Embodiments described herein are generally directed to a configuration-driven continuous delivery (CD) pipeline that can be used by multiple development teams and integrated with multiple repositories. According to an example, all commands to be run by a particular executor used by a particular development team are specified by the pipeline. A trigger event is received from an external source specifying a repository in which source code for an application being developed or maintained by the particular development team resides. Responsive to the trigger event, the pipeline is configured with information regarding subdirectories within the repository that are to be processed based on a first set of configuration information stored in the repository. Stages of the pipeline are performed by, for each subdirectory, causing the pipeline to issue a subset of the commands to the particular executor based on a second set of configuration information associated with the subdirectory.

A fully pipelined convertToBinaryFromDecimalCharacter hardware operator logic circuit configured to convert one or more human-readable decimal character sequence floating-point representations to IEEE 754-2008 binary floating-point representations every clock cycle. The circuit converts decimal character sequence floating-point representations up to 28 decimal digits in length to IEEE 754 binary64, binary32, or binary16 floating-point format representations.

Various embodiments disclosed herein relate to hardware enabled pipeline control. In a hardware acceleration system, pipelines are configured to include a hardware enable flag that allows hardware initiation of the pipeline based on triggering of a configurable event. The pipeline can be configured to set the event that triggers the initiation of the pipeline. For example, the end of pipeline of a first pipeline may trigger the initiation of a second pipeline. Accordingly, pipelines that are configured to allow hardware enable based on a specifically configured event are not subject to the extra processing required to initiate the pipeline via software in external memory and triggered by an external controller.

A data pipeline circuit includes an upstream interface circuit that receives sequential data and a downstream interface circuit that transfers the sequential data to a downstream circuit. A ready signal indicates the downstream circuit is ready to receive the sequential data. The data pipeline circuit includes a first data latch, a second data latch and a first status latch. The first data latch receives the sequential data. The first status latch generates an available signal that is asserted to indicate the second data latch is available to receive the sequential data. The second data latch receives the sequential data in response on the available signal being asserted and the ready signal indicating the downstream circuit is not ready to receive the sequential data on the data output. Limiting conditions in which the sequential data is stored in the second data latch significantly reduces power consumption of the data pipeline circuit.

A neural processing unit (NPU) includes a controller including a scheduler, the controller configured to receive from a compiler a machine code of an artificial neural network (ANN) including a fusion ANN, the machine code including data locality information of the fusion ANN, and receive heterogeneous sensor data from a plurality of sensors corresponding to the fusion ANN; at least one processing element configured to perform fusion operations of the fusion ANN including a convolution operation and at least one special function operation; a special function unit (SFU) configured to perform a special function operation of the fusion ANN; and an on-chip memory configured to store operation data of the fusion ANN, wherein the schedular is configured to control the at least one processing element and the on-chip memory such that all operations of the fusion ANN are processed in a predetermined sequence according to the data locality information.

Systems and methods for improving cache efficiency and utilization are disclosed. In one embodiment, a graphics processor includes processing resources to perform graphics operations and a cache controller of a cache coupled to the processing resources. The cache controller is configured to control cache priority by determining whether default settings or an instruction will control cache operations for the cache.

A method of checking for a stall condition in a processor is disclosed, the method including inserting an inline instruction sequence into a thread, the inline instruction sequence configured to read the result from a timing register during processing of a first instruction and store the result in a first general purpose register, wherein the timing register functions as a timer for the processor; and read the results from the timing register during processing of a second instruction and store the results in a second general purpose register, wherein the second instruction is the next consecutive instruction after the first instruction. The inline thread sequence may be inserted in sequence with the thread and further configured to compare the difference between the result in the first and second general purpose register to a programmable threshold.

An integrated circuit, comprising an instruction pipeline that includes instruction fetch phase circuitry, instruction decode phase circuitry, and instruction execution circuitry. The instruction execution circuitry includes transformation circuitry for receiving an interleaved dual vector operand as an input and for outputting a first natural order vector including a first set of data values from the interleaved dual vector operand and a second natural order vector including a second set of data values from the interleaved dual vector operand.

Methods, apparatus, systems and articles of manufacture are disclosed to establish a data pipeline between cloud computing platforms. An example apparatus includes at least one memory, machine readable instructions in the apparatus, and processor circuitry to execute the machine readable instructions to at least extract a data producer name from data, the data to be provided from a data producer to a data consumer, identify a buffer identifier based on a mapping of the data producer name to the buffer identifier, cause transmission of the data to a buffer associated with the buffer identifier, and cause transmission of the data from the buffer to the data consumer based on an association between the buffer identifier and a data consumer name, the data consumer name corresponding to the data consumer.

A method includes receiving, by a first stage in a pipeline, a first transaction from a previous stage in pipeline; in response to first transaction comprising a high priority transaction, processing high priority transaction by sending high priority transaction to a buffer; receiving a second transaction from previous stage; in response to second transaction comprising a low priority transaction, processing low priority transaction by monitoring a full signal from buffer while sending low priority transaction to buffer; in response to full signal asserted and no high priority transaction being available from previous stage, pausing processing of low priority transaction; in response to full signal asserted and a high priority transaction being available from previous stage, stopping processing of low priority transaction and processing high priority transaction; and in response to full signal being de-asserted, processing low priority transaction by sending low priority transaction to buffer.