Abstract: Materials with etch selectivity with respect to one another and one or more additional etch-stop layers are used in a Josephson junction structure to allow for integration with a Josephson junction with supporting structures such as resistors. Selective etch processes compatible with high volume manufacturing are used to pattern various layers of the Josephson junction structure to provide a Josephson junction, which is electrically coupled to a support structure.

Abstract: Approaches in accordance with various embodiments provide for the processing of sparse matrices for mathematical and programmatic operations. In particular, various embodiments enforce sparsity constraints for performing sparse matrix multiply-add instruction (MMA) operations. Deep neural networks can exhibit significant sparsity in the data used in operations, both in the activations and weights. The computational load can be reduced by excluding zero-valued data elements. A sparsity constraint is applied across all submatrices of a sparse matrix, providing fine-grained structured sparsity that is evenly distributed across the matrix. The matrix may then be compressed since a minimum number of elements of the matrix are known to have zero value. Matrix operations are then performed using these matrices.

Abstract: An integrated circuit such as, for example a graphics processing unit (GPU), includes a dynamic power controller for adjusting operating voltage and/or frequency. The controller may receive current power used by the integrated circuit and a predicted power determined based on instructions pending in a plurality of processors. The controller determines adjustments that need to be made to the operating voltage and/or frequency to minimize the difference between the current power and the predicted power. An in-system reinforced learning mechanism is included to self-tune parameters of the controller.

Abstract: Failover methods and systems for a networked storage environment are provided. A filtering data structure and a metadata data structure are generated before starting a replay of a log stored in a non-volatile memory of a second storage node, during a failover operation initiated in response to a failure at a first storage node. The second storage node operates as a partner node of the first storage node to mirror at the log one or more write requests received by the first storage node prior to the failure, and data associated with the one or more write requests. The filtering data structure identifies each log entry and the metadata structure stores a metadata attribute of each log entry. The filtering data structure and the metadata structure are used for providing access to a logical storage object during the log replay from the second storage node.

Abstract: An application may store data to a dataset comprising a plurality of volumes stored on a plurality of storage systems. The application may request a dataset image of the dataset, the dataset image comprising a volume image of each volume of the dataset. A dataset image manager operates with a plurality of volume image managers in parallel to produce the dataset image, each volume image manager executing on a storage system. The plurality of volume image managers respond by performing requested operations and sending responses to the dataset image manager in parallel. Each volume image manager on a storage system may manage and produce a volume image for each volume of the dataset stored to the storage system. If a volume image for any volume of the dataset fails, or a timeout period expires, a cleanup procedure is performed to delete any successful volume images.

Abstract: Failover methods and systems for a networked storage environment are provided. A filtering data structure and a metadata data structure are generated before starting a replay of a log stored in a non-volatile memory of a second storage node, during a failover operation initiated in response to a failure at a first storage node. The second storage node operates as a partner node of the first storage node to mirror at the log one or more write requests received by the first storage node prior to the failure, and data associated with the one or more write requests. The filtering data structure identifies each log entry and the metadata structure stores a metadata attribute of each log entry. The filtering data structure and the metadata structure are used for providing access to a logical storage object during the log replay from the second storage node.

Abstract: A technique for block data transfer is disclosed that reduces data transfer and memory access overheads and significantly reduces multiprocessor activity and energy consumption. Threads executing on a multiprocessor needing data stored in global memory can request and store the needed data in on-chip shared memory, which can be accessed by the threads multiple times. The data can be loaded from global memory and stored in shared memory using an instruction which directs the data into the shared memory without storing the data in registers and/or cache memory of the multiprocessor during the data transfer.

Abstract: An application may store data to a dataset comprising a plurality of volumes stored on a plurality of storage systems. The application may request a dataset image of the dataset, the dataset image comprising a volume image of each volume of the dataset. A dataset image manager operates with a plurality of volume image managers in parallel to produce the dataset image, each volume image manager executing on a storage system. The plurality of volume image managers respond by performing requested operations and sending responses to the dataset image manager in parallel. Each volume image manager on a storage system may manage and produce a volume image for each volume of the dataset stored to the storage system. If a volume image for any volume of the dataset fails, or a timeout period expires, a cleanup procedure is performed to delete any successful volume images.

Abstract: An application may store data to a dataset comprising a plurality of volumes stored on a plurality of storage systems. The application may request a dataset image of the dataset, the dataset image comprising a volume image of each volume of the dataset. A dataset image manager operates with a plurality of volume image managers in parallel to produce the dataset image, each volume image manager executing on a storage system. The plurality of volume image managers respond by performing requested operations and sending responses to the dataset image manager in parallel. Each volume image manager on a storage system may manage and produce a volume image for each volume of the dataset stored to the storage system. If a volume image for any volume of the dataset fails, or a timeout period expires, a cleanup procedure is performed to delete any successful volume images.

Abstract: A technique for block data transfer is disclosed that reduces data transfer and memory access overheads and significantly reduces multiprocessor activity and energy consumption. Threads executing on a multiprocessor needing data stored in global memory can request and store the needed data in on-chip shared memory, which can be accessed by the threads multiple times. The data can be loaded from global memory and stored in shared memory using an instruction which directs the data into the shared memory without storing the data in registers and/or cache memory of the multiprocessor during the data transfer.

Abstract: A technique for block data transfer is disclosed that reduces data transfer and memory access overheads and significantly reduces multiprocessor activity and energy consumption. Threads executing on a multiprocessor needing data stored in global memory can request and store the needed data in on-chip shared memory, which can be accessed by the threads multiple times. The data can be loaded from global memory and stored in shared memory using an instruction which directs the data into the shared memory without storing the data in registers and/or cache memory of the multiprocessor during the data transfer.

Abstract: A just-in-time (JIT) compiler binds constants to specific memory locations at runtime. The JIT compiler parses program code derived from a multithreaded application and identifies an instruction that references a uniform constant. The JIT compiler then determines a chain of pointers that originates within a root table specified in the multithreaded application and terminates at the uniform constant. The JIT compiler generates additional instructions for traversing the chain of pointers and inserts these instructions into the program code. A parallel processor executes this compiled code and, in doing so, causes a thread to traverse the chain of pointers and bind the uniform constant to a uniform register at runtime. Each thread in a group of threads executing on the parallel processor may then access the uniform constant.

Abstract: A compiler parses a multithreaded application into cohesive blocks of instructions. Cohesive blocks include instructions that do not diverge or converge. Each cohesive block is associated with one or more uniform registers. When a set of threads executes the instructions in a given cohesive block, each thread in the set may access the uniform register independently of the other threads in the set. Accordingly, the uniform register may store a single copy of data on behalf of all threads in the set of threads, thereby conserving resources.

Abstract: Systems and methods for change in language-based textual analysis are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for change in language-based textual analysis may include: (1) retrieving, from a data source, a first document of a first type; (2) retrieving, from the data source, a second document of the first type, the second document being subsequent in time to the first document; (3) identifying changes between the first document and the second document; (4) calculating a change score based on the changes; and (5) providing the change score to a downstream system for projecting a performance of an investment associated with the first document.

Abstract: An application may store data to a dataset comprising a plurality of volumes stored on a plurality of storage systems. The application may request a dataset image of the dataset, the dataset image comprising a volume image of each volume of the dataset. A dataset image manager operates with a plurality of volume image managers in parallel to produce the dataset image, each volume image manager executing on a storage system. The plurality of volume image managers respond by performing requested operations and sending responses to the dataset image manager in parallel. Each volume image manager on a storage system may manage and produce a volume image for each volume of the dataset stored to the storage system. If a volume image for any volume of the dataset fails, or a timeout period expires, a cleanup procedure is performed to delete any successful volume images.

Abstract: An integrated circuit such as, for example a graphics processing unit (GPU), includes a dynamic power controller for adjusting operating voltage and/or frequency. The controller may receive current power used by the integrated circuit and a predicted power determined based on instructions pending in a plurality of processors. The controller determines adjustments that need to be made to the operating voltage and/or frequency to minimize the difference between the current power and the predicted power. An in-system reinforced learning mechanism is included to self-tune parameters of the controller.

Abstract: In some aspects, the disclosure is directed to methods and systems for controlling a set top box remotely and monitoring its display output. Remote control commands may be intercepted or captured and forwarded over a network as encapsulated serial data or HDMI-CEC, in some implementations. This data may be transmitted over a network to a processing device, sometimes referred to as an HDMI pass-through and streamer device. The HDMI pass-through device may receive the encapsulated serial data via the network and retransmit the data as CEC data over HDMI to the set top box as if it were any other HDMI capable device, such as a television. Thus, the recipient set top box may receive the remote control commands via CEC and treat them as incoming IR commands and act accordingly.

Abstract: An application may store data to a dataset comprising a plurality of volumes stored on a plurality of storage systems. The application may request a dataset image of the dataset, the dataset image comprising a volume image of each volume of the dataset. A dataset image manager operates with a plurality of volume image managers in parallel to produce the dataset image, each volume image manager executing on a storage system. The plurality of volume image managers respond by performing requested operations and sending responses to the dataset image manager in parallel. Each volume image manager on a storage system may manage and produce a volume image for each volume of the dataset stored to the storage system. If a volume image for any volume of the dataset fails, or a timeout period expires, a cleanup procedure is performed to delete any successful volume images.

Abstract: An application may store data to a dataset comprising a plurality of volumes stored on a plurality of storage systems. The application may request a dataset image of the dataset, the dataset image comprising a volume image of each volume of the dataset. A dataset image manager operates with a plurality of volume image managers in parallel to produce the dataset image, each volume image manager executing on a storage system. The plurality of volume image managers respond by performing requested operations and sending responses to the dataset image manager in parallel. Each volume image manager on a storage system may manage and produce a volume image for each volume of the dataset stored to the storage system. If a volume image for any volume of the dataset fails, or a timeout period expires, a cleanup procedure is performed to delete any successful volume images.

Abstract: An application may store data to a dataset comprising a plurality of volumes stored on a plurality of storage systems. The application may request a dataset image of the dataset, the dataset image comprising a volume image of each volume of the dataset. A dataset image manager operates with a plurality of volume image managers in parallel to produce the dataset image, each volume image manager executing on a storage system. The plurality of volume image managers respond by performing requested operations and sending responses to the dataset image manager in parallel. Each volume image manager on a storage system may manage and produce a volume image for each volume of the dataset stored to the storage system. If a volume image for any volume of the dataset fails, or a timeout period expires, a cleanup procedure is performed to delete any successful volume images.