Method and Apparatus for High-Speed Processing of Financial Market Depth Data

A system for applying specific computer technology to reduce latency and increase throughput with respect to updating a plurality of financial instrument order books in response to financial market data, the system comprising:

• a memory for storing (1) a plurality of order data structures and (2) a plurality of price aggregation data structures, wherein the order data structures represent a plurality of order books for a plurality of financial instruments, wherein each order book corresponds to a financial instrument and comprises a plurality of limit order records for its corresponding financial instrument, wherein the limit order records of an order book comprise a plurality of fields that represent different limit orders for the order book's corresponding financial instrument, wherein the price aggregation data structures represent a plurality of price books for the financial instruments, wherein each price book corresponds to a financial instrument and comprises a plurality of price point records for its corresponding financial instrument, and wherein the price point records of a price book comprise a plurality of fields that represent aggregations of order information for limit orders at different price points for the price book's corresponding financial instrument;
• and
• a member of the group consisting of (1) a reconfigurable logic device, (2) a chip multi-processor (CMP), (3) an application-specific integrated circuit (ASIC), (4) a graphics processing unit (GPU), and (5) a multi-core superscalar processor, the member for processing financial market data, wherein the processed financial market data includes a plurality of limit order events for a plurality of financial instruments, and wherein the member comprises an order engine and a price engine that are deployed on the member for operation in parallel with each other;
• and
• wherein the order engine and the price engine are configured to update and maintain the order data structures and the price aggregation data structures in parallel with each other based on the limit order events within the processed financial market data.

A method for applying specific computer technology to reduce latency and increase throughput with respect to updating a plurality of financial instrument order books in response to financial market data, the method comprising:

• storing a plurality of order data structures and a plurality of price aggregation data structures in memory, wherein the order data structures represent a plurality of order books for a plurality of financial instruments, wherein each order book corresponds to a financial instrument and comprises a plurality of limit order records for its corresponding financial instrument, wherein the limit order records of an order book comprise a plurality of fields that represent different limit orders for the order book's corresponding financial instrument, wherein the price aggregation data structures represent a plurality of price books for the financial instruments, wherein each price book corresponds to a financial instrument and comprises a plurality of price point records for its corresponding financial instrument, and wherein the price point records of a price book comprise a plurality of fields that represent aggregations of order information for limit orders at different price points for the price book's corresponding financial instrument;
• and
• processing financial market data by a member of the group consisting of (1) a reconfigurable logic device, (2) a chip multi-processor (CMP), (3) an application-specific integrated circuit (ASIC), (4) a graphics processing unit (GPU), and (5) a multi-core superscalar processor, wherein the processed financial market data includes a plurality of limit order events for a plurality of financial instruments, and wherein the member comprises an order engine and a price engine that are deployed on the member for operation in parallel with each other;
• and
• wherein the processing step comprises the order engine and the price engine updating and maintaining the order data structures and the price aggregation data structures in parallel with each other based on the limit order events within the processed financial market data.