Systems and techniques that facilitate automated recommendation of microservice decomposition strategies for monolithic applications are provided. In various embodiments, a community detection component can detect a disjoint code cluster in a monolithic application based on a code property graph characterizing the monolithic application. In various aspects, the code property graph can be based on a temporal code evolution of the monolithic application. In various embodiments, a topic modeling component can identify a functional purpose of the disjoint code cluster based on a business document corpus corresponding to the monolithic application. In various embodiments, a microservices component can recommend a microservice to replace the disjoint code cluster based on the functional purpose.

The present disclosure includes apparatuses and methods related to microcode instructions indicating instruction types. One example apparatus comprises a memory storing a set of microcode instructions. Each microcode instruction of the set can comprise a first field comprising a number of control data units, and a second field comprising a number of type select data units. Each microcode instruction of the set can have a particular instruction type defined by a value of the number of type select data units, and particular functions corresponding to the number of control data units are variable based on the particular instruction type.

Embodiments relate to a computer system, computer program product, and computer-implemented method to train a machine learning (ML) model using artificial intelligence to learn an association between (regulatory) compliance requirements and features of micro-service training datasets. The trained ML model is leveraged to determine the compliance requirements of a micro-service requiring classification. In an exemplary embodiment, once the micro-service has been classified with respect to applicable compliance requirements, the classified micro-service may be used as an additional micro-service training dataset to further train the ML model and thereby improve its performance.

An apparatus has a processing pipeline, and first and second register files. A temporary-register-using instruction is supported which controls the pipeline to perform an operation using a temporary variable derived from an operand stored in the first register file. In response to the instruction, when a predetermined condition is not satisfied, the pipeline processes at least one register move micro-operation to transfer data from the at least one source register of the first register file to at least one newly allocated temporary register of the second register file. When the condition is satisfied, the operation can be performed using a temporary variable already stored in the temporary register of the second register file used by an earlier temporary-register-using instruction specifying the same source register for determining the temporary variable, in the absence of an intervening instruction for rewriting the source register.

A 3D NAND memory device is provided in which control is performed by two microcontroller units (MCU). During manufacture of the memory device, bug fixes required for the controller may be addressed using a software solution by which an instruction requiring correction in one of the two MCUs is replaced with a corrected instruction stored in a RAM.

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.

Provided is an arithmetic processing to reduce a number of parts as it is not necessary to prepare an operation device for each input processing logic. A plurality of types of input processing logics is stored in the ROM, and CPU selects one of the plurality of types of input processing logics and executes input processing according to the selected input processing logic. As a result, there is no need to prepare the ECU for each input processing logic, reducing the number of parts.

An instruction execution device includes a processor. The processor includes an instruction translator, a reorder buffer, an architecture register, and an execution unit. The instruction translator receives a macro-instruction and translates the macro-instruction into a first micro-instruction, a second micro-instruction and a third micro-instruction. The instruction translator marks the first micro-instruction and the second micro-instruction with the same atomic operation flag. The execution unit executes the first micro-instruction to generate a first execution result and to store the first execution result in a temporary register. The execution unit executes the second micro-instruction to generate a second execution result and to store the second execution result in the architecture register. The execution unit executes the third micro-instruction to read the first execution result from the temporary register and to store the first execution result in the architecture register.

A device that includes a parsing engine and an execution engine. The parsing engine is configured to identify micro operations corresponding with operations that are common among at least two jobs from a set of jobs and to store the identified micro operations in memory. The execution engine is configured to receive a job from the set of jobs, to identity micro operations and dependencies within the job, and to execute the identified micro operations for the job in accordance with the identified dependencies.

The present disclosure includes apparatus and methods for debugging on a host and memory device. An example apparatus comprises a memory device having an array of memory cells. Sensing circuitry is coupled to the array. The sensing circuitry includes a sense amplifier and a compute component configured to perform logical operations on the memory device. A controller is coupled to the array and sensing circuitry to control performance of the logical operations. An interface is configured to receive a debugging indication and to cause the controller to halt a logical operation on the memory device.