
Academic Year:  2012/3 
Owning Department/School:  Department of Mathematical Sciences 
Credits:  6 
Level:  Masters UG & PG (FHEQ level 7) 
Period: 
Semester 2 
Assessment:  CW 100% 
Supplementary Assessment:  MA50177 Mandatory extra work (where allowed by programme regulations) 
Requisites:  
Description:  Aims: To teach an understanding and appreciation of issues arising in the computational solution of challenging scientific and engineering problems. Learning Outcomes: Students should be able to write code to solve efficiently a range of scientific problems. They should be able to analyse algorithm complexity and efficiency. They should be familiar with scientific libraries and parallel programming. They will be expected to have deep knowledge of at least one challenging application. Skills: Efficient solution of realworld problems using scientific computing (T, A); parallel programming (T, A). Content: Units, complexity, analysis of algorithms, benchmarks. Floating point arithmetic. Programming in Fortran90. Makefiles. Data structures, full and sparse matrices. BLAS and LAPACK libraries. Visualisation. Parallel Computation: principles, message passing model, MPI, parallel data structures, scheduling on clusters, performance indicators. Other libraries/software on the web: NAG Library, Netlib, GAMS, ScaLAPACK, ARPACK, PETSc, hypre. Linking with other languages such as C, C++. Case studies illustrating the lectures will be chosen from the topics: numerical PDEs (iterative methods, multigrid, preconditioning), adaptive refinement, quadrature, eigenvalue problems (nuclear reactor criticality computations, power method, subspace iteration, AUTO), nonlinear equations and bifurcation (nonlinear thermal conduction, Newtontype methods), optimisation, networks and graphs (graph drawing, clustering, Google's pagerank algorithm). 
Programme availability: 
MA50177 is Compulsory on the following programmes:Department of Mathematical Sciences
