PPT-A Parallel Linear Solver for Block

Circulant Linear Systems with Applications to Acoustics Suzanne Shontz University of Kansas Ken Czuprynski University of Iowa John Fahnline Penn State EECS 739 Scientific Parallel Computing. Unlike sequential algorithms parallel algorithms cannot be analyzed very well in isolation One of our primary measures of goodness of a parallel system will be its scalability Scalability is the ability of a parallel system to take advantage of incr Parents as well as students will be made aware of this help for our students Students will be encouraged to attend to get the extra help they may need Schedule is on School Calendar Whenever possibl e we will schedule Homerooms during one of our Wed 1 Introduction to linear block codes Recall the example from the last time of a code we had some generator matrix some parity check matrix and a means of doing some decoding We will generalize these ideas A block code is a code in which bits or more Multiphysics. HPC Applications . CS267 . – Spring 2013. John Shalf. With contributions from: . Gabrielle Allen, Tom . Goodale. , Eric . Schnetter. , Ed Seidel (AEI/LSU). Phil . Colella. , Brian Van . Circulant. Linear Systems with Applications to Acoustics. Suzanne Shontz, University of Kansas . Ken . Czuprynski. , University of . Iowa. John . Fahnline. , Penn State. EECS 739: Scientific Parallel Computing. Week 3. Day 3. Reflecting on Practice. Metacognition. Develop a common understanding of what metacognition is. How do we find evidence for it in our students’ behaviors?. Merging Ideas. Our Definition. BJ Furman. 14NOV2011. The Plan for Today. Solver. Review. Non-linear regression analysis. Aerospace engineering computation using a spreadsheet. Macros and VBA programming. Learning Objectives. Use Solver to solve mathematical equations. for Incompressible and Compressible Flows . with Cavitation. Sunho . Park. 1. , Shin Hyung Rhee. 1. , and . Byeong. . Rog. Shin. 2. 1 . Seoul National . University, . 2 . Changwon. National . University. Dr. Ron Lembke. Formulating in Excel. Write the LP out on paper, with all constraints and the objective function.. Decide on cells to represent variables.. Enter coefficients of each variable in each constraint in a block of cells.. An optimization problem is a problem in which we wish to determine the best values for decision variables that will maximize or minimize a performance measure subject to a set of constraints. A feasible solution is set of values for the decision variables which satisfy all of the constraints. Dr Susan Cartwright. Dept of Physics and Astronomy. University of Sheffield. Parallel Universes. Are you unique?. Could there be another “you” differing only in what you had for breakfast this morning?. Numerical integration of smooth and non-smooth Dynamics. Time Integration in Chrono. Two classes of time stepping methods in Chrono. Time steppers for smooth dynamics. Classical multibody dynamics – rigid and flexible connected through joints. BJ Furman. 14NOV2011. The Plan for Today. Solver. Review. Non-linear regression analysis. Aerospace engineering computation using a spreadsheet. Macros and VBA programming. Learning Objectives. Use Solver to solve mathematical equations. Belos. . . 2011 . Trilinos. User Group Meeting . November 1st, 2011. Chris Baker. David . Day. Mike . Heroux. . Mark . Hoemmen. Rich . Lehoucq. Mike Parks. Heidi Thornquist (Lead). Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, .