國立虎尾科技大學 |

FPGA Based Accelerators for Financial Applications

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	FPGA Based Accelerators for Financial Applications/ edited by Christian De Schryver.
其他作者:	De Schryver, Christian.
面頁冊數:	XVIII, 273 p. 72 illus., 47 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Electronic circuits. -
電子資源:	https://doi.org/10.1007/978-3-319-15407-7
ISBN:	9783319154077

FPGA Based Accelerators for Financial Applications
FPGA Based Accelerators for Financial Applications[electronic resource] /edited by Christian De Schryver. - 1st ed. 2015. - XVIII, 273 p. 72 illus., 47 illus. in color.online resource.

10 Computational Challenges in Finance -- From model to application: calibration to market data -- Comparative study of acceleration platforms for Heston’s stochastic volatility model -- Towards Automated Benchmarking and Evaluation of Heterogeneous Systems in Finance -- Is High Level Synthesis ready for business? An Option Pricing Case Study -- High-Bandwidth Low-Latency Interfacing with FPGA Accelerators Using PCI Express -- Pricing High-Dimensional American Options on Hybrid CPU/FPGA Systems -- Bringing Flexibility to FPGA Based Pricing Systems -- Exploiting mixed-precision arithmetics in a multilevel Monte Carlo approach on FPGAs -- Accelerating Closed-Form Heston Prices for Calibration.

This book covers the latest approaches and results from reconfigurable computing architectures employed in the finance domain. So-called field-programmable gate arrays (FPGAs) have already shown to outperform standard CPU- and GPU-based computing architectures by far, saving up to 99% of energy depending on the compute tasks. Renowned authors from financial mathematics, computer architecture, and finance business introduce the readers into today’s challenges in finance IT, illustrate the most advanced approaches and use cases, and present currently known methodologies for integrating FPGAs in finance systems together with latest results. The complete algorithm-to-hardware flow is covered holistically, so this book serves as a hands-on guide for IT managers, researchers, and quants/programmers who think about integrating FPGAs into their current IT systems.

ISBN: 9783319154077

Standard No.: 10.1007/978-3-319-15407-7doiSubjects--Topical Terms:

563332
Electronic circuits.

LC Class. No.: TK7888.4

Dewey Class. No.: 621.3815

FPGA Based Accelerators for Financial Applications
LDR:02919nam a22003975i 4500 001 963052
003 DE-He213
005 20200706093156.0
007 cr nn 008mamaa
008 201211s2015 gw | s |||| 0|eng d
020 $a 9783319154077 $9 978-3-319-15407-7
024 7 $a 10.1007/978-3-319-15407-7 $2 doi
035 $a 978-3-319-15407-7
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 FPGA Based Accelerators for Financial Applications $h [electronic resource] / $c edited by Christian De Schryver.
250 $a 1st ed. 2015.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a XVIII, 273 p. 72 illus., 47 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 10 Computational Challenges in Finance -- From model to application: calibration to market data -- Comparative study of acceleration platforms for Heston’s stochastic volatility model -- Towards Automated Benchmarking and Evaluation of Heterogeneous Systems in Finance -- Is High Level Synthesis ready for business? An Option Pricing Case Study -- High-Bandwidth Low-Latency Interfacing with FPGA Accelerators Using PCI Express -- Pricing High-Dimensional American Options on Hybrid CPU/FPGA Systems -- Bringing Flexibility to FPGA Based Pricing Systems -- Exploiting mixed-precision arithmetics in a multilevel Monte Carlo approach on FPGAs -- Accelerating Closed-Form Heston Prices for Calibration.
520 $a This book covers the latest approaches and results from reconfigurable computing architectures employed in the finance domain. So-called field-programmable gate arrays (FPGAs) have already shown to outperform standard CPU- and GPU-based computing architectures by far, saving up to 99% of energy depending on the compute tasks. Renowned authors from financial mathematics, computer architecture, and finance business introduce the readers into today’s challenges in finance IT, illustrate the most advanced approaches and use cases, and present currently known methodologies for integrating FPGAs in finance systems together with latest results. The complete algorithm-to-hardware flow is covered holistically, so this book serves as a hands-on guide for IT managers, researchers, and quants/programmers who think about integrating FPGAs into their current IT systems.
650 0 $a Electronic circuits. $3 563332
650 0 $a Microprocessors. $3 632481
650 0 $a Electronics. $3 596389
650 0 $a Microelectronics. $3 554956
650 0 $a Energy. $3 784773
650 0 $a Economics, Mathematical . $3 1253712
650 1 4 $a Circuits and Systems. $3 670901
650 2 4 $a Processor Architectures. $3 669787
650 2 4 $a Electronics and Microelectronics, Instrumentation. $3 670219
650 2 4 $a Energy, general. $3 782925
650 2 4 $a Quantitative Finance. $3 669372
700 1 $a De Schryver, Christian. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1257987
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319154060
776 0 8 $i Printed edition: $z 9783319154084
776 0 8 $i Printed edition: $z 9783319362786
856 4 0 $u https://doi.org/10.1007/978-3-319-15407-7
912 $a ZDB-2-ENG
912 $a ZDB-2-SXE
950 $a Engineering (SpringerNature-11647)
950 $a Engineering (R0) (SpringerNature-43712)