000 | 03446nam a22005535i 4500 | ||
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001 | 978-3-030-35971-3 | ||
003 | DE-He213 | ||
005 | 20220801214108.0 | ||
007 | cr nn 008mamaa | ||
008 | 200130s2020 sz | s |||| 0|eng d | ||
020 |
_a9783030359713 _9978-3-030-35971-3 |
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024 | 7 |
_a10.1007/978-3-030-35971-3 _2doi |
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050 | 4 | _aTK7867-7867.5 | |
072 | 7 |
_aTJFC _2bicssc |
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_aTEC008010 _2bisacsh |
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_aTJFC _2thema |
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_a621.3815 _223 |
100 | 1 |
_aKang, Mingu. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _936272 |
|
245 | 1 | 0 |
_aDeep In-memory Architectures for Machine Learning _h[electronic resource] / _cby Mingu Kang, Sujan Gonugondla, Naresh R. Shanbhag. |
250 | _a1st ed. 2020. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2020. |
|
300 |
_aX, 174 p. 104 illus., 65 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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505 | 0 | _aIntroduction -- The Deep In-memory Architecture (DIMA) -- DIMA Prototype Integrated Circuits -- A Variation-Tolerant DIMA via On-Chip Training -- Mapping Inference Algorithms to DIMA -- PROMISE: A DIMA-based Accelerator -- Future Prospects -- Index. | |
520 | _aThis book describes the recent innovation of deep in-memory architectures for realizing AI systems that operate at the edge of energy-latency-accuracy trade-offs. From first principles to lab prototypes, this book provides a comprehensive view of this emerging topic for both the practicing engineer in industry and the researcher in academia. The book is a journey into the exciting world of AI systems in hardware. Describes deep in-memory architectures for AI systems from first principles, covering both circuit design and architectures; Discusses how DIMAs pushes the limits of energy-delay product of decision-making machines via its intrinsic energy-SNR trade-off; Offers readers a unique Shannon-inspired perspective to understand the system-level energy-accuracy trade-off and robustness in such architectures; Illustrates principles and design methods via case studies of actual integrated circuit prototypes with measured results in the laboratory; Presents DIMA's various models to evaluate DIMA's decision-making accuracy, energy, and latency trade-offs with various design parameter. | ||
650 | 0 |
_aElectronic circuits. _919581 |
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650 | 0 |
_aCooperating objects (Computer systems). _96195 |
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650 | 0 |
_aMicroprocessors. _936273 |
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650 | 0 |
_aComputer architecture. _93513 |
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650 | 1 | 4 |
_aElectronic Circuits and Systems. _936274 |
650 | 2 | 4 |
_aCyber-Physical Systems. _932475 |
650 | 2 | 4 |
_aProcessor Architectures. _936275 |
700 | 1 |
_aGonugondla, Sujan. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _936276 |
|
700 | 1 |
_aShanbhag, Naresh R. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _936277 |
|
710 | 2 |
_aSpringerLink (Online service) _936278 |
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773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783030359706 |
776 | 0 | 8 |
_iPrinted edition: _z9783030359720 |
776 | 0 | 8 |
_iPrinted edition: _z9783030359737 |
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-030-35971-3 |
912 | _aZDB-2-ENG | ||
912 | _aZDB-2-SXE | ||
942 | _cEBK | ||
999 |
_c75950 _d75950 |