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Design space exploration

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systematic exploration process. However, the exploration process is complex because of a variety of ways in which the same functionality can be implemented. A tradeoff analysis between each of the implementation option based on a certain parameter of interest forms the basis of DSE. The parameter of interest could vary across systems, but the commonly used parameters are power, performance, and cost. Additional factors like size, shape, weight, etc. can be important for some handheld systems like cellphone and tablets. With growing usage of mobile devices, energy is also becoming a mainstream optimization parameter along with power and performance.
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methods of DSE where the designer has to steer the tool after every iteration towards convergence. Since the exploration is a complex process which takes large computational time, researchers have developed exploration tools which can give an approximate analysis of the system behavior in a fraction of time compared to accurate analysis. Such tools are very important for quick comparison of design decisions and are becoming more important with increasing complexity of designs.
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To simplify the complexity of DSE, researchers have been continuously striving to raise the abstractions of component and system definition to be able to cater to larger and complex systems. For example, instead of modeling a digital system at transistor or gate level, there have been attempts to use
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Owing to the complexity of the exploration process, researchers have proposed automated DSE where the exploration software is able to take decisions and comes up with the optimal solution. However, it is not possible to have an automated DSE for all kind of systems and hence there are semi-automated
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Given the complex specification of electronic systems and the plethora of design choices ranging from the choice of components, number of components, operating modes of each of the components, connections between the components, choice of algorithm, etc.; design decisions need to be based on a
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RTL or behavioral modeling. Further higher abstractions like SystemC or block diagram based modeling are also used depending on the system requirements. Modeling at higher abstractions allows fast exploration of various design choices for the lower level implementation.
134:(DSE) refers to systematic analysis and pruning of unwanted design points based on parameters of interest. While the term DSE can apply to any kind of system, we refer to electronic and embedded system design in this article. 204: 258:. FOCS'10 Proceedings of the 16th Monterey conference on Foundations of computer software: modeling, development, and verification of adaptive systems. Springer-Verlag Berlin, Heidelberg. 149:
The ability to operate on the space of design candidates makes DSE useful for many engineering tasks, such as rapid prototyping, optimization, and system integration.
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provides insufficient context for those unfamiliar with the subject
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Kang, Eunsuk; Jackson, Ethan; Schulte, Wolfram (2010).
255:An approach for effective design space exploration 251: 337: 320: 230:11245.1/d91527ff-6f4c-4484-8437-7c9e38648a0b 43:. There might be a discussion about this on 327: 313: 174:Multifactor design of experiments software 228: 118:Learn how and when to remove this message 63:Learn how and when to remove this message 202: 338: 100:providing more context for the reader 279: 74: 15: 13: 14: 382: 283: 79: 20: 245: 196: 1: 189: 299:. You can help Knowledge by 7: 203:Pimentel, Andy (Feb 2017). 152: 10: 387: 278: 221:10.1109/MDAT.2016.2626445 132:Design Space Exploration 184:Randomized block design 351:Industrial engineering 295:-related article is a 209:IEEE Design & Test 361:Quantitative research 346:Design of experiments 371:Systems theory stubs 179:Probabilistic design 164:Design of experiment 33:confusing or unclear 356:Systems engineering 159:Computer experiment 96:improve the article 41:clarify the article 308: 307: 265:978-3-642-21291-8 128: 127: 120: 73: 72: 65: 378: 329: 322: 315: 287: 280: 270: 269: 249: 243: 242: 232: 200: 123: 116: 112: 109: 103: 83: 82: 75: 68: 61: 57: 54: 48: 24: 23: 16: 386: 385: 381: 380: 379: 377: 376: 375: 336: 335: 334: 333: 276: 274: 273: 266: 250: 246: 201: 197: 192: 155: 130: 124: 113: 107: 104: 93: 84: 80: 69: 58: 52: 49: 38: 25: 21: 12: 11: 5: 384: 374: 373: 368: 363: 358: 353: 348: 332: 331: 324: 317: 309: 306: 305: 288: 272: 271: 264: 244: 194: 193: 191: 188: 187: 186: 181: 176: 171: 166: 161: 154: 151: 126: 125: 87: 85: 78: 71: 70: 28: 26: 19: 9: 6: 4: 3: 2: 383: 372: 369: 367: 364: 362: 359: 357: 354: 352: 349: 347: 344: 343: 341: 330: 325: 323: 318: 316: 311: 310: 304: 302: 298: 294: 289: 286: 282: 281: 277: 267: 261: 257: 256: 248: 240: 236: 231: 226: 222: 218: 214: 210: 206: 199: 195: 185: 182: 180: 177: 175: 172: 170: 167: 165: 162: 160: 157: 156: 150: 147: 143: 139: 135: 133: 122: 119: 111: 108:February 2023 101: 97: 91: 88:This article 86: 77: 76: 67: 64: 56: 53:February 2023 46: 45:the talk page 42: 36: 34: 29:This article 27: 18: 17: 301:expanding it 290: 275: 254: 247: 215:(1): 77–90. 212: 208: 198: 148: 144: 140: 136: 131: 129: 114: 105: 94:Please help 89: 59: 50: 39:Please help 30: 366:Experiments 340:Categories 190:References 35:to readers 169:MULTICUBE 239:16297637 153:See also 293:systems 31:may be 262:  237:  291:This 235:S2CID 297:stub 260:ISBN 225:hdl 217:doi 98:by 342:: 233:. 223:. 213:34 211:. 207:. 328:e 321:t 314:v 303:. 268:. 241:. 227:: 219:: 121:) 115:( 110:) 106:( 102:. 92:. 66:) 60:( 55:) 51:( 47:. 37:.

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confusing or unclear
clarify the article
the talk page
Learn how and when to remove this message
improve the article
providing more context for the reader
Learn how and when to remove this message
Computer experiment
Design of experiment
MULTICUBE
Multifactor design of experiments software
Probabilistic design
Randomized block design
"Exploring Exploration: A Tutorial Introduction to Embedded Systems Design Space Exploration"
doi
10.1109/MDAT.2016.2626445
hdl
11245.1/d91527ff-6f4c-4484-8437-7c9e38648a0b
S2CID
16297637
An approach for effective design space exploration
ISBN
978-3-642-21291-8
Stub icon
systems
stub
expanding it
v
t
e

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