Abstract: A method, system and apparatus for sensing data and updating statistical data. The method, system and apparatus can include one or more sensors physically located at a live sporting event that collect sensed data; a live database that receives sensor data continuously during activity in the live sporting event; a base module that continuously polls the live database, stores sensed data from any completed action in the live event in a sensed data database, and transmits the sensed data to a historical action database; a situational database that houses situational data about sensed data; and a processor that associates the situational data is with the sensed data to determine dynamic statistical data.

Abstract: The present disclosure describes apparatuses and methods for implementing a pipelined processor with configurable grouping of processor elements. In aspects, an apparatus comprises a host interface configured for communication with a host system, a media interface configured to enable access to storage media, and a plurality of processor elements operably coupled to at least one of the host interface and the media interface. The plurality of processor elements is organized into multiple stages of a pipelined processor for processing data access commands associated with the host system. In various implementations, the plurality of processor elements can be selectively grouped to form the multiple stages of the pipelined processor and loaded with microcode to implement respective functions of each stage of the pipelined processor. By so doing, the pipelined processor may be configured based on various parameters to improve processing performance when processing the data access commands of the host system.

Abstract: A recursive divide operation is performed on a logical address for a predetermined number of iterations. On each iteration of the recursive divide operation, a respective component of a physical address represented by the logical address is derived. The physical address corresponding to the logical address is the constructed from the derived components.

Abstract: A computer system manages the allocation of memory to an application program using a dependency tree. The dependency tree informs a memory manager of data inputs, data outputs, and intermediate values associated with execution of the application program. The memory manager allocates a single heap structure within a physical memory. Data associated with each node of the dependency tree is allocated to the heap structure so that data input values are allocated in a contiguous block, and intermediate values are allocated separately. In various examples, as execution of the application program proceeds, the separation of intermediate values from non-intermediate values within the heap reduces memory fragmentation providing improved performance of the computer system as a whole.

Abstract: A computer system manages the allocation of memory to an application program using a dependency tree. The dependency tree informs a memory manager of data inputs, data outputs, and intermediate values associated with execution of the application program. The memory manager allocates a single heap structure within a physical memory. Data associated with each node of the dependency tree is allocated to the heap structure so that data input values are allocated in a contiguous block, and intermediate values are allocated separately. In various examples, as execution of the application program proceeds, the separation of intermediate values from non-intermediate values within the heap reduces memory fragmentation providing improved performance of the computer system as a whole.

Abstract: A method for graphically displaying data. The method can include sensing a position of a ball on a field using one or more sensors during a live sporting event; sensing human movement and location information using one or more sensors in the live sporting event; determining positioning information of one or more players based on the sensed human movement and location information and the sensed ball position on the field; and generating graphical indica on a transmitted broadcast of the live sporting event, the graphical indica showing a generated graphic of at least one of positioning information and ball position on the field.

Abstract: A method, system, and apparatus for a live sporting event broadcast system. Embodiments include one or more video cameras that record the live sporting event; one or more sensors that track movement of one or more players in the live sporting event; one or more sensors that track location data of one or more pieces of equipment used in the live sporting event; at least one processor configured to: determine and/or track situational data of the live sporting event and synchronizes the tracked player movement and location data of the one or more pieces of equipment with the tracked situational data, compare the synchronized tracked player movement and the tracked location data of the one or more pieces of equipment with historical data, and determine at least an expected player movement in an upcoming action in the live event; a video highlight that is displayed on a broadcast transmission stream.

Abstract: A method, system and apparatus for sensing data and updating statistical data. The method, system and apparatus can include one or more sensors physically located at a live sporting event that collect sensed data; a live database that receives sensor data continuously during activity in the live sporting event; a base module that continuously polls the live database, stores sensed data from any completed action in the live event in a sensed data database, and transmits the sensed data to a historical action database; a situational database that houses situational data about sensed data; and a processor that associates the situational data is with the sensed data to determine dynamic statistical data.

Abstract: A method, system, and apparatus for tracking actions in a live event. Embodiments can include one or more cameras located at the live event, the one or more cameras each focused on at least one of a player participating in the live event or equipment used in the live event, and one or more cameras collect sensed movement data regarding the at least one player or the equipment; and a processor that receives transmitted sensed movement data, compares the sensed movement data to historical movement data in a database, and determines a predicted movement of the at least one player or equipment in the live event. Further, the historical movement data in the database is updated in substantially real time after the collection of the sensed movement data by the one or more cameras.

Abstract: The present disclosure describes apparatuses and methods for implementing a pipelined processor with configurable grouping of processor elements. In aspects, an apparatus comprises a host interface configured for communication with a host system, a media interface configured to enable access to storage media, and a plurality of processor elements operably coupled to at least one of the host interface and the media interface. The plurality of processor elements is organized into multiple stages of a pipelined processor for processing data access commands associated with the host system. In various implementations, the plurality of processor elements can be selectively grouped to form the multiple stages of the pipelined processor and loaded with microcode to implement respective functions of each stage of the pipelined processor. By so doing, the pipelined processor may be configured based on various parameters to improve processing performance when processing the data access commands of the host system.

Abstract: A method, system, and apparatus for generating probabilities, for example for displaying on a video feed, which may be generated or adjusted using machine learning and/or artificial intelligence. One embodiment includes a method for generating and adjusting probabilities. the generated probabilities in order to create and display probability graphics on a display device. The graphics may be generated and/or updated using artificial intelligence or machine learning. Display information may be updated in real-time as changes are made in the game (e.g. a player injury, substitutions, changing weather conditions, etc.). The changes may be detected by a detection system on the field, attached to players or equipment.

Abstract: A method, system, and apparatus for generating probabilities, for example for displaying on a video feed, which may be generated or adjusted using machine learning and/or artificial intelligence. One embodiment includes a method for generating and adjusting probabilities. the generated probabilities in order to create and display probability graphics on a display device. The graphics may be generated and/or updated using artificial intelligence or machine learning. Display information may be updated in real-time as changes are made in the game (e.g. a player injury, substitutions, changing weather conditions, etc.). The changes may be detected by a detection system on the field, attached to players or equipment.

Abstract: A computation graph is accessed. In the computation graph, operations to be performed are represented as interior nodes, inputs to the operations are represented as leaf nodes, and a result of the operations is represented as a root. Selected sets of the operations are combined to form respective kernels of operations. Code is generated execute the kernels of operations. The code is executed to determine the result.

Abstract: System and method of compiling a program having a mixture of host code and device code to enable Profile Guided Optimization (PGO) for device code execution. An exemplary integrated compiler can compile source code programmed to be executed by a host processor (e.g., CPU) and a co-processor (e.g., a GPU) concurrently. The compilation can generate an instrumented executable code which includes: profile instrumentation counters for the device functions; and instructions for the host processor to allocate and initialize device memory for the counters and to retrieve collected profile information from the device memory to generate instrumentation output. The output is fed back to the compiler for compiling the source code a second time to generate optimized executable code for the device functions defined in the source code.

Abstract: Systems and methods for automated monitoring and troubleshooting of unknown dependencies in a virtual infrastructure are disclosed. In particular, systems and methods disclosed herein enable automation of processes for detecting network errors for virtual machines residing on virtual infrastructures and retrieving network addresses and physical ports associated with the errors. Aspects of the technology use the IEEE MAC address of the virtual instance to triage the L2 connectivity to determine the physical port to which the virtual instance is attached and then automatically report the port to the network operator. The system also provides a method of saving virtual instances that are in a faulty state so that instances can be investigated further by automated monitoring tools.

Abstract: Disclosed is a distributed storage system and methods for providing real-time localized data access from different storage nodes of the distributed storage system. Providing the localized data access may include tracking access frequencies with which a file is directly accessed from the different storage nodes, storing a source copy of the file at the first storage node in response to the access frequency at the first storage node being greater than the access frequency at the other storage nodes, caching the file at a second storage node, transferring control over the source copy from the first storage node to a third storage node based on a change to the access frequencies, and validating the cached copy of the file at the second storage node against the source copy at the third storage node prior to responding to a request for the file from the second storage node.

Abstract: Provided is a predictive read ahead system for dynamically prefetching content from different storage devices. The dynamic prefetching may include receiving requests to read a first set of data of first content from a first storage device at a first rate, and requests to read a first set of data of second content from a second storage device at a different second rate. The dynamic prefetching may include determining different performance for the first storage device than the second storage device, prioritizing an allocation of cache based on a first difference between the first rate and the second rate, and a second difference based on the different performance between the storage devices, and prefetching a first amount of the first content data from the first storage device and a different second amount of the second content data from the second storage device based on the first and second differences.

Abstract: Methods, systems, and devices for training and verification of learning models are described. A device may capture a camera frame including a road feature of a physical environment, determine a first classification and a first localization of the road feature based on positioning information of the road feature from a high-definition map and positioning information of the device from a positioning engine. The device may analyze a learning model by comparing one or more of the first classification of the road feature or the first localization of the road feature in the camera frame to one or more of a second classification or a second localization of the road feature determined by the learning model. The device may then determine a loss comparison value and adapt the learning model according to the loss comparison value.

Abstract: Disclosed is a distributed storage system and methods for providing real-time localized data access from different storage nodes of the distributed storage system. Providing the localized data access may include tracking access frequencies with which a file is directly accessed from the different storage nodes, storing a source copy of the file at the first storage node in response to the access frequency at the first storage node being greater than the access frequency at the other storage nodes, caching the file at a second storage node, transferring control over the source copy from the first storage node to a third storage node based on a change to the access frequencies, and validating the cached copy of the file at the second storage node against the source copy at the third storage node prior to responding to a request for the file from the second storage node.

Abstract: An asynchronous storage system may perform asynchronous writing of data from different sets of received non-consecutive synchronous write requests based on a dynamic write threshold that varies according to parameters of the storage device and/or synchronous write request patterns. The asynchronous writing may include coalescing data from a set of non-consecutive write requests in a plurality of received write requests that contain different data for a particular file, issuing a single asynchronous write request with the data that is coalesced from each write request of the set of non-consecutive write requests to the storage device instead of each write request of the set of non-consecutive write requests, and writing the data that is coalesced from each write request of the set of non-consecutive write requests to the storage device with a single write operation that is executed in response to the single asynchronous write request.