Paper Info
Title
GPU Extended Stock Market Software Architecture.
Abstract
We propose a stock market software architecture extended by a graphics processing unit, which employs parallel programming paradigm techniques to optimize long-running tasks like computing daily trends and performing statistical analysis of stock market data in realtime. The system uses the ability of Nvidia's CUDA parallel computation application programming interface (API) to integrate with traditional web development frameworks. The web application offers extensive statistics and stocks' information which is periodically recomputed through scheduled batch jobs or calculated in real-time. To illustrate the advantages of using many-core programming, we explore several use-cases and evaluate the improvement in performance and speedup obtained in comparison to the traditional approach of executing long-running jobs on a central processing unit (CPU).
Year
DOI
Venue
2019
10.1007/978-3-030-23976-3_34
Lecture Notes of the Institute for Computer Sciences, Social Informatics, and Telecommunications Engineering
Keywords
DocType
Volume
Stock market,GPU,Parallel programming,CUDA
Conference
283
ISSN
Citations 
PageRank 
1867-8211
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Alisa Krstova100.34
Marjan Gusev229268.27
Vladimir Zdraveski374.69