MARC 主機 00000nam a2200481 i 4500 
001    978-3-319-92792-3 
003    DE-He213 
005    20180821164954.0 
006    m     o  d         
007    cr nn 008maaau 
008    180821s2019    gw      s         0 eng d 
020    9783319927923|q(electronic bk.) 
020    9783319927916|q(paper) 
024 7  10.1007/978-3-319-92792-3|2doi 
040    GP|cGP|erda 
041 0  eng 
050  4 QA76.9.A73 
082 04 004.35|223 
245 00 Hardware accelerators in data centers /|cedited by 
       Christoforos Kachris, Babak Falsafi, Dimitrios Soudris 
264  1 Cham :|bSpringer International Publishing :|bImprint: 
       Springer,|c2019 
300    1 online resource (ix, 279 pages) :|billustrations, 
       digital ;|c24 cm 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
347    text file|bPDF|2rda 
505 0  Introduction -- 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    This 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 Computer architecture 
650  0 High performance computing 
650 14 Engineering 
650 24 Circuits and Systems 
650 24 Processor Architectures 
650 24 Signal, Image and Speech Processing 
700 1  Kachris, Christoforos,|eeditor 
700 1  Falsafi, Babak,|eeditor 
700 1  Soudris, Dimitrios,|eeditor 
710 2  SpringerLink (Online service) 
773 0  |tSpringer eBooks 
856 40 |uhttp://dx.doi.org/10.1007/978-3-319-92792-3