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1 - 10 of 24 results for: CME ; Currently searching spring courses. You can expand your search to include all quarters

CME 104: Linear Algebra and Partial Differential Equations for Engineers (ENGR 155B)

Linear algebra: matrix operations, systems of algebraic equations, Gaussian elimination, undetermined and overdetermined systems, coupled systems of ordinary differential equations, eigensystem analysis, normal modes. Fourier series with applications, partial differential equations arising in science and engineering, analytical solutions of partial differential equations. Numerical methods for solution of partial differential equations: iterative techniques, stability and convergence, time advancement, implicit methods, von Neumann stability analysis. Examples and applications from various engineering fields. Prerequisite: CME 102/ ENGR 155A.
Terms: Spr | Units: 5 | UG Reqs: GER:DB-Math, WAY-FR
Instructors: Khayms, V. (PI)

CME 104A: Linear Algebra and Partial Differential Equations for Engineers, ACE

Students attend CME104/ENGR155B lectures with additional recitation sessions; two to four hours per week, emphasizing engineering mathematical applications and collaboration methods. Prerequisite: application at: http://soe.stanford.edu/current_students/edp/programs/ace.html
Terms: Spr | Units: 6 | UG Reqs: GER:DB-Math, WAY-FR
Instructors: Khayms, V. (PI)

CME 192: Introduction to MATLAB

This short course runs for the first three weeks of the quarter and is offered each quarter during the academic year. It is highly recommended for students with no prior programming experience who are expected to use MATLAB in math, science, or engineering courses. It will consist of interactive lectures and application-based assignments.nnThe goal of the short course is to make students fluent in MATLAB and to provide familiarity with its wide array of features. The course covers an introduction of basic programming concepts, data structures, and control/flow; and an introduction to scientific computing in MATLAB, scripts, functions, visualization, simulation, efficient algorithm implementation, toolboxes, and more.
Terms: Win, Spr | Units: 1

CME 194: Introduction to MPI

This short course runs for the first three weeks of the spring quarter.nnIt is recommended for students who would like to learn the basic theory andnnpractice of developing scientific software for clusters and supercomputers.nnIdeally students will already be familiar with C or C++, but no prior parallelnnprogramming experience is required. The course will focus on many of thennfundamental concepts behind (distributed-memory) parallel programming, such asnndata dependency graphs, communication cost models, collective communicationnnalgorithms, and network topologies. This hands-on course will focus on nnprogramming via the Message Passing Interface (MPI), but hybrid programmingnnmodels (e.g., MPI+OpenMP and MPI+CUDA) will also be discussed.
Terms: Spr | Units: 1

CME 206: Introduction to Numerical Methods for Engineering (AA 214A, ME 300C)

Numerical methods from a user's point of view. Lagrange interpolation, splines. Integration: trapezoid, Romberg, Gauss, adaptive quadrature; numerical solution of ordinary differential equations: explicit and implicit methods, multistep methods, Runge-Kutta and predictor-corrector methods, boundary value problems, eigenvalue problems; systems of differential equations, stiffness. Emphasis is on analysis of numerical methods for accuracy, stability, and convergence. Introduction to numerical solutions of partial differential equations; Von Neumann stability analysis; alternating direction implicit methods and nonlinear equations. Prerequisites: CME 200/ ME 300A, CME 204/ ME 300B.
Terms: Spr | Units: 3

CME 213: Introduction to parallel computing using MPI, openMP, and CUDA (ME 339)

This class will give hands on experience with programming multicore processors, graphics processing units (GPU), and parallel computers. Focus will be on the message passing interface (MPI, parallel clusters) and the compute unified device architecture (CUDA, GPU). Topics will include: network topologies, modeling communication times, collective communication operations, parallel efficiency, MPI, dense linear algebra using MPI. Symmetric multiprocessing (SMP), pthreads, openMP. CUDA, combining MPI and CUDA, dense linear algebra using CUDA, sort, reduce and scan using CUDA. Pre-requisites include: C programming language and numerical algorithms (solution of differential equations, linear algebra, Fourier transforms).
Terms: Spr | Units: 3

CME 213B: Parallel Computing Group Projects

Students in groups of up to four will discuss, devise and implement a cluster/GPU parallel application for a discipline of mutual interest. Instructors will help guide students to relevant literature and resources. Prerequisites: Current or previous enrollment in CME 213 or equivalent background.

CME 291: Master's Research

Students require faculty sponsor. (Staff)
Terms: Aut, Win, Spr, Sum | Units: 1-5 | Repeatable for credit

CME 306: Numerical Solution of Partial Differential Equations (MATH 226)

Terms: Spr | Units: 3
Instructors: Ying, L. (PI)

CME 308: Stochastic Methods in Engineering (MATH 228)

Review of basic probability; Monte Carlo simulation; state space models and time series; parameter estimation, prediction, and filtering; Markov chains and processes; stochastic control; and stochastic differential equations. Examples from various engineering disciplines. Prerequisites: exposure to probability; background in real variables and analysis.
Terms: Spr | Units: 3
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