A system and method are disclosed for a cache IP that includes registers that are programmed through a service port. Service registers are selected from the registers to define an address range so that all cache lines within the address range can be flushed automatically using a control signal sent to a control register.

Techniques for transferring virtual machines and resource management in a virtualized computing environment are described. In one embodiment, for example, an apparatus may include at least one memory, at least one processor, and logic for transferring a virtual machine (VM), at least a portion of the logic comprised in hardware coupled to the at least one memory and the at least one processor, the logic to generate a plurality of virtualized capability registers for a virtual device (VDEV) by virtualizing a plurality of device-specific capability registers of a physical device to be virtualized by the VM, the plurality of virtualized capability registers comprising a plurality of device-specific capabilities of the physical device, determine a version of the physical device to support via a virtual machine monitor (VMM), and expose a subset of the virtualized capability registers associated with the version to the VM. Other embodiments are described and claimed.

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.

A computing device having a tightly attached or closely attached hardware accelerator directly coupled with one or more processors for efficient uses of the hardware accelerator for executing specific functions are described. According to an embodiment, the hardware accelerator is instantiated inside the main processor unit and interfaces to a load-store unit (LS) using virtual addresses. The hardware accelerator instantiated inside the main processing unit (e.g., core) is referred to as a tightly attached hardware accelerator. In an alternative embodiment, the hardware accelerator is instantiated inside a cluster of processor cores. The hardware accelerator that is instantiated inside the cluster of processor cores but not inside a specific processor core is referred to as a closely attached hardware accelerator.

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 streaming engine employed in a digital data processor may specify a fixed read-only data stream defined by plural nested loops. An address generator produces address of data elements for the nested loops. A steam head register stores data elements next to be supplied to functional units for use as operands. A stream template register independently specifies a linear address or a circular address mode for each of the nested loops.

The present disclosure provides a computation device. The computation device is configured to perform a machine learning computation, and includes an operation unit, a controller unit, and a conversion unit. The storage unit is configured to obtain input data and a computation instruction. The controller unit is configured to extract and parse the computation instruction from the storage unit to obtain one or more operation instructions, and to send the one or more operation instructions and the input data to the operation unit. The operation unit is configured to perform operations on the input data according to one or more operation instructions to obtain a computation result of the computation instruction. In the examples of the present disclosure, the input data involved in machine learning computations is represented by fixed-point data, thereby improving the processing speed and efficiency of training operations.

Techniques are described for metadata processing that can be used to encode an arbitrary number of security policies for code running on a processor. Metadata may be added to every word in the system and a metadata processing unit may be used that works in parallel with data flow to enforce an arbitrary set of policies. In one aspect, the metadata may be characterized as unbounded and software programmable to be applicable to a wide range of metadata processing policies. Techniques and policies have a wide range of uses including, for example, safety, security, and synchronization. Additionally, described are aspects and techniques in connection with metadata processing in an embodiment based on the RISC-V architecture.

A digital data processor includes an instruction memory storing instructions specifying a data processing operation and a data operand field, an instruction decoder coupled to the instruction memory for recalling instructions from the instruction memory and determining the operation and the data operand, and an operational unit coupled to a data register file and to an instruction decoder to perform a data processing operation upon an operand corresponding to an instruction decoded by the instruction decoder and storing results of the data processing operation. The operational unit is configured to perform a table write in response to a look up table initialization instruction by duplicating at least one data element from a source data register to create duplicated data elements, and writing the duplicated data elements to a specified location in a specified number of at least one table and a corresponding location in at least one other table.

A semiconductor device including a first processor having a first register, the first processor configured to perform region of interest (ROI) calculations using the first register; and a second processor having a second register, the second processor configured to perform arithmetic calculations using the second register. The first register is shared with the second processor, and the second register is shared with the first processor.