國立虎尾科技大學 |

Hardware Accelerators in Data Centers

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Hardware Accelerators in Data Centers/ edited by Christoforos Kachris, Babak Falsafi, Dimitrios Soudris.
其他作者:	Kachris, Christoforos.
面頁冊數:	IX, 279 p. 107 illus., 88 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Electronic circuits. -
電子資源:	https://doi.org/10.1007/978-3-319-92792-3
ISBN:	9783319927923

Hardware Accelerators in Data Centers
Hardware Accelerators in Data Centers[electronic resource] /edited by Christoforos Kachris, Babak Falsafi, Dimitrios Soudris. - 1st ed. 2019. - IX, 279 p. 107 illus., 88 illus. in color.online resource.

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.

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.

ISBN: 9783319927923

Standard No.: 10.1007/978-3-319-92792-3doiSubjects--Topical Terms:

563332
Electronic circuits.

LC Class. No.: TK7888.4

Dewey Class. No.: 621.3815

Hardware Accelerators in Data Centers
LDR:03147nam a22003975i 4500 001 1013072
003 DE-He213
005 20200704205005.0
007 cr nn 008mamaa
008 210106s2019 gw | s |||| 0|eng d
020 $a 9783319927923 $9 978-3-319-92792-3
024 7 $a 10.1007/978-3-319-92792-3 $2 doi
035 $a 978-3-319-92792-3
050 4 $a TK7888.4
072 7 $a TJFC $2 bicssc
072 7 $a TEC008010 $2 bisacsh
072 7 $a TJFC $2 thema
082 0 4 $a 621.3815 $2 23
245 1 0 $a Hardware Accelerators in Data Centers $h [electronic resource] / $c edited by Christoforos Kachris, Babak Falsafi, Dimitrios Soudris.
250 $a 1st ed. 2019.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a IX, 279 p. 107 illus., 88 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a 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 $a 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 $a Electronic circuits. $3 563332
650 0 $a Microprocessors. $3 632481
650 0 $a Signal processing. $3 561459
650 0 $a Image processing. $3 557495
650 0 $a Speech processing systems. $3 564428
650 1 4 $a Circuits and Systems. $3 670901
650 2 4 $a Processor Architectures. $3 669787
650 2 4 $a Signal, Image and Speech Processing. $3 670837
700 1 $a Kachris, Christoforos. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1072879
700 1 $a Falsafi, Babak. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 675871
700 1 $a Soudris, Dimitrios. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 783536
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319927916
776 0 8 $i Printed edition: $z 9783319927930
776 0 8 $i Printed edition: $z 9783030065188
856 4 0 $u https://doi.org/10.1007/978-3-319-92792-3
912 $a ZDB-2-ENG
912 $a ZDB-2-SXE
950 $a Engineering (SpringerNature-11647)
950 $a Engineering (R0) (SpringerNature-43712)