000 | 03884nam a22005535i 4500 | ||
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001 | 978-3-319-92792-3 | ||
003 | DE-He213 | ||
005 | 20220801214929.0 | ||
007 | cr nn 008mamaa | ||
008 | 180821s2019 sz | s |||| 0|eng d | ||
020 |
_a9783319927923 _9978-3-319-92792-3 |
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024 | 7 |
_a10.1007/978-3-319-92792-3 _2doi |
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_a621.3815 _223 |
245 | 1 | 0 |
_aHardware Accelerators in Data Centers _h[electronic resource] / _cedited by Christoforos Kachris, Babak Falsafi, Dimitrios Soudris. |
250 | _a1st ed. 2019. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2019. |
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300 |
_aIX, 279 p. 107 illus., 88 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 -- Building the Infrastructure for Deploying FPGAs in the Cloud -- dReDBox: A Disaggregated Architectural Perspective for Data Centers -- The Green Computing Continuum: The OPERA Perspective -- SPynq: Acceleration of Machine Learning Applications over Spark on Pynq -- M2DC - A Novel Heterogeneous Hyperscale Microserver Platform -- Towards an Energy-aware Framework for Application Development and Execution in Heterogeneous Parallel Architectures -- Enabling Virtualized Programmable Logic Resources at the Edge and the Cloud -- Energy Efficient Servers and Cloud -- Towards Ubiquitous Low-power Image Processing Platforms -- Energy-efficient Heterogeneous COmputing at exaSCALE - ECOSCALE -- On Optimizing the Energy Consumption of Urban Data Centers. | |
520 | _aThis book provides readers with an overview of the architectures, programming frameworks, and hardware accelerators for typical cloud computing applications in data centers. The authors present the most recent and promising solutions, using hardware accelerators to provide high throughput, reduced latency and higher energy efficiency compared to current servers based on commodity processors. Readers will benefit from state-of-the-art information regarding application requirements in contemporary data centers, computational complexity of typical tasks in cloud computing, and a programming framework for the efficient utilization of the hardware accelerators. Provides a single-source reference to the state of the art for hardware accelerators in data centers; Describes integrated frameworks for the seamless deployment of hardware accelerators; Includes several use-case scenarios of hardware accelerators for typical cloud computing applications, such as machine learning, graph computation, and databases. | ||
650 | 0 |
_aElectronic circuits. _919581 |
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650 | 0 |
_aMicroprocessors. _941322 |
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650 | 0 |
_aComputer architecture. _93513 |
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650 | 0 |
_aSignal processing. _94052 |
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650 | 1 | 4 |
_aElectronic Circuits and Systems. _941323 |
650 | 2 | 4 |
_aProcessor Architectures. _941324 |
650 | 2 | 4 |
_aSignal, Speech and Image Processing . _931566 |
700 | 1 |
_aKachris, Christoforos. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _941325 |
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700 | 1 |
_aFalsafi, Babak. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _941326 |
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700 | 1 |
_aSoudris, Dimitrios. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _941327 |
|
710 | 2 |
_aSpringerLink (Online service) _941328 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783319927916 |
776 | 0 | 8 |
_iPrinted edition: _z9783319927930 |
776 | 0 | 8 |
_iPrinted edition: _z9783030065188 |
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-319-92792-3 |
912 | _aZDB-2-ENG | ||
912 | _aZDB-2-SXE | ||
942 | _cEBK | ||
999 |
_c76915 _d76915 |