 | Study programme 2017-2018 | Français | |
 | High performance and cloud computing | ||
Programme component of Master's Degree in Computer Science à la Faculty of Science |
| Code | Type | Head of UE | Department’s contact details | Teacher(s) |
|---|---|---|---|---|
| US-M1-INFO60-006-M | Compulsory UE | MANNEBACK Pierre | F114 - Informatique |
|
| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Credits | Weighting | Term |
|---|---|---|---|---|---|---|---|---|---|
| Anglais | 18 | 18 | 12 | 0 | 0 | 3 | 3 | 1st term |
| AA Code | Teaching Activity (AA) | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term | Weighting |
|---|---|---|---|---|---|---|---|---|
| I-INFO-009 | High performance and cloud computing | 18 | 18 | 12 | 0 | 0 | Q1 | 100.00% |
| Programme component |
|---|
Objectives of Programme's Learning Outcomes
- Have acquired highly specialised and integrated knowledge and broad skills in the various disciplines of computer science, which come after those within the Bachelor's in computer science.
- Carry out development or innovation projects in IT.
- Apply, mobilise, articulate and promote the knowledge and skills acquired in order to contribute to the achievement of a development or innovation project.
- Master the complexity of such work and take into account the objectives and constraints which characterise it.
- Apply scientific methodology.
- Critically reflect on the impact of IT in general, and on the contribution to projects.
Learning Outcomes of UE
Master parallel algorithmic and programing, in shared memory and distributed memory environments. Implement GPU accelerators and knwo how to deploy an application on a Cloud.
Content of UE
Course on Parallel and Distributed Computing, High Performance Computing and Cloud Computing. <strong>GPU programming</strong> Exploitation of Multi-CPU-GPU Architectures. Application for Multimedia processing.Multi-CPU/Multi-GPU based image processing. Multi-GPU based video processing in Real Time. Multi-CPU/Multi-GPU based framework for HD image and video processing Experimental Results <strong>Cloud computing </strong> Cloud computing architecture Cloud components Deployment models Service models Cloud storage Cloud supports Cloud security Cloud advantages Cloud uses cases Demonstration : Cloud-based image and video processing platform
Prior Experience
Real time Computing. C++ Programming.
Type of Assessment for UE in Q1
- Oral examination
Q1 UE Assessment Comments
Exam on Computer with oral questions on the courseware and similar exercices than those of practical sesssions. (parallelize a given sequential program using OpenMP and/or MPI and/or GPU programming. Deployement on Cloud.
Type of Assessment for UE in Q3
- Oral examination
Q3 UE Assessment Comments
idem Q1
Type of Resit Assessment for UE in Q1 (BAB1)
- N/A
Q1 UE Resit Assessment Comments (BAB1)
Not applicable
Type of Teaching Activity/Activities
| AA | Type of Teaching Activity/Activities |
|---|---|
| I-INFO-009 |
|
Mode of delivery
| AA | Mode of delivery |
|---|---|
| I-INFO-009 |
|
Required Reading
| AA | Required Reading |
|---|---|
| I-INFO-009 |
Required Learning Resources/Tools
| AA | Required Learning Resources/Tools |
|---|---|
| I-INFO-009 | Not applicable |
Recommended Reading
| AA | Recommended Reading |
|---|---|
| I-INFO-009 |
Recommended Learning Resources/Tools
| AA | Recommended Learning Resources/Tools |
|---|---|
| I-INFO-009 | Not applicable |
Other Recommended Reading
| AA | Other Recommended Reading |
|---|---|
| I-INFO-009 | M. McCool, A.D. Robinson, J. Reinders, Structured Parallel Programming, Morgan Kaufmann, 2012. L.R. Scott, T. Clark, B.Bagheri, Scientific parallel computing, Princeton Univ. Press, 2005. |
Grade Deferrals of AAs from one year to the next
| AA | Grade Deferrals of AAs from one year to the next |
|---|---|
| I-INFO-009 | Authorized |