Disclosed are various examples of providing provide efficient waiting for detection of memory value updates for Advanced RISC Machines (ARM) architectures. An ARM processor component instructs a memory agent to perform a processing action, and executes a waiting function. The waiting function ensures that the processing action is completed by the memory agent. The waiting function performs an exclusive load at a memory location, and a wait for event (WFE) instruction that causes the ARM processor component to wait in a low-power mode for an event register to be set. Once the event register is set, the waiting function completes and a second processing action is executed by the ARM processor component.

A compute-in-memory (CIM) macro device and an electronic device are proposed. The CIM macro device includes a CIM cell array including multiple CIM cells. First data is being divided into at least two bit groups including a first bit group which is the most significant bits of the first data and a second bit group which is the least significant bits of the first data, and the bit groups are respectively loaded in CIM cells of different columns of the CIM cell array. The electronic device includes at least one CIM macro and at least one processing circuit. The processing circuit is configured to receive and perform operation on parallel outputs respectively corresponding to the columns of the CIM cell array, where the parallel outputs include multiple correspondences, and where each of the correspondences includes most significant bits of an output activation and least significant bits of the output activation.

An integrated circuit includes a safety processor and a secure computing module including a secure processor, first and second cryptographic units for encrypting and decrypting data, and first and second data transfer units for transferring data between a memory and the first and second cryptographic units respectively. The first cryptographic unit and the first data transfer unit provide a first cryptographic data handling system and the second cryptographic unit and the second data transfer unit provide a second cryptographic data handling system. The secure computing module includes selector circuitry for selectively coupling and uncoupling the first and second cryptographic units in response to control signals from a switch. In a first mode, the first and second cryptographic data handling systems are uncoupled and operable independently of each other. In a second mode, the first and second cryptographic data handling system are coupled and operable together to provide hardware redundancy.

A field programmable gate array (FPGA) device including a configuration interface arranged to receive configuration data from an FPGA programmer. The FPGA device includes a plurality of random access memory (RAM) types, including a first RAM type and a second RAM type, arranged to store the configuration or image data. The FPGA device also includes a FIFO IP core arranged to implement a FIFO function in a plurality of different FPGA platforms. The FIFO IP core is: i) configured to implement the FIFO in the FPGA device based on the configuration data, and ii) configurable to store the configuration data in one or both of the first RAM type and the second RAM type.

A computing device comprising: a plurality of ALUs; a set of registers; a memory; a memory interface between the registers and the memory; a control unit controlling the ALUs by generating: at least one cycle i including both implementing at least one first computing operation by way of an arithmetic logic unit and downloading a first dataset from the memory to at least one register; at least one cycle ii, following the at least one cycle i, including implementing a second computing operation by way of an arithmetic logic unit, for which second computing operation at least part of the first dataset forms at least one operand.

A system to support a machine learning (ML) operation comprises a core configured to receive and interpret commands into a set of instructions for the ML operation and a memory unit configured to maintain data for the ML operation. The system further comprises an inference engine having a plurality of processing tiles, each comprising an on-chip memory (OCM) configured to maintain data for local access by components in the processing tile and one or more processing units configured to perform tasks of the ML operation on the data in the OCM. The system also comprises an instruction streaming engine configured to distribute the instructions to the processing tiles to control their operations and to synchronize data communication between the core and the inference engine so that data transmitted between them correctly reaches the corresponding processing tiles while ensuring coherence of data shared and distributed among the core and the OCMs.

A system to support a machine learning (ML) operation comprises a core configured to receive and interpret commands into a set of instructions for the ML operation and a memory unit configured to maintain data for the ML operation. The system further comprises an inference engine having a plurality of processing tiles, each comprising an on-chip memory (OCM) configured to maintain data for local access by components in the processing tile and one or more processing units configured to perform tasks of the ML operation on the data in the OCM. The system also comprises an instruction streaming engine configured to distribute the instructions to the processing tiles to control their operations and to synchronize data communication between the core and the inference engine so that data transmitted between them correctly reaches the corresponding processing tiles while ensuring coherence of data shared and distributed among the core and the OCMs.

A microcontroller includes two processing blocks that respectively have a Central Processing Unit (CPU) and a peripheral circuit, where an access to the peripheral circuit in each of the processing blocks, that is, to a Read-Only Memory (ROM) or a Pulse Width Modulator (PWM) signal generator, is limited only from the CPU disposed in the same processing block. Thereby a fail-safe functionality of the microcontroller is improved.

The present invention discloses a processor comprising three-dimensional memory (3D-M) array (3D-processor). Instead of logic-based computation (LBC), the 3D-processor uses memory-based computation (MBC). It comprises an array of computing elements, with each computing element comprising an arithmetic logic circuit (ALC) and a 3D-M-based look-up table (3DM-LUT). The ALC performs arithmetic operations on the LUT data, while the 3DM-LUT is stored in at least one 3D-M array.

Embodiments of the present invention provide a method for incorporating a dynamic processing memory core into a single memory chip to enable computational processing and memory storage from the single memory chip. The method includes storing data elements by memory storage devices positioned on the single memory chip. The method also includes executing, by a processing devices positioned on the single memory chip, memory instructions. The method also includes transitioning the dynamic memory processing core from a memory storage device to a processing device by instructing the processing device to execute the memory instructions. The method also includes transitioning the dynamic processing memory core from the processing device to the memory storage device by instructing the processing device to not execute the memory instructions thereby terminating the computational processing of the dynamic processing memory core and maintaining the memory storage provided by the memory storage device.