Scientific Computing on Supercomputers II

'Vectorization, Optimization and Supercomputer Architecture.- Abstract.- 1. The architecture of vector computers.- 2. Arithmetic operations, memory bandwidth and memory access.- 3. Data structures and the design of algorithms.- 4. Matrix multiplication and related problems.- 5. Red-black SOR and diagonal storing of matrices.- 6. The linear first order recurrence.- 7. Generation of random numbers.- 8. Supercomputer software independent of a special architecture.- 9. Concluding remarks.- 10. References.- Vectorization of Some General Purpose Algorithms.- Abstract.- I. Introduction.- II. The vector concept in Fortran-200.- III. Main vector extensions in Fortran-200.- III.A. Vector variables and vector assignments.- III.A.1. Explicit vector reference.- III.A.2. Implicit vector reference.- III.A.3. Vector functions.- III.B. Vector flow control.- IV. Intrinsic functions.- IV.A. Scalar functions with scalar arguments.- IV.B. The intrinsic V-functions.- IV.C. The intrinsic Q8-functions.- IV.C.1. Initialization of a vector.- IV.C.2. Extracting scalar information from vectors.- IV.C.3. Extracting vector information from vectors.- IV.C.4. Reversion, compression, expansion, merging, ... of vectors.- IV.C.5. Gather and scatter operations.- V. Practical examples.- V.A. Integration with equally-spaced abscissas.- V.B. Gaussian quadrature.- V.C. Chebychev approximation.- Conclusion.- References.- ASTRID: a Programming Environment for Scientific Applications on Parallel Vector Computers.- Abstract.- 1. Introduction.- 2. Organization of ASTRID.- 2.1. Application modules.- 2.2. Special characteristics.- Hardware environment.- Subdomain decomposition.- Structured meshing.- Adaptive mesh refinement.- 3. ASTRID command language.- 3.1. User interface.- 3.2. Command syntax.- Lne syntax.- Keywords.- Attributes.- Comments.- Procedures.- Macro lines.- Constants.- Variables and expressions.- Control statements.- Scripts.- 3.2. Database commands.- 4. MiniM: mini-modeller to define the geometry.- 4.1. Create database objects.- 4.2. Modify database objects.- 4.3. Remove database objects.- 5. CASE: interface to define physical quantities.- 5.1. Analysis directives.- 5.2. Boundary conditions.- 5.3. Material constants.- 6. Mesh: numerical mesh.- 6.1. Autoadaptive mesh.- 6.2. Mesh one subdomain.- 6.3. Mesh all subdomains.- 7. Solve: solves the problem.- 7.1. Construction of the matrix and right hand side.- 7.2. Direct matrix solver.- 7.3. Iterative matrix solvers.- 8. BASPL: graphics system.- 8.1. Fundamental remarks.- 8.2. Functionalities of BASPL.- 9. Application: distribution of electrical contacts.- 9.1. The physical problem.- 9.2. MiniM.- 9.3. CASE.- 9.4. SOLVE.- 9.5. Numerical results.- 9.6. BASPL.- Acknowledgments.- References.- Large Scale Computations in Solid State Physics.- I. Introduction.- II. Numerical procedures.- 1. Matrix diagonalization.- 1.1. The recursive method.- 1.2. The RMS-DIIS method.- 2. Iterative solution of the self-consistent matrix.- 2.1. Simple iterations.- 2.2. Mixing procedures.- 2.3. An improved iteration scheme.- III. Summary of the results.- IV. Acknowledgment.- Appendix A: the density functional theory.- Appendix B: the pseudopotential theory and plane wave expansion.- References.- Could User-friendly Supercomputers be Designed?.- Abstract.- 1. Introduction.- 2. The requirements for a supercomputer in engineering sciences.- 2.1. Performance and balanced system.- 2.2. Data transfer operations.- 2.3. Scalar performance.- 2.4. Programming language.- 2.5. Summary of requirements.- 3. Parallel architectures.- 4. The continuous pipe vector computer (CPVC).- 4.1. Memory bandwidth.- 4.2. Local and extended memory.- 4.3. Number of pipes.- 4.4. Memory organization.- 4.5. Pipe switch and delay register.- 4.6. Building blocks and marketing considerations.- 4.7. Fail-safe system.- 4.8. The continuous pipe.- 4.9. Vector dependencies.- 4.10.