大葉大學圖書館 |

FPGA based accelerators for financial applications[electronic resource] /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	621.4
書名/作者:	FPGA based accelerators for financial applications/ edited by Christian De Schryver.
其他題名:	Field Programmable Gate Arrays based accelerators for financial applications
其他作者:	Schryver, Christian De.
出版者:	Cham : : Springer International Publishing :, 2015.
面頁冊數:	xviii, 273 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Field programmable gate arrays.
標題:	Gate array circuits.
標題:	Engineering.
標題:	Circuits and Systems.
標題:	Processor Architectures.
標題:	Electronics and Microelectronics, Instrumentation.
標題:	Energy, general.
標題:	Quantitative Finance.
ISBN:	9783319154077 (electronic bk.)
ISBN:	9783319154060 (paper)
內容註:	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.
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1007/978-3-319-15407-7

FPGA based accelerators for financial applications[electronic resource] /
FPGA based accelerators for financial applications[electronic resource] /Field Programmable Gate Arrays based accelerators for financial applicationsedited by Christian De Schryver. - Cham :Springer International Publishing :2015. - xviii, 273 p. :ill., digital ;24 cm.

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 (electronic bk.)

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

382931
Field programmable gate arrays.

LC Class. No.: TK7895.G36

Dewey Class. No.: 621.4

FPGA based accelerators for financial applications[electronic resource] /
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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.
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