Processing circuitry performs data processing operations in response to instructions fetched from a cache or memory or micro-operations decoded from the instructions. Sampling circuitry selects a subset of instructions or micro-operations as sampled operations to be profiled. Profiling circuitry captures, in response to processing of an instruction or micro-operation selected as a sampled operation, a sample record specifying an operation type of the sampled operation and information about behaviour of the sampled operation which is directly attributed to the sampled operation. The profiling circuitry can include, in the sample record for a sampled operation corresponding to a given instruction, a reference instruction address indicator indicative of an address of a reference instruction appearing earlier or later in program order than the given instruction, for which control flow is sequential between any instructions occurring between the reference instruction and the given instruction in program order.

A non-volatile memory apparatus and corresponding method of operation are provided. The apparatus includes non-volatile memory cells in an integrated circuit device along with a microcontroller in communication with the non-volatile memory cells. The microcontroller is configured to receive a memory operation command and in response, determine a condition value of one of a plurality of conditions associated with the memory operation command and whether the one of the plurality of conditions is dynamic. In parallel, the microcontroller determines and outputs an output value using the condition value. The microcontroller then determines whether the one the plurality of conditions has changed. If the one of the plurality of conditions is dynamic and has changed, the microcontroller determines an updated condition value and in parallel, compares the condition value and the updated condition value and determines and outputs an updated output value using the updated condition value and the comparison.

A non-volatile memory apparatus and corresponding method of operation are provided. The apparatus includes non-volatile memory cells in an integrated circuit device along with a microcontroller in communication with the non-volatile memory cells. The microcontroller is configured to receive a memory operation command and in response, determine a condition value of one of a plurality of conditions associated with the memory operation command and whether the one of the plurality of conditions is dynamic. In parallel, the microcontroller determines and outputs an output value using the condition value. The microcontroller then determines whether the one the plurality of conditions has changed. If the one of the plurality of conditions is dynamic and has changed, the microcontroller determines an updated condition value and in parallel, compares the condition value and the updated condition value and determines and outputs an updated output value using the updated condition value and the comparison.

A prefetcher for a coprocessor is disclosed. An apparatus includes a processor and a coprocessor that are configured to execute processor and coprocessor instructions, respectively. The processor and coprocessor instructions appear together in code sequences fetched by the processor, with the coprocessor instructions being provided to the coprocessor by the processor. The apparatus further includes a coprocessor prefetcher configured to monitor a code sequence fetched by the processor and, in response to identifying a presence of coprocessor instructions in the code sequence, capture the memory addresses, generated by the processor, of operand data for coprocessor instructions. The coprocessor is further configured to issue, for a cache memory accessible to the coprocessor, prefetches for data associated with the memory addresses prior to execution of the coprocessor instructions by the coprocessor.

Rescheduling a load instruction based on past replays is disclosed. A load replay predictor of a processor device determines, at a first time, that a load instruction is scheduled to be executed by a load store unit to load data from a memory location. The load replay predictor accesses load replay data associated with a previous replay of the load instruction and, based on the load replay data, causes the load instruction to be rescheduled.

Rescheduling a load instruction based on past replays is disclosed. A load replay predictor of a processor device determines, at a first time, that a load instruction is scheduled to be executed by a load store unit to load data from a memory location. The load replay predictor accesses load replay data associated with a previous replay of the load instruction and, based on the load replay data, causes the load instruction to be rescheduled.

A processor includes a first level register file, second level register file, and register file mapper. The first and second level register files are comprised of physical registers, with the first level register file more efficiently accessed relative to the second level register file. The register file mapper is coupled with the first and second level register files. The register file mapper comprises a mapping structure and register file mapper controller. The mapping structure hosts mappings between logical registers and physical registers of the first level register file. The register file mapper controller determines whether to map a destination logical register of an instruction to a physical register in the first level register file. The register file mapper controller also determines, based on metadata associated with the instruction, whether to write data associated with the destination logical register to one of the physical registers of the second level register file.

In one embodiment of the present invention, a programmable vision accelerator enables applications to collapse multi-dimensional loops into one dimensional loops. In general, configurable components included in the programmable vision accelerator work together to facilitate such loop collapsing. The configurable elements include multi-dimensional address generators, vector units, and load/store units. Each multi-dimensional address generator generates a different address pattern. Each address pattern represents an overall addressing sequence associated with an object accessed within the collapsed loop. The vector units and the load store units provide execution functionality typically associated with multi-dimensional loops based on the address pattern. Advantageously, collapsing multi-dimensional loops in a flexible manner dramatically reduces the overhead associated with implementing a wide range of computer vision algorithms. Consequently, the overall performance of many computer vision applications may be optimized.

Embodiments of the invention are directed to updating a dynamic library. Aspects include receiving an indication that the dynamic library has been updated and identifying all program modules that depend on the dynamic library. Aspects also include, for each program module that depends on the dynamic library, reassigning an application program interface (API) address for a current version of the dynamic library to an API address of the updated version of the dynamic library.

Embodiments of the invention are directed to updating a dynamic library. Aspects include receiving an indication that the dynamic library has been updated and identifying all program modules that depend on the dynamic library. Aspects also include, for each program module that depends on the dynamic library, reassigning an application program interface (API) address for a current version of the dynamic library to an API address of the updated version of the dynamic library.