Page 34 - REC :: M.E. CSE Curriculum and Syllabus - R2019

CP19P14 PARALLEL ALGORITHMS Category L T P C
PE 3 0 0 3

Objectives:
⚫ To understand different parallel architectures and models of computation.
⚫ To introduce the various classes of parallel algorithms.
⚫ To study parallel algorithms for basic problems.

UNIT-I INTRODUCTION 9
Need for Parallel Processing – Data and Temporal Parallelism – Models of Computation – RAM and PRAM Model –
Shared Memory and Message Passing Models- Processor Organizations – PRAM Algorithm – Analysis of PRAM
Algorithms- Parallel Programming Languages.
PRAM ALGORITHMS: Parallel Algorithms for Reduction – Prefix Sum – List Ranking –Preorder Tree Traversal –
Searching -Sorting – Merging Two Sorted Lists – Matrix Multiplication – Graph Coloring – Graph Searching.

UNIT-II SEQUENTIAL MODEL 9
LMCC, Hypercube, Cube Connected Cycle, Butterfly, Perfect Shuffle Computers, Tree model, Pyramid model, Fully
Connected model, PRAM-CREW, EREW models, simulation of one model from another one.
Performance Measures of Parallel Algorithms, speed-up and efficiency of PA, Cost- optimality, An example of
illustrate Cost- optimal algorithms- such as summation, Min/Max on various models.

UNIT-III SIMD ALGORITHMS 9
2D Mesh SIMD Model – Parallel Algorithms for Reduction – Prefix Computation – Selection – Odd-Even Merge
Sorting – Matrix Multiplication, Hypercube SIMD Model – Parallel Algorithms for Selection- Odd-Even Merge Sort-
Bitonic Sort- Matrix Multiplication Shuffle Exchange SIMD Model – Parallel Algorithms for Reduction -Bitonic
Merge Sort – Matrix Multiplication – Minimum Cost Spanning Tree

UNIT-IV MIMD AND SEARCHING ALGORITHMS 9
UMA Multiprocessor Model -Parallel Summing on Multiprocessor- Matrix Multiplication on Multiprocessors and
Multicomputer – Parallel Quick Sort – Mapping Data to Processors.
Parallel Searching Algorithm, Kth element, Kth element in X+Y on 8 PRAM, Parallel Matrix Transportation and
Multiplication Algorithm on PRAM, MCC, Vector-Matrix Multiplication, Solution of Linear Equation, Root finding.

UNIT-V SORTING AND GRAPH ALGORITHMS 9
Parallel Sorting: Networks, Parallel Merging Algorithms on, CREW/EREW/MCC, Parallel Sorting Networks
CREW/EREW/MCC/, linear array.
Graph Algorithms - Connected Graphs, search and traversal, Combinatorial Algorithms-Permutation, Combinations,
Derrangements.
Total Contact Hours : 45

Course Outcomes:
Upon completion of the course, students will be able to
⚫ Develop parallel algorithms for standard problems and applications.
Analyze efficiency of different parallel algorithms.
⚫
Understand SIMD architecture and its applications
⚫
Implement MIMD and searching Algorithms
⚫
Perform Sorting using Graph Theory
⚫

Reference Books(s) / Web links:
1 Michael J. Quinn, “Parallel Computing: Theory & Practice”, Tata McGraw Hill Edition, Second edition, 2017.
2 M.J. Quinn, “Designing Efficient Algorithms for Parallel Computer”, McGrawHill.
Ellis Horowitz, Sartaj Sahni and Sanguthevar Rajasekaran, “Fundamentals of Computer Algorithms”,
3
University press, Second edition, 2011.
4 V. Rajaraman, C Siva Ram Murthy,“Parallel computers- Architecture and Programming”, PHI learning, 2016.