Methods and systems relating to improved processing architectures with pre-staged instructions are disclosed herein. A disclosed processor includes an instruction memory, at least one functional processing unit, a bus, a set of instruction registers configured to be loaded, using the bus, with a set of pre-staged instructions from the instruction memory, and a logic circuit configured to provide the set of pre-staged instructions from the set of instruction registers to the at least one functional processing unit in response to receiving an instruction from the instruction memory.

Methods and systems relating to improved processing architectures with pre-staged instructions are disclosed herein. A disclosed processor includes an instruction memory, at least one functional processing unit, a bus, a set of instruction registers configured to be loaded, using the bus, with a set of pre-staged instructions from the instruction memory, and a logic circuit configured to provide the set of pre-staged instructions from the set of instruction registers to the at least one functional processing unit in response to receiving an instruction from the instruction memory.

A symmetric multiprocessor includes with a hierarchical ring-based interconnection network is disclosed. The symmetric processor includes a plurality of buses comprised on the symmetric multiprocessor, wherein each of the buses are configured in a circular topology. The symmetric multiprocessor also includes a plurality of multi-processing nodes interconnected by the buses to make a hierarchical ring-based interconnection network for conveying commands between the multi-processing nodes. The interconnection network includes a command network configured to transport commands based on command tokens, wherein the tokens dictate a destination of the command, a partial response network configured to transport partial responses generated by the multi-processing nodes, and a combined response network configured to combine the partial responses generated by the multi-processing nodes using combined response tokens.

A symmetric multiprocessor includes with a hierarchical ring-based interconnection network is disclosed. The symmetric processor includes a plurality of buses comprised on the symmetric multiprocessor, wherein each of the buses are configured in a circular topology. The symmetric multiprocessor also includes a plurality of multi-processing nodes interconnected by the buses to make a hierarchical ring-based interconnection network for conveying commands between the multi-processing nodes. The interconnection network includes a command network configured to transport commands based on command tokens, wherein the tokens dictate a destination of the command, a partial response network configured to transport partial responses generated by the multi-processing nodes, and a combined response network configured to combine the partial responses generated by the multi-processing nodes using combined response tokens.

Data channel parameter optimization with intelligent selection of initial data channel conditions and optimization algorithm hyperparameters for use of a black box optimizer to optimize one or more data channel parameters. It is currently identified that the initial data channel condition affects the ability of a black box optimizer to optimize data channel parameters. In turn, by use of an intelligent agent (e.g., employing artificial intelligence or machine learning) to iteratively select optimized initial data channel conditions, the optimization of the data channel may be improved. Moreover, the sensitivity of the data channel parameters may be determined, which allows for identification of a subset of data channel parameters that are varied in an optimization approach. This may result in improved performance of the optimization without sacrificing optimized performance of the data channel.

Data channel parameter optimization with intelligent selection of initial data channel conditions and optimization algorithm hyperparameters for use of a black box optimizer to optimize one or more data channel parameters. It is currently identified that the initial data channel condition affects the ability of a black box optimizer to optimize data channel parameters. In turn, by use of an intelligent agent (e.g., employing artificial intelligence or machine learning) to iteratively select optimized initial data channel conditions, the optimization of the data channel may be improved. Moreover, the sensitivity of the data channel parameters may be determined, which allows for identification of a subset of data channel parameters that are varied in an optimization approach. This may result in improved performance of the optimization without sacrificing optimized performance of the data channel.

The master interface generates copy data by copying the first data, and generates an error detection code based on the copy data. The protocol conversion unit generates the second data by converting the first data from the first protocol to the second protocol. The slave interface detects errors in the copy data based on the error detection code. The slave interface also generates the first verification data by performing a conversion from one of the first protocol or the second protocol to the other for one of the second data or copy data. In addition, the slave interface compares the second verification data with the first verification data, using the other of the second data or copy as the second verification data.

A memory controller component of a memory system stores memory access requests within a transaction queue until serviced so that, over time, the transaction queue alternates between occupied and empty states. The memory controller transitions the memory system to a low power mode in response to detecting the transaction queue is has remained in the empty state for a predetermined time. In the transition to the low power mode, the memory controller disables oscillation of one or more timing signals required to time data signaling operations within synchronous communication circuits of one or more attached memory devices and also disables one or more power consuming circuits within the synchronous communication circuits of the one or more memory devices.

Systems and methods for improving power efficiency of electronic systems are disclosed. An intelligent voltage regulator module (VRM) can self-regulate the output power provided to one or more components of an electronic system. For example, output voltage to a component can be increased when more computational power is needed or lowered when appropriate. The intelligent VRM can regulate the output power, for instance, based on one or more of usage or activity of the component. In some cases, the intelligent VRM can independently regulate the output power without input from a host device or override one or more output power parameters. Adjustment of the output power can be performed using machine learning (ML).

Systems and methods for improving power efficiency of electronic systems are disclosed. An intelligent voltage regulator module (VRM) can self-regulate the output power provided to one or more components of an electronic system. For example, output voltage to a component can be increased when more computational power is needed or lowered when appropriate. The intelligent VRM can regulate the output power, for instance, based on one or more of usage or activity of the component. In some cases, the intelligent VRM can independently regulate the output power without input from a host device or override one or more output power parameters. Adjustment of the output power can be performed using machine learning (ML).