C++ for Scientists - Technische Universität Dresden

More documents

Recommendations

Info

16 CHAPTER 1. GOOD AND BAD SCIENTIFIC SOFTWARE than C ++. Yes, C ++ can look like this if one puts enough effort in good software. Evidently, it is also much easier to write algorithms at this abstraction level than expressing it with low-level operations. The Purpose of Scienfic Software Scientists shall do science. Excellent scientific software is expressed only in mathematical and domainspecific operations without any technical detail exposed. At this abstraction level, scientists can focus on models and algorithms, being much more productive and progress scientific discovery. Nobody knows how many scientists wasting how much time every year dwelling on small technical details of bad software like in Listing 1.1. Of course, the technical details have to be realized in some place but not in a scientific application. This is the worst possible location. Use a two-level approach: write your applications in terms of expressive mathematical operations and if they do not exist, implement them separately. These mathematical operations must be carefully implemented for maximal performance or use other operations with maximal performance. Investing time in the performance of these fundamental operations is highly rentable because the functions will be reused very often. Advise Use the right abstractions! If they do not exist, implement them. Speaking of abstractions, the CG implementation in Listing 1.2 does not commit to any technical detail. In no place, the function is restricted to a numerical type like double. It works as well for float, GNU’s multiprecision, complex, interval arithmetic, quaternions, . . . The matrix A can have any internal format, as long as it can be multiplied with a vector it can be used in the function. In fact, it does not even need to be matrix but can be any linear operator. For instance, an object that performs a Fast Fourier Transformation (FFT) on a vector can be used as A when the FFT is expressed by a product of A with the vector. Similarly, the vectors do not need to be represented by finite-dimensional arrays but can be elements of any vector space that is somehow computer-representable as long as all operations in the algorithm can be performed. We are also open to other computer architectures. If the matrix and the vectors are distributed over the nodes of a parallel supercomputer and according parallel operations are available, the functions runs in parallel without changing any single line. (GP)GPU acceleration can be also realized within the data structures and their operations without changing the algorithm. In
general, any existing or new platform that is supported in the operations of the matrix and vector types is also supported by our ‘Generic’ conjugate gradient function. As mentioned before, we do not even need to change it. If we have a sophisticated scientific application of several thousand lines (not 100,000s) written with appropriate abstractions, we need to modify it either. Starting with the next chapter, we will explain you how to write good scientific software. 17
Page 1 and 2: Technische Universität Dresden Fak
Page 3 and 4: Contents I Understanding C++ 7 Intr
Page 5 and 6: CONTENTS 5 10.5 Unix and Linux . .
Page 7: Part I Understanding C ++ 7
Page 10 and 11: 10 C ++ was not a reliable computer
Page 12 and 13: 12 CHAPTER 1. GOOD AND BAD SCIENTIF
Page 20 and 21: 20 CHAPTER 2. C++ BASICS • std::c
Page 22 and 23: 22 CHAPTER 2. C++ BASICS In the fir
Page 24 and 25: 24 CHAPTER 2. C++ BASICS int main (
Page 26 and 27: 26 CHAPTER 2. C++ BASICS Operator A
Page 28 and 29: 28 CHAPTER 2. C++ BASICS The bitwis
Page 30 and 31: 30 CHAPTER 2. C++ BASICS cast (type
Page 32 and 33: 32 CHAPTER 2. C++ BASICS complicate
Page 34 and 35: 34 CHAPTER 2. C++ BASICS } else if
Page 36 and 37: 36 CHAPTER 2. C++ BASICS eps/= 2.0;
Page 38 and 39: 38 CHAPTER 2. C++ BASICS for (...;
Page 40 and 41: 40 CHAPTER 2. C++ BASICS 2.6.1 Inli
Page 42 and 43: 42 CHAPTER 2. C++ BASICS To make su
Page 44 and 45: 44 CHAPTER 2. C++ BASICS float divi
Page 46 and 47: 46 CHAPTER 2. C++ BASICS The first
Page 48 and 49: 48 CHAPTER 2. C++ BASICS #ifndef at
Page 50 and 51: 50 CHAPTER 2. C++ BASICS float A[7]
Page 52 and 53: 52 CHAPTER 2. C++ BASICS Encapsulat
Page 54 and 55: 54 CHAPTER 2. C++ BASICS As a pract
Page 56 and 57: 56 CHAPTER 2. C++ BASICS A function
Page 58 and 59: 58 CHAPTER 2. C++ BASICS Now that t
Page 60 and 61: 60 CHAPTER 2. C++ BASICS we need sm
Page 62 and 63: 62 CHAPTER 2. C++ BASICS 2.12 Exerc
Page 64 and 65: 64 CHAPTER 2. C++ BASICS 2.13 Opera
Page 66 and 67:
66 CHAPTER 3. CLASSES apply symm bl
Page 68 and 69:
68 CHAPTER 3. CLASSES int main() {
Page 70 and 71:
70 CHAPTER 3. CLASSES class solver
Page 72 and 73:
72 CHAPTER 3. CLASSES • Compilers
Page 74 and 75:
74 CHAPTER 3. CLASSES a real number
Page 76 and 77:
76 CHAPTER 3. CLASSES } return ∗t
Page 78 and 79:
78 CHAPTER 3. CLASSES This mechanis
Page 80 and 81:
80 CHAPTER 3. CLASSES One could not
Page 82 and 83:
82 CHAPTER 3. CLASSES class matrix
Page 84 and 85:
84 CHAPTER 3. CLASSES Approach 3: R
Page 86 and 87:
86 CHAPTER 3. CLASSES of the decrem
Page 88 and 89:
88 CHAPTER 3. CLASSES There are two
Page 90 and 91:
90 CHAPTER 4. GENERIC PROGRAMMING }
Page 92 and 93:
92 CHAPTER 4. GENERIC PROGRAMMING c
Page 94 and 95:
94 CHAPTER 4. GENERIC PROGRAMMING A
Page 96 and 97:
96 CHAPTER 4. GENERIC PROGRAMMING v
Page 98 and 99:
98 CHAPTER 4. GENERIC PROGRAMMING c
Page 100 and 101:
100 CHAPTER 4. GENERIC PROGRAMMING
Page 102 and 103:
Page 104 and 105:
Page 106 and 107:
Page 108 and 109:
Page 110 and 111:
Page 112 and 113:
Page 114 and 115:
Page 116 and 117:
Page 118 and 119:
Page 120 and 121:
Page 122 and 123:
Page 124 and 125:
Page 126 and 127:
Page 128 and 129:
Page 130 and 131:
Page 132 and 133:
Page 134 and 135:
134 CHAPTER 5. META-PROGRAMMING exp
Page 136 and 137:
136 CHAPTER 5. META-PROGRAMMING dou
Page 138 and 139:
138 CHAPTER 5. META-PROGRAMMING We
Page 140 and 141:
140 CHAPTER 5. META-PROGRAMMING Fir
Page 142 and 143:
142 CHAPTER 5. META-PROGRAMMING hig
Page 144 and 145:
144 CHAPTER 5. META-PROGRAMMING The
Page 146 and 147:
146 CHAPTER 5. META-PROGRAMMING tra
Page 148 and 149:
148 CHAPTER 5. META-PROGRAMMING tem
Page 150 and 151:
150 CHAPTER 5. META-PROGRAMMING 5.3
Page 152 and 153:
152 CHAPTER 5. META-PROGRAMMING •
Page 154 and 155:
154 CHAPTER 5. META-PROGRAMMING Dis
Page 156 and 157:
156 CHAPTER 5. META-PROGRAMMING };
Page 158 and 159:
158 CHAPTER 5. META-PROGRAMMING A s
Page 160 and 161:
160 CHAPTER 5. META-PROGRAMMING ass
Page 162 and 163:
162 CHAPTER 5. META-PROGRAMMING num
Page 164 and 165:
164 CHAPTER 5. META-PROGRAMMING Usi
Page 166 and 167:
166 CHAPTER 5. META-PROGRAMMING } v
Page 168 and 169:
168 CHAPTER 5. META-PROGRAMMING The
Page 170 and 171:
170 CHAPTER 5. META-PROGRAMMING onl
Page 172 and 173:
172 CHAPTER 5. META-PROGRAMMING for
Page 174 and 175:
174 CHAPTER 5. META-PROGRAMMING } u
Page 176 and 177:
176 CHAPTER 5. META-PROGRAMMING } r
Page 178 and 179:
Page 180 and 181:
180 CHAPTER 5. META-PROGRAMMING } t
Page 182 and 183:
Page 184 and 185:
184 CHAPTER 5. META-PROGRAMMING Com
Page 186 and 187:
186 CHAPTER 5. META-PROGRAMMING tem
Page 188 and 189:
188 CHAPTER 6. INHERITANCE { } std:
Page 190 and 191:
190 CHAPTER 6. INHERITANCE 6.4.1 Ca
Page 192 and 193:
192 CHAPTER 6. INHERITANCE dbp= sta
Page 194 and 195:
194 CHAPTER 6. INHERITANCE Our comp
Page 196 and 197:
196 CHAPTER 6. INHERITANCE Another
Page 198 and 199:
198 CHAPTER 6. INHERITANCE
Page 200 and 201:
200 CHAPTER 7. EFFECTIVE PROGRAMMIN
Page 202 and 203:
Page 204 and 205:
Page 206 and 207:
Page 208 and 209:
Page 210 and 211:
Page 212 and 213:
Page 214 and 215:
Page 216 and 217:
Page 218 and 219:
Page 220 and 221:
Page 222 and 223:
Page 225 and 226:
Finite World of Computers Chapter 8
Page 227 and 228:
8.2. MORE NUMBERS AND BASIC STRUCTU
Page 229 and 230:
8.2. MORE NUMBERS AND BASIC STRUCTU
Page 231 and 232:
8.4. THE OTHER WAY AROUND 231 As ca
Page 233 and 234:
How to Handle Physics on the Comput
Page 235 and 236:
Programming tools Chapter 10 In thi
Page 237 and 238:
10.2. DEBUGGING 237 T& glas::contin
Page 239 and 240:
10.3. VALGRIND 239 Stepi and Nexti
Page 241 and 242:
10.5. UNIX AND LINUX 241 • top: l
Page 243 and 244:
C ++ Libraries for Scientific Compu
Page 245 and 246:
11.3. BOOST.BINDINGS 245 • Math a
Page 247 and 248:
11.3. BOOST.BINDINGS 247 #include
Page 249 and 250:
11.4. MATRIX TEMPLATE LIBRARY 249 c
Page 251 and 252:
11.7. GEOMETRIC LIBRARIES 251 11.7.
Page 253 and 254:
Real-World Programming Chapter 12 1
Page 255 and 256:
12.1. TRANSCENDING LEGACY APPLICATI
Page 257 and 258:
12.1. TRANSCENDING LEGACY APPLICATI
Page 259 and 260:
Parallelism Chapter 13 13.1 Multi-T
Page 261 and 262:
13.2. MESSAGE PASSING 261 int main
Page 263 and 264:
Numerical exercises Chapter 14 In t
Page 265 and 266:
14.1. COMPUTING AN EIGENFUNCTION OF
Page 267 and 268:
Page 269 and 270:
Page 271 and 272:
Page 273 and 274:
14.3. THE SOLUTION OF A SYSTEM OF D
Page 275 and 276:
14.4. GOOGLE’S PAGE RANK 275 Taki
Page 277 and 278:
14.5. THE BISECTION METHOD FOR FIND
Page 279 and 280:
14.6. THE NEWTON-RAPHSON METHOD FOR
Page 281 and 282:
14.7. SEQUENTIAL NOISE REDUCTION OF
Page 283 and 284:
14.7. SEQUENTIAL NOISE REDUCTION OF
Page 285 and 286:
Programmierprojekte Kapitel 15 Die
Page 287 and 288:
15.6. MATRIX-SKALIERUNG 287 Siehe h
Page 289 and 290:
15.10. ANWENDUNG MTL4 AUF TYPEN MIT
Page 291 and 292:
Acknowledgement Chapter 16 Special
Page 293:
Bibliography [AG04] David Abrahams
show all

C++ for Scientists - Technische Universität Dresden

Create successful ePaper yourself

Delete template?

Save as template?