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Accelerated Anticor Online Portfolio Selection on Multi-core CPUs and GPU with OpenCL.

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Title: Accelerated Anticor Online Portfolio Selection on Multi-core CPUs and GPU with OpenCL.
Authors: Nazir, Amril1 amril@tu.edu.sa
Source: IAENG International Journal of Computer Science. Sep2018, Vol. 45 Issue 3, p390-402. 13p.
Subjects: OpenCL (Computer program language), Programming languages, Central processing units, Graphics processing units, Computer science
Abstract: We present an efficient financial portfolio selection and optimization implementation of Anticor's algorithm. Our solution utilizes the OpenCL framework to offer the most optimal speedups on heterogeneous hardware platforms that take advantage* of multi-core CPU and many-core GPU architectures. To our knowledge, this work is the first accelerated Anticor portfolio selection implementation that solves computationally intensive portfolio optimization problems across heterogeneous platforms using both multi-core CPUs and GPU. [ABSTRACT FROM AUTHOR]
Copyright of IAENG International Journal of Computer Science is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: Accelerated Anticor Online Portfolio Selection on Multi-core CPUs and GPU with OpenCL.
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  Data: We present an efficient financial portfolio selection and optimization implementation of Anticor's algorithm. Our solution utilizes the OpenCL framework to offer the most optimal speedups on heterogeneous hardware platforms that take advantage* of multi-core CPU and many-core GPU architectures. To our knowledge, this work is the first accelerated Anticor portfolio selection implementation that solves computationally intensive portfolio optimization problems across heterogeneous platforms using both multi-core CPUs and GPU. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of IAENG International Journal of Computer Science is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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      – SubjectFull: Programming languages
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      – TitleFull: Accelerated Anticor Online Portfolio Selection on Multi-core CPUs and GPU with OpenCL.
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              Text: Sep2018
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