David Mark Indeck

8156101, Apr 10, 2012

Dec 17, 2009

12/640891

Ronald S. Indeck - St. Louis MO, US
David Mark Indeck - Highlands Ranch CO, US

Exegy Incorporated - St. Louis MO

G06F 17/30

707707, 707770, 707771

Disclosed herein is a method and system for integrating an enterprise's structured and unstructured data to provide users and enterprise applications with efficient and intelligent access to that data. Queries can be directed toward both an enterprise's structured and unstructured data using standardized database query formats such as SQL commands. A coprocessor can be used to hardware-accelerate data processing tasks (such as full-text searching) on unstructured data as necessary to handle a query. Furthermore, traditional relational database techniques can be used to access structured data stored by a relational database to determine which portions of the enterprise's unstructured data should be delivered to the coprocessor for hardware-accelerated data processing.

8374986, Feb 12, 2013

May 15, 2008

12/121473

Ronald S. Indeck - St. Louis MO, US
David Mark Indeck - Highlands Ranch CO, US
Naveen Singla - St. Louis MO, US
Jason R. White - Manchester MO, US

Exegy Incorporated - St. Louis MO

G06F 17/00
G06N 5/02

706 47, 370329, 709 22

Disclosed herein is a method and system for hardware-accelerating various data processing operations in a rule-based decision-making system such as a business rules engine, an event stream processor, and a complex event stream processor. Preferably, incoming data streams are checked against a plurality of rule conditions. Among the data processing operations that are hardware-accelerated include rule condition check operations, filtering operations, and path merging operations. The rule condition check operations generate rule condition check results for the processed data streams, wherein the rule condition check results are indicative of any rule conditions which have been satisfied by the data streams. The generation of such results with a low degree of latency provides enterprises with the ability to perform timely decision-making based on the data present in received data streams.

20080114724, May 15, 2008

Nov 12, 2007

11/938709

Ronald S. Indeck - St. Louis MO, US
David Mark Indeck - Highlands Ranch CO, US

EXEGY INCORPORATED - St. Louis MO

G06F 17/30

707 2

Disclosed herein is a method and system for integrating an enterprise's structured and unstructured data to provide users and enterprise applications with efficient and intelligent access to that data. Queries can be directed toward both an enterprise's structured and unstructured data using standardized database query formats such as SQL commands. A coprocessor can be used to hardware-accelerate data processing tasks (such as full-text searching) on unstructured data as necessary to handle a query. Furthermore, traditional relational database techniques can be used to access structured data stored by a relational database to determine which portions of the enterprise's unstructured data should be delivered to the coprocessor for hardware-accelerated data processing.

20130007000, Jan 3, 2013

Apr 9, 2012

13/442442

Ronald S. Indeck - St. Louis MO, US
David Mark Indeck - Highlands Ranch CO, US

EXEGY INCORPORATED - St. Louis MO

G06F 17/30

707741, 707769, 707E17002, 707E17014

Disclosed herein is a method and system for integrating an enterprise's structured and unstructured data to provide users and enterprise applications with efficient and intelligent access to that data. In accordance with exemplary embodiments, the generation of metadata indexes about unstructured data can be hardware-accelerated by processing streaming unstructured data through a reconfigurable logic device to generate the metadata about the unstructured data for the index.

20130151458, Jun 13, 2013

Feb 5, 2013

13/759430

David Mark Indeck - Highlands Ranch CO, US
Naveen Singla - St. Louis MO, US
Jason R. White - Manchester MO, US

Exegy Incorporated - St. Louis MO

G06N 5/02

706 47

Disclosed herein is a method and apparatus for hardware-accelerating various data quality checking operations. Incoming data streams can be processed with respect to a plurality of data quality check operations using offload engines (e.g., reconfigurable logic such as field programmable gate arrays (FPGAs)). Accelerated data quality checking can be highly advantageous for use in connection with Extract, Transfer, and Load (ETL) systems.

20200007157, Jan 2, 2020

Sep 9, 2019

16/564112

- St. Louis MO, US
David Mark Indeck - Highlands Ranch CO, US
Naveen Singla - St. Louis MO, US
Jason R. White - Manchester MO, US

H03M 13/00
G06F 16/2453
G06F 16/2455
G06N 5/02
G06F 9/54

Disclosed herein are methods and systems for hardware-accelerating various data processing operations in a rule-based decision-making system such as a business rules engine, an event stream processor, and a complex event stream processor. Preferably, incoming data streams are checked against a plurality of rule conditions. Among the data processing operations that are hardware-accelerated include rule condition check operations, filtering operations, and path merging operations. The rule condition check operations generate rule condition check results for the processed data streams, wherein the rule condition check results are indicative of any rule conditions which have been satisfied by the data streams. The generation of such results with a low degree of latency provides enterprises with the ability to perform timely decision-making based on the data present in received data streams.

20190155831, May 23, 2019

Jan 28, 2019

16/259326

- Creve Coeur MO, US
David Mark Indeck - Highlands Ranch CO, US
Naveen Singla - St. Louis MO, US
David E. Taylor - St. Louis MO, US

G06F 16/35
G06F 16/2458
G06F 16/22
G06F 16/33
G06F 16/31
G06F 16/28

Disclosed herein are methods and systems for integrating an enterprise's structured and unstructured data to provide users and enterprise applications with efficient and intelligent access to that data. In accordance with exemplary embodiments, the generation of feature vectors about unstructured data can be hardware-accelerated by processing streaming unstructured data through a reconfigurable logic device, a graphics processor unit (GPU), or chip multi-processor (CMP) to determine features that can aid clustering of similar data objects.

20170123866, May 4, 2017

Jan 12, 2017

15/404794

- St. Louis MO, US
David Mark Indeck - Highlands Ranch CO, US
Naveen Singla - St. Louis MO, US
Jason R. White - Manchester MO, US

G06F 9/54
G06F 17/30

Disclosed herein are methods and systems for hardware-accelerating various data processing operations in a rule-based decision-making system such as a business rules engine, an event stream processor, and a complex event stream processor. Preferably, incoming data streams are checked against a plurality of rule conditions. Among the data processing operations that are hardware-accelerated include rule condition check operations, filtering operations, and path merging operations. The rule condition check operations generate rule condition check results for the processed data streams, wherein the rule condition check results are indicative of any rule conditions which have been satisfied by the data streams. The generation of such results with a low degree of latency provides enterprises with the ability to perform timely decision-making based on the data present in received data streams.