Title
Faster FAST: multicore acceleration of streaming financial data
Abstract
By 2010, the global options and equity markets will average over 128 billion messages per day, amounting to trillions of dollars in trades. Trading systems, the backbone of the low-latency high-frequency business, need fundamental research and innovation to overcome their current processing bottlenecks. With market data rates rapidly growing, the financial community is demanding solutions that are extremely fast, flexible, adaptive, and easy to manage. This paper explores multiple avenues to deal with the decoding and normal- ization of Option Price Reporting Authority (OPRA) stock market data feeds encoded with FIX Adapted for Streaming (FAST) representation, on commodity multicore platforms, and describes a novel solution that encodes the OPRA protocol with a high-level description language. Our algorithm achieves a processing rate of 15 million messages per second in the fastest single socket configuration on an Intel Xeon E5472, which is an order of mag- nitude higher than the current needs of the financial systems. We also present an in-depth performance evaluation that exposes important properties of our OPRA parsing algorithm on a collection of multicore processors.
Year
DOI
Venue
2009
10.1007/s00450-009-0093-5
Computer Science - R&D
Keywords
Field
DocType
low latency,high frequency,multicore processors,financial system,option pricing
Bottleneck,Computer science,High-level programming language,Equity (finance),Decoding methods,Xeon,Market data,Finance,Multi-core processor,Stock market
Journal
Volume
Issue
ISSN
23
3-4
1865-2042
Citations 
PageRank 
References 
11
1.32
7
Authors
7
Name
Order
Citations
PageRank
Virat Agarwal124816.61
Bader, David A.22507219.90
Lin Dan3111.32
Lurng-kuo Liu431640.47
Davide Pasetto516311.77
Michael P. Perrone67616.50
Fabrizio Petrini72050165.82