Abstract: Embodiments are directed to a file system that include object stores. An object store for write requests may be provided. Write ahead log (WAL) entries that include data blocks may be generated. A WAL object may be generated based on the WAL entries and stored in the object store. An in-memory overlay may be updated to associate the data blocks with the WAL object. A checkpoint operation may be executed to: generate an index object that includes index entries that associate other data blocks with data objects stored in the object store; update the index object to include index entries that associate the data blocks with the WAL object; store the updated index object in the object store; update the in-memory overlay to remove the association of the data blocks and the WAL object and update the in memory WAL to remove records of successfully checkpointed WAL objects.

Abstract: A tailgate deactivation system. A switch includes two terminals configured to be electrically coupled to a tailgate power circuit that supplies power to at least a portion of a tailgate of a vehicle, and an actuator configured to electrically couple the two terminals in an on state to allow power to flow in the tailgate power circuit, and to electrically decouple the two terminals in an off state to inhibit power from flowing in the tailgate power circuit.

Abstract: Embodiments are directed to a file system that include object stores. An object store for write requests may be provided. Write ahead log (WAL) entries that include data blocks may be generated. A WAL object may be generated based on the WAL entries and stored in the object store. An in-memory overlay may be updated to associate the data blocks with the WAL object. A checkpoint operation may be executed to: generate an index object that includes index entries that associate other data blocks with data objects stored in the object store; update the index object to include index entries that associate the data blocks with the WAL object; store the updated index object in the object store; update the in-memory overlay to remove the association of the data blocks and the WAL object and update the in memory WAL to remove records of successfully checkpointed WAL objects.

Abstract: Techniques in wavelet filtering for advanced deep learning provide improvements in one or more of accuracy, performance, and energy efficiency. An array of processing elements comprising a portion of a neural network accelerator performs flow-based computations on wavelets of data. Each processing element comprises a compute element to execute programmed instructions using the data and a router to route the wavelets in accordance with virtual channel specifiers. Each processing element is enabled to perform local filtering of wavelets received at the processing element, selectively, conditionally, and/or optionally discarding zero or more of the received wavelets, thereby preventing further processing of the discarded wavelets. The wavelet filtering is performed by one or more configurable wavelet filters operable in various modes, such as counter, sparse, and range modes.

Abstract: Techniques in placement of compute and memory for accelerated deep learning provide improvements in one or more of accuracy, performance, and energy efficiency. An array of processing elements comprising a portion of a neural network accelerator performs flow-based computations on wavelets of data. Each processing element comprises a compute element to execute programmed instructions using the data and a router to route the wavelets. The routing is in accordance with virtual channel specifiers of the wavelets and controlled by routing configuration information of the router. A software stack determines placement of compute resources and memory resources based on a description of a neural network. The determined placement is used to configure the routers including usage of the respective colors. The determined placement is used to configure the compute elements including the respective programmed instructions each is configured to execute.

Abstract: A vent system for a motor vehicle includes a vent conduit defining a vent conduit inlet. A vent outlet is separated from the vent conduit inlet. A first vent channel includes a first vent channel inlet in fluid communication with the vent conduit inlet and a first channel nozzle defining a first fluid flow path to the vent outlet along a first direction. A second vent channel includes a second channel inlet in fluid communication with the vent conduit inlet and a second channel nozzle defining a second fluid flow path to the vent outlet along a second direction convergent with the first direction.

Abstract: Techniques in dynamic routing for advanced deep learning provide improvements in one or more of accuracy, performance, and energy efficiency. An array of processing elements comprising a portion of a neural network accelerator performs flow-based computations on wavelets of data. Each processing element comprises a compute element enabled to execute programmed instructions using the data and a router enabled to route the wavelets via static routing, dynamic routing, or both. The routing is in accordance with a respective virtual channel specifier of each of the wavelets and controlled by routing configuration information of the router. The static techniques enable statically specifiable neuron connections. The dynamic techniques enable information from the wavelets to alter the routing configuration information during neural network processing.

Abstract: A tailgate deactivation system. A switch includes two terminals configured to be electrically coupled to a tailgate power circuit that supplies power to at least a portion of a tailgate of a vehicle, and an actuator configured to electrically couple the two terminals in an on state to allow power to flow in the tailgate power circuit, and to electrically decouple the two terminals in an off state to inhibit power from flowing in the tailgate power circuit.

Abstract: A tailgate deactivation system. A switch includes two terminals configured to be electrically coupled to a tailgate power circuit that supplies power to at least a portion of a tailgate of a vehicle, and an actuator configured to electrically couple the two terminals in an on state to allow power to flow in the tailgate power circuit, and to electrically decouple the two terminals in an off state to inhibit power from flowing in the tailgate power circuit.

Abstract: A system and method for flood hazard estimation inputs a satellite elevation map and applies a machine learning model to output a geographic map representing flood hazard areas. The machine learning model is trained using a generative adversarial network (GAN) to produce an output of a deterministic hazard mapping algorithm. A GAN objective applies a loss function, reweighted to increase the importance of high hazard areas. The method retrieves a DEM topography file representing elevation data of an identified terrain, and applies a sink-filling algorithm to detect and fill sinks in the DEM topography. The algorithm subtracts the DEM elevation data to generate a filled topography, and identifies flattest regions of the filled topography. The algorithm then generates a flood hazard map by merging the filled topography and the DEM elevation data, using a weighting function that balances the detected sinks and the flattest regions of the filled topography.

Abstract: Techniques in wavelet filtering for advanced deep learning provide improvements in one or more of accuracy, performance, and energy efficiency. An array of processing elements comprising a portion of a neural network accelerator performs flow-based computations on wavelets of data. Each processing element comprises a compute element to execute programmed instructions using the data and a router to route the wavelets in accordance with virtual channel specifiers. Each processing element is enabled to perform local filtering of wavelets received at the processing element, selectively, conditionally, and/or optionally discarding zero or more of the received wavelets, thereby preventing further processing of the discarded wavelets. The wavelet filtering is performed by one or more configurable wavelet filters operable in various modes, such as counter, sparse, and range modes.

Abstract: Techniques in placement of compute and memory for accelerated deep learning provide improvements in one or more of accuracy, performance, and energy efficiency. An array of processing elements comprising a portion of a neural network accelerator performs flow-based computations on wavelets of data. Each processing element comprises a compute element to execute programmed instructions using the data and a router to route the wavelets. The routing is in accordance with virtual channel specifiers of the wavelets and controlled by routing configuration information of the router. A software stack determines placement of compute resources and memory resources based on a description of a neural network. The determined placement is used to configure the routers including usage of the respective colors. The determined placement is used to configure the compute elements including the respective programmed instructions each is configured to execute.

Abstract: Techniques in dynamic routing for advanced deep learning provide improvements in one or more of accuracy, performance, and energy efficiency. An array of processing elements comprising a portion of a neural network accelerator performs flow-based computations on wavelets of data. Each processing element comprises a compute element enabled to execute programmed instructions using the data and a router enabled to route the wavelets via static routing, dynamic routing, or both. The routing is in accordance with a respective virtual channel specifier of each of the wavelets and controlled by routing configuration information of the router. The static techniques enable statically specifiable neuron connections. The dynamic techniques enable information from the wavelets to alter the routing configuration information during neural network processing.

Abstract: A tailgate deactivation system. A switch includes two terminals configured to be electrically coupled to a tailgate power circuit that supplies power to at least a portion of a tailgate of a vehicle, and an actuator configured to electrically couple the two terminals in an on state to allow power to flow in the tailgate power circuit, and to electrically decouple the two terminals in an off state to inhibit power from flowing in the tailgate power circuit.

Abstract: Techniques in wavelet filtering for advanced deep learning provide improvements in one or more of accuracy, performance, and energy efficiency. An array of processing elements comprising a portion of a neural network accelerator performs flow-based computations on wavelets of data. Each processing element comprises a compute element to execute programmed instructions using the data and a router to route the wavelets in accordance with virtual channel specifiers. Each processing element is enabled to perform local filtering of wavelets received at the processing element, selectively, conditionally, and/or optionally discarding zero or more of the received wavelets, thereby preventing further processing of the discarded wavelets. The wavelet filtering is performed by one or more configurable wavelet filters operable in various modes, such as counter, sparse, and range modes.

Abstract: A door latch clasp assembly configured for use with a door having a door latch assembly and a door latch plate is provided. The door latch clasp assembly includes a first aperture section having a first aperture. The first aperture section has an arcuate cross-sectional shape. A second aperture section has a second aperture and the second aperture section has an arcuate cross-sectional shape. An intermediate section extends from the first aperture section to the second aperture section. The intermediate section has an arcuate cross-sectional shape and a latch assembly aperture. The arcuate cross-sectional shapes of the first and the second aperture sections and the arcuate cross-sectional shape of the intermediate section are configured to approximate an arcuate cross-sectional shape of a perimeter wall of a face bore of the door.

Abstract: Techniques in advanced deep learning provide improvements in one or more of accuracy, performance, and energy efficiency, such as accuracy of learning, accuracy of prediction, speed of learning, performance of learning, and energy efficiency of learning. An array of processing elements performs flow-based computations on wavelets of data. Each processing element has a respective compute element and a respective routing element. Each compute element has processing resources and memory resources. Each router enables communication via wavelets with at least nearest neighbors in a 2D mesh. Stochastic gradient descent, mini-batch gradient descent, and continuous propagation gradient descent are techniques usable to train weights of a neural network modeled by the processing elements. Reverse checkpoint is usable to reduce memory usage during the training.

Abstract: A supporting ring for an air-suspension strut. In embodiments, a support ring has a central longitudinal axis and includes a wall. In a radially inward direction, the wall has or forms an internal-abutment geometry that projects in the radial direction, and/or, in a radially outward direction, the wall has or forms an external-abutment geometry that projects in the radial direction.

Abstract: Techniques in advanced deep learning provide improvements in one or more of accuracy, performance, and energy efficiency. An array of processing elements performs flow-based computations on wavelets of data. Each processing element has a compute element and a routing element. Each router enables communication via wavelets with at least nearest neighbors in a 2D mesh. Routing is controlled by virtual channel specifiers in each wavelet and routing configuration information in each router. Execution of an activate instruction or completion of a fabric vector operation activates one of the virtual channels. A virtual channel is selected from a pool comprising previously activated virtual channels and virtual channels associated with previously received wavelets. A task corresponding to the selected virtual channel is activated by executing instructions corresponding to the selected virtual channel.

Abstract: A tailgate stop apparatus. The apparatus includes a base member configured to be fixed with respect to a primary gate assembly of a multiple-gate tailgate. The apparatus includes a stop member coupled to the base member, wherein the stop member is movable between a tailgate-engaged position configured to inhibit an inner gate panel of an inner gate assembly of the multiple-gate tailgate from being moved to a closed position, and a tailgate-disengaged position configured to allow the inner gate panel to be moved to the closed position.