Parallel Algorithms

Semester:
8th
Course Type:
Elective Specialization courses (ΠΜ-E)
Track:
CS (Computer Science)
Code:
ΘΠ19
ECTS:
6
TEACHING HOURS per week
Theory:
3
Seminar:
1
Laboratory:
-
Specializations
Foundations of Computer Science (S1):
-
Data and Knowledge Management (S2):
-
Software (S3):
-
Hardware and Architecture (S4):
-
Communications and Networking (S5):
-
Signal and Information Processing (S6):
-
Related Courses
Prerequisites:
-
Expected Prior Knowledge:
Detailed Description
DIT_PPS_ΘΠ19-Parallel Algorithms.pdf
Course Content

The course introduces the concept of design and analysis of parallel numerical and non numerical algorithms. In particular, covers the following subjects:

Part Ι : Parallel Non Numerical Algorithms. Introductory concepts, Parallel Architectures, Methods of design and development of Parallel Algorithms, Efficiency of Parallel algorithms, Parallel Selection, Parallel Merge, Parallel Sorting and Searching, Parallel Graph Algorithms, Parallel Algorithms of Computational Geometry.

Part II : Parallel numerical algorithms. Introductory concepts, Parallel matrix computations (parallel transpose of a matrix, parallel matrix vector multiplication, parallel matrix multiplication), Parallel direct methods for solving linear systems (parallel Gaussian Elimination, parallel Gauss-Jordan, parallel Huard, Parallel LU, parallel WZ), Parallel Iterative methods for solving linear systems with application to the solution of Partial Differential equations (Red-Black SOR, multicolor SOR, Local SOR), Parallel methods for computing the eigenpair of a matrix. Systolic algorithms.

LITERATURE AND STUDY MATERIALS - READING LIST
  1. Pantziou G, Mamalis B and Tomaras A., Introduction to Parallel Computing, New Technologies Publ., 2013.
  2. Gene H. Golub, Charles F. Van Loan, Theory and Matrix Computations, John Hopkins University Press, 2015 (translated in greek, Pedio Publ.).
e-Class link
Parallel Algorithms - ECLASS