Go to Dana Petcu's homepageDANA PETCU'S LECTURE DESCRIPTIONS:
For: PhD students, Semester 1
Lectures: 2h/week
What is grid computing. Its benefits. Grid applications. Architecture and standards: SOA, SOAP, OGSA, OGSI, WSDL, WSRF. Globus components. MDS, GRIS, GRAM, GIIS, GASS, RSL, GridFTP. Getting started with developments in C++. Programming examples using Java. Grid service development: specifying, coding, building, packing, deploying, testing. Major features of grid services: factory, service data elements, life cycle, notification. Designing grid applications. Application examples: lottery, small blue, hello-world. Case study: a bulletin service application. Developing a portal. Overview of grid computing products and tools. Special issues: grid security, data management, information and workload virtualization. Grid projects in research and industry. Labs with Globus Toolkit 4
For: Graduate students in Distributed and Parallel Computing, Semester 2
Lectures: 2h/week Labs: 1h/week
Hardware organization of a parallel computer. Why parallel computing.Architectural classification. Theory of parallel computing: performancemeasurements, paradigms and models -- shared memory and distributed memory.Inter-connection networks and message passing. Parallel algorithms: buildingparallel codes and examples -- sorting, linear algebra. Labs with PVM and MPI.
For: Undergarduate students in Computer Science, Computers-Mathematics, Applied Mathematics Semester 7 Technology of Information Semester 5
Lectures: 2h/week Labs: 2h/week
Geometry of visualization techniques: projections, 3D transformations,visualization coordinate system. Drawing basic graphical elements: theprinciples of incremental drawing with applications to lines, circles, planecurves, spatial curves, polynomial surfaces. Clipping. Models of 3D objects.Rendering: algorithms for visible lines and surface drawing, illumination,shadows, filling, textures, fractals, colors. Ray tracing. Animation. Labs withOpenGL, VRML and PovRay.
For: Undergarduate students in Computer Science, Semester 5 Technology of Information, Semester 5
Lectures: 2h/week Labs: 2h/week
Classification. Short history of mathematical software. Scientific modeling,Software design. Numerical software: numerical analysis and numerical dataprocessing, numerical problems, errors, available and reusable software.Computer Algebra Systems: evaluation, data types, limitations. Expert systemsand problem solving environments. Educational software. Labs with Maple, Matlaband MathCad.
For: Graduate students in Distributed and Parallel Computing, Semester 1
Lectures: 2h/week Labs: 1h/week
Requests addressed to a distributed system. Properties and services. Networks.Distributed algorithms: measuring time, leader election, synchronization, faulttolerance, broadcast and multicast, agreement, distributed transactions,recovery, replication, distributed model of shared memory. Distributedoperating systems, security, remote call procedures, remote method invocation.Clusters and metacomputers. Labs with Java, Corba and DCOM.