Abstract: A variety of embodiments for hardware-accelerating the processing of financial market depth data are disclosed. A coprocessor, which may be resident in a ticker plant, can be configured to update order books and price books based on financial market depth data at extremely low latency. Such a coprocessor can also be configured to enrich a stream of limit order events pertaining to financial instruments with data from a plurality of updated order and price books.

Abstract: A variety of embodiments for hardware-accelerating the processing of financial market depth data are disclosed. A coprocessor, which may be resident in a ticker plant, can be configured to update order books and price books based on financial market depth data at extremely low latency. Such a coprocessor can also be configured to enrich a stream of limit order events pertaining to financial instruments with data from a plurality of updated order and price books.

Abstract: Apparatuses and methods are disclosed for comparing a first biosequence string with a second biosequence string to assess similarity between those biosequence strings. For example, a field programmable gate array (FPGA) can be used to (1) detect substrings of the second biosequence string that are matches to substrings of the first biosequence string, and (2) map the detected substrings of the second biosequence string to corresponding positions in the first biosequence string where the detected substrings are located based on a data structure that links substrings of the first biosequence string to positions in the first biosequence string where the substrings of the first biosequence string are located. These operations can be used to seed an alignment between the first and second biosequence strings that permits comparisons to be performed over longer substrings of the first and second biosequence strings so that similarities between those longer substrings can be quantified.

Abstract: Method and Apparatus for High-Speed Processing of Financial Market Depth Data A variety of embodiments for hardware-accelerating the processing of financial market depth data are disclosed. A coprocessor, which may be resident in a ticker plant, can be configured to update order books and price books based on financial market depth data at extremely low latency. Such a coprocessor can also be configured to enrich a stream of limit order events pertaining to financial instruments with data from a plurality of updated order and price books.

Abstract: Apparatuses and methods are disclosed for comparing a first biosequence string with a second biosequence string to assess similarity between those biosequence strings. For example, a field programmable gate array (FPGA) can be used to (1) detect substrings of the second biosequence string that are matches to substrings of the first biosequence string, and (2) map the detected substrings of the second biosequence string to corresponding positions in the first biosequence string where the detected substrings are located based on a data structure that links substrings of the first biosequence string to positions in the first biosequence string where the substrings of the first biosequence string are located. These operations can be used to seed an alignment between the first and second biosequence strings that permits comparisons to be performed over longer substrings of the first and second biosequence strings so that similarities between those longer substrings can be quantified.

Abstract: A variety of embodiments for hardware-accelerating the processing of financial market depth data are disclosed. A coprocessor, which may be resident in a ticker plant, can be configured to update order books based on financial market depth data at extremely low latency. Such a coprocessor can also be configured to enrich a stream of limit order events pertaining to financial instruments with data from a plurality of updated order books.

Abstract: Apparatuses and methods are disclosed for comparing a first biosequence string with a second biosequence string to assess similarity between those biosequence strings. For example, a field programmable gate array (FPGA) can be used to (1) detect substrings of the second biosequence string that are matches to substrings of the first biosequence string, and (2) map the detected substrings of the second biosequence string to corresponding positions in the first biosequence string where the detected substrings are located based on a data structure that links substrings of the first biosequence string to positions in the first biosequence string where the substrings of the first biosequence string are located. These operations can be used to seed an alignment between the first and second biosequence strings that permits comparisons to be performed over longer substrings of the first and second biosequence strings so that similarities between those longer substrings can be quantified.

Abstract: A system and method for performing similarity searching is disclosed wherein programmable logic devices such as field programmable gate arrays (FPGAs) can be used to implement Bloom filters for identifying possible matches between a query and data. The Bloom filters can be implemented in a parallel architecture where the different parallel Bloom filters share access to the same memory units. Further, a hash table may be generated to map a set of strings to keys. In other examples, the hash table may be used to map a set of substrings to a position in a larger string.

Abstract: A variety of embodiments for hardware-accelerating the processing of financial market depth data are disclosed. A coprocessor, which may be resident in a ticker plant, can be configured to update order books based on financial market depth data at extremely low latency. Such a coprocessor can also be configured to enrich a stream of limit order events pertaining to financial instruments with data from a plurality of updated order books.

Abstract: A variety of embodiments for hardware-accelerating the processing of financial market depth data are disclosed. A coprocessor, which may be resident in a ticker plant, can be configured to update order books based on financial market depth data at extremely low latency. Such a coprocessor can also be configured to enrich a stream of limit order events pertaining to financial instruments with data from a plurality of updated order books.

Abstract: A system and method for performing similarity searching is disclosed wherein programmable logic devices such as field programmable gate arrays (FPGAs) can be used to implement Bloom filters for identifying possible matches between a query and data. The Bloom filters can be implemented in a parallel architecture where the different parallel Bloom filters share access to the same memory units. Further, a hash table may be generated to map a set of strings to keys. In other examples, the hash table may be used to map a set of substrings to a position in a larger string.

Abstract: A system and method for performing similarity searching is disclosed wherein programmable logic devices such as field programmable gate arrays (FPGAs) can be used to implement Bloom filters for identifying possible matches between a query and data. The Bloom filters can be implemented in a parallel architecture where the different parallel Bloom filters share access to the same memory units.

Abstract: A variety of embodiments for hardware-accelerating the processing of financial market depth data are disclosed. A coprocessor, which may be resident in a ticker plant, can be configured to update order books based on financial market depth data at extremely low latency. Such a coprocessor can also be configured to enrich a stream of limit order events pertaining to financial instruments with data from a plurality of updated order books.

Abstract: A variety of embodiments for hardware-accelerating the processing of financial market depth data are disclosed. A coprocessor, which may be resident in a ticker plant, can be configured to update order books based on financial market depth data at extremely low latency. Such a coprocessor can also be configured to enrich a stream of limit order events pertaining to financial instruments with data from a plurality of updated order books.

Abstract: A variety of embodiments for hardware-accelerating the processing of financial market depth data are disclosed. A coprocessor, which may be resident in a ticker plant, can be configured to update order books based on financial market depth data at extremely low latency. Such a coprocessor can also be configured to generate a quote event in response to a limit order event being determined to modify the top of an order book.

Abstract: A system and method for performing similarity searching is disclosed wherein programmable logic devices such as field programmable gate arrays (FPGAs) can be used to implement Bloom filters for identifying possible matches between a query and data. The Bloom filters can be implemented in a parallel architecture where the different parallel Bloom filters share access to the same memory units.

Abstract: A system and method for performing similarity searching is disclosed. This includes a programmable logic device configured to include a pipeline that comprises a matching stage, the matching stage being configured to receive a data stream comprising a plurality of possible matches between a plurality of data strings and a plurality of substrings of a query string. The pipeline may further include an ungapped extension prefilter stage located downstream from the matching stage, the prefilter stage being configured to shift through pattern matches between the data strings and the plurality of substrings of a query string and provide a score so that only pattern matches that exceed a user defined score will pass downstream from the prefilter stage. The matching stage may include at least one Bloom filter.

Abstract: A variety of embodiments for hardware-accelerating the processing of financial market depth data are disclosed. A coprocessor, which may be resident in a ticker plant, can be configured to update order books based on financial market depth data at extremely low latency. Such a coprocessor can also be configured to enrich a stream of limit order events pertaining to financial instruments with data from a plurality of updated order books.

Abstract: A variety of embodiments for hardware-accelerating the processing of financial market depth data are disclosed. A coprocessor, which may be resident in a ticker plant, can be configured to update order books based on financial market depth data at extremely low latency. Such a coprocessor can also be configured to generate a quote event in response to a limit order event being determined to modify the top of an order book.

Abstract: A variety of embodiments for hardware-accelerating the processing of financial market depth data are disclosed. A coprocessor, which may be resident in a ticker plant, can be configured to update order books based on financial market depth data at extremely low latency. Such a coprocessor can also be configured to enrich a stream of limit order events pertaining to financial instruments with data from a plurality of updated order books.