| Code: | PRODEI027 | Acronym: | CP |
| Keywords | |
|---|---|
| Classification | Keyword |
| OFICIAL | Science and Technology Programming |
| Active? | Yes |
| E-learning page: | https://moodle.fe.up.pt/ |
| Responsible unit: | Department of Informatics Engineering |
| Course/CS Responsible: | Doctoral Program in Informatics Engineering |
| Acronym | No. of Students | Study Plan | Curricular Years | Credits UCN | Credits ECTS | Contact hours | Total Time |
|---|---|---|---|---|---|---|---|
| PRODEI | 2 | Syllabus | 1 | - | 6 | 54 | 162 |
BACKGROUND
Parallel and distributed computing is becoming the computing paradigm as hardware tends to multi-processing units. The common desktop is today built with multicore processors that collectively have more processing power, than the single core processor, but cores are individually less powerful. Programmers will have to deal with multiprocessor architectures in order to use effectively the machines of today and of the future.
AIMS
Acquisition of useful knowledge to develop parallel programs. Construction of solid basis in parallel architectures, algorithms parallelization, programming models, synchronization of processes and performance measures by the development of programs.
Scientific component:50%
Technological component:50%
Students should be able to: a) Analyze a problem and identify the adequate parallelization model (Knowledge and Understanding) b) Write message-passing and shared memory programs (Engineering Analysis, Engineering Practice) c) Design parallel solutions for new problems (Engineering Design) d) Use computational models to estimate applications computation time (Investigations) e) knowledge of process concurrency and best practices to implement resource sharing (Transferable skills).
Students should had completed successfully the programming subjects of the 1st and 2nd year.
INTRODUCTION: - Distributed and parallel programming, parallel machines, processors, memory organization.
PARALLEL PROGRAMMING FUNDAMENTALS: Problem Division, Communication Patterns, Synchronization, Granularity of Parallelization, Staggering (distribution of work by the processors)
MULTI-PROCESSOR PROGRAMMING: - Message passing programming with MPI - Shared memory programming with OpenMP - Data Parallel programming with GPUs.
CHARACTERIZATION OF PARALLEL COMPUTING: Execution Models, Programming Models, Computing Models, Efficiency and performance Measures, Expansivity (Isoefficiency Function).
INTRODUCTION TO DISTRIBUTED COMPUTING IN INTERNET ENVIRONMENT: P2P, GRID, CLOUD COMPUTING. Application characteristics.
Theoretical classes: exposition of the subject matter with presentation and discussion of examples. Theoretical-practical classes: problem solving and discussion, including the development of some programs.
| Description | Type | Time (hours) | Weight (%) | End date |
|---|---|---|---|---|
| Attendance (estimated) | Participação presencial | 42,00 | 10,00 | |
| Lab work and reports for evaluation | Defesa pública de dissertação, de relatório de projeto ou estágio, ou de tese | 60,00 | 70,00 | 2013-06-07 |
| Lab work | Trabalho laboratorial | 20,00 | 20,00 | 2013-06-07 |
| Total: | - | 100,00 |
| Description | Type | Time (hours) | End date |
|---|---|---|---|
| Personal study | Estudo autónomo | 40 | 2013-06-07 |
| Total: | 40,00 |
Concluding and presenting the programming assignments.
Final Grade= 0.1*P + 0.2*CW + 0.7(0.5*R1 + 0.5*R2)
P - Attendance
CW - class work
R1 - Report 1
R2 - Report 2
The programming assignments are mandatory and must be worked out and presented along the semester.
The programming assignments can only be improved in the course next instance.
Fluency in C/C++ programming is required.