Lockheed Martin Corporation

Chandan Mathur

John Walter Rapp

Scott Hellenbach

Mark J Jones

Joseph A Capizzi

Larry Jackson

Kenneth R Schulz

Troy Cherasaro

Andrew Hamm

A mission system includes a peer vector machine having a host processor and pipeline accelerator and including bridge objects that provide communication via signal objects, message objects, and mission objects.

Object oriented mission framework and system and method

A computing machine includes a first buffer and a processor coupled to the buffer. The processor executes an application, a first data-transfer object, and a second data-transfer object, publishes data under the control of the application, loads the published data into the buffer under the control of the first data-transfer object, and retrieves the published data from the buffer under the control of the second data-transfer object. Alternatively, the processor retrieves data and loads the retrieved data into the buffer under the control of the first data-transfer object, unloads the data from the buffer under the control of the second data-transfer object, and processes the unloaded data under the control of the application. Where the computing machine is a peer-vector machine that includes a hardwired pipeline accelerator coupled to the processor, the buffer and data-transfer objects facilitate the transfer of data between the application and the accelerator.

Computing machine using software objects for transferring data that includes no destination information

A computing machine comprises an electronic circuit operable to perform a function, a programmable integrated circuit such as an FPGA, and a processor. The processor is operable to detect a failure of the electronic circuit and to configure the programmable integrated circuit to perform the function of the electronic circuit in response to detecting the failure. Alternatively, the computing machine comprises a hardwired pipeline operable to perform a function and a processor operable to detect a failure of the pipeline and to perform the function in response to detecting the failure. By allowing a first type of circuit (e.g., an FPGA) to take over for a failed second type of circuit (e.g., a processor), such a computing machine can be fault-tolerant without having redundant versions of each component, and may thus be less expensive and smaller than computing machines of comparable computing power.

Reconfigurable computing machine and related systems and methods

According to an embodiment of the invention, a computing machine comprises a pipeline accelerator, a host processor coupled to the pipeline accelerator, and a redundant processor, a redundant pipeline unit, or both, coupled to the host processor and to the pipeline accelerator. The computing machine may also include a system-restore server and a system-restore bus that allow the machine to periodically save the machine states in case of a failure. Such a computing machine has a fault-tolerant scheme that is often more flexible than conventional schemes. For example, if the pipeline accelerator has more extra 'space' than the host processor, then one can add to the computing machine one or more redundant pipeline units that can provide redundancy to both the pipeline and the host processor. Therefore, the computing machine can include redundancy for the host processor even though it has no redundant processing units.

Computing machine with redundancy and related systems and methods

A peer-vector machine includes a host processor and a hardwired pipeline accelerator. The host processor executes a program, and, in response to the program, generates host data, and the pipeline accelerator generates pipeline data from the host data. Alternatively, the pipeline accelerator generates the pipeline data, and the host processor generates the host data from the pipeline data. Because the peer-vector machine includes both a processor and a pipeline accelerator, it can often process data more efficiently than a machine that includes only processors or only accelerators. For example, one can design the peer-vector machine so that the host processor performs decision-making and non-mathematically intensive operations and the accelerator performs non-decision-making and mathematically intensive operations. By shifting the mathematically intensive operations to the accelerator, the peer-vector machine often can, for a given clock frequency, process data at a speed that surpasses the speed at which a processor-only machine can process the data.

Growing community of inventors

Manassas, VA, United States of America

Chandan Mathur