency

1.2k views • 64 slides

Principles of Parallel Algorithm Design

Principles of Parallel Algorithm Design. Introduction to Parallel Algorithms Decomposition Techniques Characteristics of Tasks and Interactions Mapping Techniques for Load Balancing Methods for Minimizing Interaction Overheads Parallel Algorithm Design Models.

870 views • 62 slides

John Cavazos Dept of Computer & Information Sciences University of Delaware

John Cavazos Dept of Computer & Information Sciences University of Delaware www.cis.udel.edu/~cavazos/cisc879. Lecture 5 Patterns for Parallel Programming. Lecture 5: Overview. Writing a Parallel Program Design Patterns for Parallel Programs Finding Concurrency Algorithmic Structure

713 views • 59 slides

What is ESMF and what does it mean to adopt it?

What is ESMF and what does it mean to adopt it?. NCAR/LANL CCSM. Climate. Data Assimilation. GFDL FMS Suite. NASA GMAO Analysis. GMAO Seasonal Forecast. Weather. MITgcm. 3 rd ESMF Community Meeting Cecelia DeLuca cdeluca@ucar.du Nancy Collins nancy@ucar.edu

329 views • 32 slides

The Model Coupling Toolkit and the CCSM Next-Generation Coupler (NGC)

384 views • 27 slides

Productivity T ools for Scientific Computing

Productivity T ools for Scientific Computing. Python & ECLIPSE. akhilap@iisc.ac.in. HPC workflow. Data preparation Data decomposition Write a job script with appropriate parameters (nodes, cores per node) Submit the job to the queue Verify job run status

226 views • 22 slides

Paper_topic: Parallel Matrix Multiplication using Vertical Data

Paper_topic: Parallel Matrix Multiplication using Vertical Data. Decomposition, Tasks, and Dependency Graphs. The 1 st step in developing a parallel algorithm: decompose the problem into tasks that can execute concurrently

113 views • 11 slides

The Idea in a Nutshell

The Idea in a Nutshell . Classify a new item based on the classes of its k nearest neighbors. Sensitivity to k distance metric how the k points contribute to the decision . Computational Challenges. Distance metric needs to be tuned (e.g., parameter scaling).

124 views • 3 slides