Abstract: A radar system processes signals in a flexible, adaptive manner to determine range, Doppler (velocity) and angle of objects in an environment. The radar system processes the received signal to achieve different objectives depending on the environment, the current information stored in the radar system, and/or external information provided to the radar system. The system allows improved resolution of range, Doppler and/or angle depending on the desired objective.

Abstract: A radar sensing system for a vehicle includes a transmitter, a receiver, a memory, and a processor. The transmitter transmits a radio signal and the receiver receives a reflected radio signal. The processor samples reflected radio signals during a plurality of time slices. The processor produces samples by correlating reflected radio signals to time-delayed replicas of transmitted radio signals. The processor accumulates the time slices into a first radar data cube and stores the first radar data cube in a memory. The processor combines a portion of the first radar data cube with a portion of a previously stored radar data cube. Based at least in part on the combined portions of the radar data cubes, the processor processes a time series that is a time series of the first radar data cube concatenated with a time series from the previously stored radar data cube.

Abstract: A radar sensing system includes at least one transmitter, at least one receiver and a processor. The at least one transmitter transmits a power shaped RF signal. The transmitted RF signal decreases in power over time. The at least one receiver receives a reflected RF signal. The reflected RF signal is the transmitted RF signal reflected from targets in the environment. The reflected RF signal is down-converted and the result provided to the processor. The processor samples the down-converted reflected RF signal during a plurality of time intervals to produce a sampled stream. The different time intervals of the plurality of time intervals will contain different signal levels of RF signals reflected from the targets. The processor also selects samples in the sampled stream over a selected time interval of the plurality of time intervals that is free of RF signals reflected off of near targets.

Abstract: A radar system has different modes of operation. In one mode the radar operates as a single-input, multiple-output (SIMO) radar system utilizing one transmitted signal from one antenna at a time. Codes with known excellent autocorrelation properties are utilized in this mode. At each receiver the response after correlating with various possible transmitted signals is measured in order to estimate the interference that each transmitter will represent at each receiver. The estimated effect of the interference from one transmitter on a receiver that correlates with a different code is used to mitigate the interference. In another mode, the radar operates as a MIMO radar system utilizing all the antennas at a time. Interference cancellation of the non-ideal cross correlation sidelobes when transmitting in the MIMO mode are employed to remove ghost targets due to unwanted sidelobes.

Abstract: A radar sensing system for a vehicle includes a transmitter, a receiver, a memory, and a processor. The transmitter transmits a radio signal and the receiver receives a reflected radio signal. The processor samples reflected radio signals during a plurality of time slices. The processor produces samples by correlating reflected radio signals to time-delayed replicas of transmitted radio signals. The processor accumulates the time slices into a first radar data cube and stores the first radar data cube in a memory. The processor combines a portion of the first radar data cube with a portion of a previously stored radar data cube. Based at least in part on the combined portions of the radar data cubes, the processor processes a time series that is a time series of the first radar data cube concatenated with a time series from the previously stored radar data cube.

Abstract: A system for performing data-parallel operations and task-parallel operations. A first switch fabric node (SFN) includes first and second lane processing engines (LPEs). The first LPE includes a first set of lane processing units (LPUs) configured to perform data-parallel operations, where each LPU performs a set of operations, and each LPU uses a different set of data for the set of operations, and each LPU within the first set of LPUs uses a different set of data for the set of operations. The second LPE includes a second set of LPUs configured to perform task-parallel operations, where each LPU performs a different set of operations. A processing control engine (PCE) is configured to distribute instructions and data to the first LPE and the second LPE. Advantageously, data parallel operations and task parallel operations are able to be performed on the same processor simultaneously.

Abstract: A method of operating a Linear Complementarity Problem (LCP) solver is disclosed, where the LCP solver is characterized by multiple execution units operating in parallel to implement a competent computational method adapted to resolve physics-based LCPs in real-time.

Abstract: One embodiment of the invention sets forth a hardware-based physics processing unit (PPU) having unique architecture designed to efficiently generate physics data. The PPU includes a PPU control engine (PCE), a data movement engine and a floating point engine (FPE). The PCE manages the overall operation of the PPU by allocating memory resources and transmitting graphics processing commands to the FPE and data movement commands to the DME. The FPE includes multiple vector processors that operate in parallel and perform floating point operations on data received from a host unit to generate physics simulation data. The DME facilitates the transmission of data between the host unit and the FPE by performs data movement operations between memories internal and external to the PPU.

Abstract: A method of providing physics data within a game program or simulation using a hardware-based physics processing unit having unique architecture designed to efficiently calculate physics related data.

Abstract: An integrated circuit comprises an external memory, a plurality of parallel connected Vector Processing Engines (VPEs), and an External Memory Unit (EMU) providing a data transfer path between the VPEs and the external memory. Each VPE contains a plurality of data processing units and a message queuing system adapted to transfer messages between the data processing units and other components of the integrated circuit.

Abstract: A method of operating a Linear Complementarity Problem (LCP) solver is disclosed, where the LCP solver is characterized by multiple execution units operating in parallel to implement a competent computational method adapted to resolve physics-based LCPs in real-time.

Abstract: An integrated circuit comprises an external memory, a plurality of parallel connected Vector Processing Engines (VPEs), and an External Memory Unit (EMU) providing a data transfer path between the VPEs and the external memory. Each VPE contains a plurality of data processing units and a message queuing system adapted to transfer messages between the data processing units and other components of the integrated circuit.

Abstract: A Linear Complementarity Problem (LCP) solver is characterized by multiple execution units operating in parallel to implement a competent computational method adapted to resolve physics-based LCPs in real-time.

Abstract: An efficient quasi-custom instruction set for Physics Processing Unit (PPU) is enabled by balancing the dictates of a parallel arrangement of multiple, independent vector processors and programming considerations. A hierarchy of multiple, programmable memories and distributed control over data transfer is presented.

Abstract: A method of operating a Linear Complementarity Problem (LCP) solver is disclosed, where the LCP solver is characterized by multiple execution units operating in parallel to implement a competent computational method adapted to resolve physics-based LCPs in real-time.

Abstract: A Linear Complementarity Problem (LCP) solver is characterized by multiple execution units operating in parallel to implement a competent computational method adapted to resolve physics-based LCPs in real-time.

Abstract: A system, such as a PC, incorporating a dedicated physics processing unit adapted to generate physics data for use within a physics simulation or game animation. The hardware-based physics processing unit is characterized by a unique architecture designed to efficiently calculate physics data, including multiple, parallel floating point operations.

Abstract: A method of providing physics data within a game program or simulation using a hardware-based physics processing unit having unique architecture designed to efficiently calculate physics related data.

Abstract: A hardware-based physics processing unit having unique architecture designed to efficiently calculate physics data.

Abstract: A method and device for controlling bandwidth distribution through a switch fabric is provided wherein a plurality of line cards and processor cards are connected through a switch fabric for parallel processing of transmission requests, along with the provision of transmission “credits” allowing for transmitting additional data bytes during a given cycle, which provides efficient and speedy bandwidth distribution, as well as resolution of output contentions. The processors maintain a credit balance which allows flexibility in granting transmission requests to accommodate transmission scheduling and “bursty” transmissions. Processors on both of the line cards and the processor cards normalize the data transmission requirements for both inputs and outputs connected by the switch fabric. Smoothing of data transmission is provided using a time-weighted buffer.