Abstract: A method for executing a machine code using a microprocessor includes, after an operation of decoding a current loaded instruction, constructing a mask from the signals generated by an instruction decoder in response to decoding of the current loaded instruction by the decoder. The constructed mask varies as a function of the current loaded instruction. Subsequently, before an operation of decoding a next loaded instruction, the next loaded instruction is unmasked using the constructed mask.

Abstract: A neural processing device, a processing element included therein and a method for operating various formats of the neural processing device are provided. The neural processing device includes at least one neural processor, a shared memory shared by the at least one neural processor, and a global interconnection configured to transmit data between the at least one neural processor and the shared memory, wherein each of the at least one neural processor comprises at least one processing element, each of the at least one processing element receives an input in a first format and thereby performs an operation, and receives an input in a second format that is different from the first format and thereby performs an operation if a format conversion signal is received, and the first format and the second format have a same number of bits.

Abstract: Methods and systems for executing an application data flow graph on a set of computational nodes are disclosed. The computational nodes can each include a programmable controller from a set of programmable controllers, a memory from a set of memories, a network interface unit from a set of network interface units, and an endpoint from a set of endpoints. A disclosed method comprises configuring the programmable controllers with instructions. The method also comprises independently and asynchronously executing the instructions using the set of programmable controllers in response to a set of events exchanged between the programmable controllers themselves, between the programmable controllers and the network interface units, and between the programmable controllers and the set of endpoints. The method also comprises transitioning data in the set of memories on the computational nodes in accordance with the application data flow graph and in response to the execution of the instructions.

Abstract: Stochastic hyperdimensional arithmetic computing is provided. Hyperdimensional computing (HDC) is a neurally-inspired computation model working based on the observation that the human brain operates on high-dimensional representations of data, called hypervectors. Although HDC is powerful in reasoning and association of the abstract information, it is weak on feature extraction from complex data. Consequently, most existing HDC solutions rely on expensive pre-processing algorithms for feature extraction. This disclosure proposes StocHD, a novel end-to-end hyperdimensional system that supports accurate, efficient, and robust learning over raw data. StocHD expands HDC functionality to the computing area by mathematically defining stochastic arithmetic over HDC hypervectors. StocHD enables an entire learning application (including feature extractor) to process using HDC data representation, enabling uniform, efficient, robust, and highly parallel computation.

Abstract: Described herein are systems and methods for dynamic designation of instructions as sensitive. For example, some methods include detecting that a first instruction of a first process has been designated as a sensitive instruction; checking whether a sensitive handling enable indicator in a process state register storing a state of the first process is enabled; responsive to detection of the sensitive instruction and enablement of the sensitive handling enable indicator, invoking a constraint for execution of the first instruction; executing the first instruction subject to the constraint; and executing a second instruction of the first process without the constraint.

Abstract: A processing element architecture adapted to a convolution comprises a plurality of processing elements and a delayed queue circuit. The plurality of processing elements includes a first processing element and a second processing element, wherein the first processing element and the second processing element perform the convolution according to a shared datum at least. The delayed queue circuit connects to the first processing element and connects to the second processing element. The delayed queue circuit receives the shared datum sent by the first processing element, and sends the shared datum to the second processing element after receiving the shared datum and waiting for a time interval.

Abstract: A system including one or more processors configured to receive a transpose instruction indicating to transpose a source matrix to a result matrix, provide data elements of the source matrix to input switching circuits, reorder the data elements using the input switching circuits, provide the data elements from the input switching circuits to one or more lanes of a datapath, provide the data elements from the datapath to output switching circuits, undo the reordering of the data elements using the output switching circuits, and provide the data elements from the output switching circuits to a result matrix. Each respective lane of the datapath receiving data elements receives multiple data elements directed to different respective non-overlapping portions of the lane.

Abstract: Processor-guided execution of offloaded instructions using fixed function operations is disclosed. Instructions designated for remote execution by a target device are received by a processor. Each instruction includes, as an operand, a target register in the target device. The target register may be an architected virtual register. For each of the plurality of instructions, the processor transmits an offload request in the order that the instructions are received. The offload request includes the instruction designated for remote execution. The target device may be, for example, a processing-in-memory device or an accelerator coupled to a memory.

Abstract: Systems, methods, and apparatuses relating to instructions to multiply values of one are described.

Abstract: A supplemental computing system can provide card services while saving processing power of a data center for other tasks. For example, the supplemental computing system described herein can include a processor and a memory that includes instructions that are executable by the processor to perform operations. The operations can include receiving a first subset of card requests. The operations can further include performing at least one servicing task to a card request resulting in an altered card request. Additionally, the operations can include selecting, for each altered card request in the first subset, a secondary card processor from at least one secondary card processor. The operations can also include transforming the altered card request into a secondary card processor specific card request suitable for the selected secondary card processor. The operations can include submitting the secondary card processor specific card request to the selected secondary card processor.

Abstract: Merging branch target buffer entries includes maintaining, in a branch target buffer, an entry corresponding to first branch instruction, where the entry identifies a first branch target address for the first branch instruction and a second branch target address for a second branch instruction; and accessing, based on the first branch instruction, the entry.

Abstract: Disclosed herein are embodiments related to a power efficient multi-bit storage system. In one configuration, the multi-bit storage system includes a first storage circuit, a second storage circuit, a prediction circuit, and a clock gating circuit. In one aspect, the first storage circuit updates a first output bit according to a first input bit, in response to a trigger signal, and the second storage circuit updates a second output bit according to a second input bit, in response to the trigger signal. In one aspect, the prediction circuit generates a trigger enable signal indicating whether at least one of the first output bit or the second output bit is predicted to change a state. In one aspect, the clock gating circuit generates the trigger signal based on the trigger enable signal.

Abstract: In an embodiment a system on chip includes at least one master device, at least one slave device, a connection interface configured to route signals between the at least one master device and the at least one slave device, the connection interface configured to operate according to configuration parameters, and a configuration bus connected to the connection interface, wherein the configuration bus is configured to deliver new configuration parameters to the connection interface so as to adapt operation of the connection interface.

Abstract: Systems, methods, and apparatuses relating to microarchitectural mechanisms for the prevention of side-channel attacks are disclosed herein. In one embodiment, a processor core includes an instruction fetch circuit to fetch instructions; a branch target buffer comprising a plurality of entries that each include a thread identification (TID) and a privilege level bit; and a branch predictor, coupled to the instruction fetch circuit and the branch target buffer, to predict a target instruction corresponding to a branch instruction based on at least one entry of the plurality of entries in the branch target buffer, and cause the target instruction to be fetched by the instruction fetch circuit.

Abstract: A multi-core processor configured to improve processing performance in certain computing contexts is provided. The multi-core processor includes multiple processing cores that implement barrel threading to execute multiple instruction threads in parallel while ensuring that the effects of an idle instruction or thread upon the performance of the processor is minimized. The multiple cores can also share a common data cache, thereby minimizing the need for expensive and complex mechanisms to mitigate inter-cache coherency issues. The barrel-threading can minimize the latency impacts associated with a shared data cache. In some examples, the multi-core processor can also include a serial processor configured to execute single threaded programming code that may not yield satisfactory performance in a processing environment that employs barrel threading.

Abstract: Data format conversion processing of an accelerator accessed by a processor of a computing environment is reduced. The processor and accelerator use different data formats, and the accelerator is configured to perform an input conversion to convert data from a processor data format to an accelerator data format prior to performing an operation using the data, and an output conversion to convert resultant data from accelerator data format back to processor data format after performing the operation. The reducing includes determining that adjoining operations of a process to run on the processor and accelerator are to be performed by the accelerator, where the adjoining operations include a source operation and destination operation. Further, the reducing includes blocking an output data format conversion of the source operation and an input data format conversion of the input data for the destination operation.

Abstract: A lens distortion correction function operates by backmapping output images to the uncorrected, distorted input images. As a vision image processor completes processing on the image data lines needed for the lens distortion correction function to operate on a group of output, undistorted image lines, the lens distortion correction function begins processing the image data. This improves image processing pipeline delays by overlapping the operations. The vision image processor provides output image data to a circular buffer in SRAM, rather than providing it to DRAM. The lens distortion correction function operates from the image data in the circular buffer. By operating from the SRAM circular buffer, access to the DRAM for the highly fragmented backmapping image data read operations is removed, improving available DRAM bandwidth. By using a circular buffer, less space is needed in the SRAM. The improved memory operations further improve the image processing pipeline delays.

Abstract: The present disclosure is directed to a distributed graphics processor unit (GPU) architecture that includes an array of processing nodes. Each processing node may include a GPU node that is coupled to its own fast memory unit and its own storage unit. The fast memory unit and storage unit may be integrated into a single unit or may be separately coupled to the GPU node. The processing node may have its fast memory unit coupled to both the GPU node and the storage node. The various architectures provide a GPU-based system that may be treated as a storage unit, such as solid state drive (SSD) that performs onboard processing to perform memory-oriented operations. In this respect, the system may be viewed as a “smart drive” for big-data near-storage processing.

Abstract: Techniques are disclosed for a vector processor architecture that enables data interpolation in accordance with multiple dimensions, such as one-, two-, and three-dimensional linear interpolation. The vector processor architecture includes a vector processor and accompanying vector addressable memory that enable a simultaneous retrieval of multiple entries in the vector addressable memory to facilitate linear interpolation calculations. The vector processor architecture vastly increases the speed in which such calculations may occur compared to conventional processing architectures. Example implementations include the calculation of digital pre-distortion (DPD) coefficients for use with radio frequency (RF) transmitter chains to support multi-band applications.

Abstract: A data processing apparatus comprises receiver circuitry for receiving instructions from each of a plurality of requester devices. Processing circuitry executes the instructions associated with each of a subset of the requester devices at a time and arbitration circuitry determines the subset of the requester devices and causes the instructions associated with each of the subset of the requester devices to be executed next. In response to the receiver circuitry receiving an instruction of a predetermined type from one of the requester devices outside the subset of requester devices, the arbitration circuitry causes the instruction of the predetermined type to be executed next.