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The Design and Analysis of Parallel Algorithms by Justin R. Smith full ebook and pdf notes download
Neeraj Yadav

The Design and Analysis of Parallel Algorithms by Justin R. Smith full ebook and pdf notes download

Neeraj Yadav | 07-Apr-2016 |
Basic Concepts , Models of parallel computation , Distributed-Memory Models , Examples of Existing Parallel Computers , Numerical Algorithms , A Survey of Symbolic Algorithms , Probabilistic Algorithms ,

Hi friends, here Neeraj Yadav uploaded notes for Parallel Algorithms with title The Design and Analysis of Parallel Algorithms by Justin R. Smith full ebook and pdf notes download. You can download this lecture notes, ebook by clicking on the below file name or icon.

Contents


Chapter 1. Basic Concepts 1
1. Introduction 1
Chapter 2. Models of parallel computation 13
1. Generalities 13
2. Sorting on an EREW-SIMD PRAM computer 18
3. Bitonic Sorting Algorithm 19
4. Appendix: Proof of the 0-1 Principal 24
5. Relations between PRAM models 25
5.1. Complexity Classes and the Parallel Processing Thesis 29
5.2. P-Completeness and Inherently Sequential Problems 37
5.3. Further reading. 41
5.4. Brent’s Theorem 42
5.5. SIMD Algorithms 44
5.5.1. Doubling Algorithms 44
5.5.2. The Brent Scheduling Principle. 45
5.5.3. Pipelining. 46
5.5.4. Divide and Conquer. 46
5.6. MIMD Algorithms 46
5.6.1. Generalities 46
5.6.2. Race-conditions 47
5.6.3. Optimization of loops 51
5.6.4. Deadlocks 52
5.7. Comparison of the SIMD and MIMD models of computation 53
Chapter 3. Distributed-Memory Models 57
1. Introduction. 57
2. Generic Parallel Algorithms. 57
3. The Butterfly Network. 61
3.1. Discussion and further reading 66
3.2. Description 67
3.3. Discussion and further reading. 76
4. Cube-Connected Cycles 77
5. Dataflow Computers 84
Chapter 4. Examples of Existing Parallel Computers 95
1. Asynchronous Parallel Programming 95
1.1. Portable Programming Packages 95
1.1.1. Linda 95
1.1.2. p4 99
1.1.3. MPI 99
1.2. Automatically Parallelizing Compilers 100
2. Discussion and further reading 100
3. SIMD Programming: the Connection Machine 101
3.1. Generalities 101
3.2. Algorithm-Design Considerations 103
3.3. The C* Programming Language 103
3.3.1. Running a C* program. 109
3.4. Semantics of C* 109
3.4.1. Shapes and parallel allocation of data. 109
3.4.2. Action of the with-statement 110
3.4.3. Action of the where-statement. 111
3.4.4. Parallel Types and Procedures. 114
3.4.5. Special Parallel Operators. 117
3.4.6. Sample programs. 117
3.4.7. Pointers. 121
3.4.8. Subtleties of Communication. 122
3.4.9. Collisions. 123
3.5. A Critique of C* 126
4. Programming a MIMD-SIMD Hybrid Computer: Modula* 128
4.1. Introduction. 128
4.2. Data declaration. 129
4.2.1. Elementary data types. 129
4.2.2. Parallel data types. 129
4.3. The FORALL Statement. 130
4.3.1. The asynchronous case. 131
4.3.2. The synchronous case. 131
4.4. Sample Programs 134
4.5. A Critique of Modula* 135
Chapter 5. Numerical Algorithms 137
1. Linear algebra 137
1.1. Matrix-multiplication 137
1.2. Systems of linear equations 137
1.2.1. Generalities on vectors and matrices 138
1.2.2. Appendix: Diagonalization of Hermitian Matrices 147
1.2.3. The Jacobi Method 151
1.2.4. The JOR method 154
1.2.5. The SOR and Consistently Ordered Methods 157
1.2.6. Discussion 163
1.3. Power-series methods: the Pan-Reif Algorithm 165
1.3.1. Introduction. 165
1.3.2. The main algorithm 167
1.3.3. Proof of the main result 170
1.4. Nonlinear Problems 173
1.5. A Parallel Algorithm for Computing Determinants 174
1.6. Further reading 178
2. The Discrete Fourier Transform 178
2.1. Background 178
2.2. Definition and basic properties 182
2.3. The Fast Fourier Transform Algorithm 186
2.4. Eigenvalues of cyclic matrices 197
3. The JPEG Algorithm 200
4. Wavelets 201
4.1. Background 201
4.2. DiscreteWavelet Transforms 208
4.3. Discussion and Further reading 220
5. Numerical Evaluation of Definite Integrals 222
5.1. The one-dimensional case. 222
5.2. Higher-dimensional integrals 227
5.3. Discussion and Further reading. 230
6. Partial Differential Equations 232
6.1. Elliptic Differential Equations 233
6.1.1. Basic concepts 233
6.1.2. Self-adjoint equations 242
6.1.3. Rate of convergence 244
6.2. Parabolic Differential Equations 250
6.2.1. Basic Methods 250
6.2.2. Error Analysis 252
6.2.3. Implicit Methods 255
6.2.4. Error Analysis 259
6.3. Hyperbolic Differential Equations 261
6.3.1. Background 261
6.3.2. Finite differences 262
6.4. Further reading 265
Chapter 6. A Survey of Symbolic Algorithms 267
1. Doubling Algorithms 267
1.1. General Principles 267
1.2. Recurrence Relations 273
1.3. Deterministic Finite Automata 275
1.4. Parallel Interpolation 278
2. The Euler Tour Algorithm 282
2.1. Parallel Tree Contractions 289
2.2. Shortest Paths 290
2.3. Connected Components 293
2.3.1. Algorithm for a CREW Computer 294
2.3.2. Algorithm for a CRCW computer 301
2.4. Spanning Trees and Forests 305
2.4.1. An algorithm for an inverted spanning forest 311
2.5. Minimal Spanning Trees and Forests 315
2.6. Cycles in a Graph 327
2.6.1. Definitions 327
2.6.2. A simple algorithm for a cycle basis 328
2.6.3. Lowest Common Ancestors 329
2.7. Further Reading 331
3. Parsing and the Evaluation of arithmetic expressions 333
3.1. Introduction 333
3.2. An algorithm for building syntax-trees 334
3.3. An algorithm for evaluating a syntax tree 338
3.4. Discussion and Further Reading 344
3.5. Appendix: Parenthesis-matching algorithm 348
3.6. Parallel searching 348
3.7. Sorting Algorithms for a PRAM computer 349
3.7.1. The Cole Sorting Algorithm — CREW version 349
3.7.2. Example 356
3.7.3. The Cole Sorting Algorithm — EREW version 361
3.8. Detailed proof of the correctness of the algorithm 376
3.9. Expander Graphs 379
3.10. Introduction 382
3.11. Number-Theoretic Considerations 384
3.12. Discussion and further reading 398
Chapter 7. Probabilistic Algorithms 401
1. Introduction and basic definitions 401
1.1. Numerical algorithms 401
1.1.1. Monte Carlo Integration 401
1.2. Monte Carlo algorithms 403
1.3. Las Vegas algorithms 404
2. The class textbfRNC 405
2.1. Work-efficient parallel prefix computation 406
2.2. The Valiant and Brebner Sorting Algorithm 409
2.3. Maximal Matchings in Graphs 410
2.3.1. A Partitioning Lemma 412
2.3.2. Perfect Matchings 412
2.3.3. The General Case 415
2.4. The Maximal Independent-Set Problem 417
2.4.1. Definition and statement of results. 417
2.4.2. Proof of the main results. 421
3. Further reading 426

 

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Pankaj Yadav
07-Apr-2016

Pankaj Yadav

nice :)

Neeraj Yadav
07-Apr-2016

Neeraj Yadav

thanx

Muhammed Shafi
06-Feb-2018

Muhammed Shafi

thanx