Disclosed embodiments relate to systems for performing instructions to quickly convert and use matrices (tiles) as one-dimensional vectors. In one example, a processor includes fetch circuitry to fetch an instruction having fields to specify an opcode, locations of a two-dimensional (2D) matrix and a one-dimensional (1D) vector, and a group of elements comprising one of a row, part of a row, multiple rows, a column, part of a column, multiple columns, and a rectangular sub-tile of the specified 2D matrix, and wherein the opcode is to indicate a move of the specified group between the 2D matrix and the 1D vector, decode circuitry to decode the fetched instruction; and execution circuitry, responsive to the decoded instruction, when the opcode specifies a move from 1D, to move contents of the specified 1D vector to the specified group of elements.

A method for sorting of a vector in a processor is provided that includes performing, by the processor in response to a vector sort instruction, generating a control input vector for vector permutation logic comprised in the processor based on values in lanes of the vector and a sort order for the vector indicated by the vector sort instruction and storing the control input vector in a storage location.

In various examples, a VPU and associated components may be optimized to improve VPU performance and throughput. For example, the VPU may include a min/max collector, automatic store predication functionality, a SIMD data path organization that allows for inter-lane sharing, a transposed load/store with stride parameter functionality, a load with permute and zero insertion functionality, hardware, logic, and memory layout functionality to allow for two point and two by two point lookups, and per memory bank load caching capabilities. In addition, decoupled accelerators may be used to offload VPU processing tasks to increase throughput and performance, and a hardware sequencer may be included in a DMA system to reduce programming complexity of the VPU and the DMA system. The DMA and VPU may execute a VPU configuration mode that allows the VPU and DMA to operate without a processing controller for performing dynamic region based data movement operations.

A Very Long Instruction Word (VLIW) digital signal processor particularly adapted for single instruction multiple data (SIMD) operation on various operand widths and data sizes. A vector compare instruction compares first and second operands and stores compare bits. A companion vector conditional instruction performs conditional operations based upon the state of a corresponding predicate data register bit. A predicate unit performs data processing operations on data in at least one predicate data register including unary operations and binary operations. The predicate unit may also transfer data between a general data register file and the predicate data register file.

Methods and systems for allowing software components that operate at a specific exception level (e.g., EL-3 to EL-1, etc.) to repeatedly or continuously observe or evaluate the integrity of software components operating at a lower exception level (e.g., EL-2 to EL-0) to ensure that the software components have not been corrupted or compromised (e.g., subjected to malware, cyberattacks, etc.) include a computing device that identifies, by a component operating at a higher exception level (“HEL component”), at least one of a current vector base address (VBA), an exception raising instruction (ERI) address, or a control and system register value associated with a component operating at a lower exception level (“LEL component”). The computing device may perform a responsive action in response to determining that the current VBA, the ERT address, or control and system register value do not match the corresponding reference data.

Systems and methods related to implementing vector registers in memory. A memory system for implementing vector registers in memory can include an array of memory cells, where a plurality of rows in the array serve as a plurality of vector registers as defined by an instruction set architecture. The memory system for implementing vector registers in memory can also include a processing resource configured to, responsive to receiving a command to perform a particular vector operation on a particular vector register, access a particular row of the array serving as the particular register to perform the vector operation.

Various techniques for accelerating Smith-Waterman sequence alignments are provided. For example, threads in a group of threads are employed to use an interleaved cell layout to store relevant data in registers while computing sub-alignment data for one or more local alignment problems. In another example, specialized instructions that reduce the number of cycles required to compute each sub-alignment score are utilized. In another example, threads are employed to compute sub-alignment data for a subset of columns of one or more local alignment problems while other threads begin computing sub-alignment data based on partial result data received from the preceding threads. After computing a maximum sub-alignment score, a thread stores the maximum sub-alignment score and the corresponding position in global memory.

In various examples, a VPU and associated components may be optimized to improve VPU performance and throughput. For example, the VPU may include a min/max collector, automatic store predication functionality, a SIMD data path organization that allows for inter-lane sharing, a transposed load/store with stride parameter functionality, a load with permute and zero insertion functionality, hardware, logic, and memory layout functionality to allow for two point and two by two point lookups, and per memory bank load caching capabilities. In addition, decoupled accelerators may be used to offload VPU processing tasks to increase throughput and performance, and a hardware sequencer may be included in a DMA system to reduce programming complexity of the VPU and the DMA system. The DMA and VPU may execute a VPU configuration mode that allows the VPU and DMA to operate without a processing controller for performing dynamic region based data movement operations.

Vector sort circuits that can be used to accelerate sorting operations in a vector processor. When a new data element is received, the vector sort circuit can read multiple existing data elements from a vector-sort database in parallel, compare metrics of the existing data elements to a metric of the new data element, and output updated data elements to the vector-sort database based on the metrics. Depending on implementation, the vector-sort database can be maintained in sorted order, or the data elements can have assigned ranks indicating the sort order and the elements need not be stored in sorted order. A vector sort circuit can be incorporated into a vector sort functional unit of a microprocessor, and the instruction set of the microprocessor can include instructions that are executed by the vector sort functional unit using the vector sort circuit.

Methods, systems and apparatuses for performing walk operations of single instruction, multiple data (SIMD) instructions are disclosed. One method includes initiating, by a scheduler, a SIMD thread, where the scheduler is operative to schedule the SIMD thread. The method further includes fetching a plurality of instructions for the SIMD thread. The method further includes determining, by a thread arbiter, at least one instruction that is a walk instruction, where the walk instruction iterates a block of instructions for a subset of channels of the SIMD thread, where the walk instruction includes a walk size, and where the walk size is a number of channels in the subset of channels of the SIMD thread that are processed in a walk iteration in association with the walk instruction. The method further includes executing the walk instruction based on the walk size.