000			03722nam a22004455i 4500
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007			cr nn nnnaamaa
710	2		_aSpringerLink (Online service) _9106996
999			_c110809 _d110809 _x1
001			110809
003			ES-MaUEC
005			20230102113439.0
008			180821s2019 gw a o |||| 0|eng d
020			_a9783319927923
024	7		_a10.1007/978-3-319-92792-3 _2doi
040			_bspa _dES-MaUEC _cES-MaUEC
050		4	_aQA76.9 .A73 _b2019 EB
245	0	0	_aHardware Accelerators in Data Centers _cedited by Christoforos Kachris, Babak Falsafi, Dimitrios Soudris
264		1	_aCham _bSpringer International Publishing : _bImprint: Springer _c2019
300			_a1 recurso en línea (IX, 279 páginas) _b107 ilustraciones, 88 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aEngineering (Springer-11647)
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	3		_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
988			_aPrimersemestre_2019_Engineering
650		7	_2embne _aArquitectura de ordenador _9144554
650		7	_2embne _aInformática en la nube _9666069
650		7	_2embne _aComputación de altas prestaciones _9468437
700	1		_aFalsafi, Babak. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aKachris, Christoforos. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aSoudris, Dimitrios. _eeditor literario _4edt _4http://id.loc.gov/vocabulary/relators/edt
776	0	8	_iPrinted edition: _z9783030065188
776	0	8	_iPrinted edition: _z9783319927916
776	0	8	_iPrinted edition: _z9783319927930
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-92792-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_aSI _cm _dz _feng _ggw _h0 _b09/2019 _eel _zSI