In one embodiment, the present invention includes a method for receiving incoming data in a processor and performing a checksum operation on the incoming data in the processor pursuant to a user-level instruction for the checksum operation. For example, a cyclic redundancy checksum may be computed in the processor itself responsive to the user-level instruction. Other embodiments are described and claimed.

A network data prediction method applied to a device that implements an OSI model is provided. The device communicates with a target network device that implements the OSI model. The method includes the following steps: generating a transmission data according to a communication protocol of a first abstraction layer, the transmission data being able to be processed by a first peer abstraction layer of the target network device, and the first peer abstraction layer corresponding to the first abstraction layer and obeying the communication protocol; generating a predicted data according to the communication protocol and the transmission data; and transmitting the transmission data and the predicted data to a second abstraction layer.

Novel and useful system and methods of several functional safety mechanisms for use in an artificial neural network (ANN) processor. The mechanisms can be deployed individually or in combination to provide a desired level of safety in neural networks. Multiple strategies are applied involving redundancy by design, redundancy through spatial mapping as well as self-tuning procedures that modify static (weights) and monitor dynamic (activations) behavior. The various mechanisms of the present invention address ANN system level safety in situ, as a system level strategy that is tightly coupled with the processor architecture. The NN processor incorporates several functional safety concepts which reduce its risk of failure that occurs during operation from going unnoticed. The mechanisms function to detect and promptly flag and report the occurrence of an error with some mechanisms capable of correction as well. The safety mechanisms cover data stream fault detection, software defined redundant allocation, cluster interlayer safety, cluster intralayer safety, layer control unit (LCU) instruction addressing, weights storage safety, and neural network intermediate results storage safety.

Novel and useful system and methods of several functional safety mechanisms for use in an artificial neural network (ANN) processor. The mechanisms can be deployed individually or in combination to provide a desired level of safety in neural networks. Multiple strategies are applied involving redundancy by design, redundancy through spatial mapping as well as self-tuning procedures that modify static (weights) and monitor dynamic (activations) behavior. The various mechanisms of the present invention address ANN system level safety in situ, as a system level strategy that is tightly coupled with the processor architecture. The NN processor incorporates several functional safety concepts which reduce its risk of failure that occurs during operation from going unnoticed. The mechanisms function to detect and promptly flag and report the occurrence of an error with some mechanisms capable of correction as well. The safety mechanisms cover data stream fault detection, software defined redundant allocation, cluster interlayer safety, cluster intralayer safety, layer control unit (LCU) instruction addressing, weights storage safety, and neural network intermediate results storage safety.

Novel and useful system and methods of several functional safety mechanisms for use in an artificial neural network (ANN) processor. The mechanisms can be deployed individually or in combination to provide a desired level of safety in neural networks. Multiple strategies are applied involving redundancy by design, redundancy through spatial mapping as well as self-tuning procedures that modify static (weights) and monitor dynamic (activations) behavior. The various mechanisms of the present invention address ANN system level safety in situ, as a system level strategy that is tightly coupled with the processor architecture. The NN processor incorporates several functional safety concepts which reduce its risk of failure that occurs during operation from going unnoticed. The mechanisms function to detect and promptly flag and report the occurrence of an error with some mechanisms capable of correction as well. The safety mechanisms cover data stream fault detection, software defined redundant allocation, cluster interlayer safety, cluster intralayer safety, layer control unit (LCU) instruction addressing, weights storage safety, and neural network intermediate results storage safety.

Techniques related to improving power consumption of an LDPC decoder are described. In an example, the LDPC decoder uses a message passing algorithm between variable nodes and check nodes. A check node processing unit that generates check node to variable node messages implements a plurality of check node processing mode. Operation in each mode consumes a certain amount of power while providing a certain accuracy. Depending on a reliability of a variable node to check node message received by the check node processing unit, an appropriate check node processing mode is selected and used to generate a corresponding check node to variable node message. The reliability can be estimated for a set of variable node to check node messages based on, for instance, syndrome-related parameters.

Provided is a method for detecting stored data and device, a storage medium and an electronic device. The method includes: the first check information of first data stored in a memory in the current period is determined; the first check information is compared with second check information to obtain a check result, wherein the second check information is check information of second data stored in the memory in a period prior to the current period; and the correctness of storage of the second data is detected according to the check result.

Memory controllers bit-flipping (BF) decoders and methods that selectively apply a checksum-aided error reduction (CA-ER) scheme to BF decoding of a low-density parity-check (LDPC) code. In decoding a codeword, a hard decision value resulting from decoding a select variable node is changed when a first condition is satisfied to yield an updated hard decision value. Also, when the first condition is satisfied, a current checksum value after processing the select variable node is updated using the updated hard decision value. The CA-ER scheme is applied when the updated checksum value is not reduced to a set minimum and a second condition based on a previous checksum value, calculated after a previous variable node is processed, is satisfied.

Instructions stored on a computer-readable medium include, in response to receiving a new message for transmission, generating a candidate message by attempting recovery of a previous message from the new message and recovery bits of the previous message. The instructions include, in response to an indicator indicating that the attempted recovery was successful, computing a delta between the new message and the candidate message and generating a delivery message based on the computed delta. The instructions include, in response to the indicator indicating that the attempted recovery was unsuccessful, generating the delivery message based on the new message exclusive of the computed delta. The instructions include calculating new recovery bits from the new message. The instructions include storing the new recovery bits as the recovery bits of the previous message. The instructions include transmitting the delivery message to a destination over a communications channel.

A method includes generating an extended result from a first operation circuitry having a result register bit width greater than a bus width associated with a residue check path of a second operation circuitry associated with a floating point unit. An extended result residue less a first portion residue of the extended result received from the residue check path is stored as a first partial result residue. The first partial result residue is compared with a first result residue of the second operation circuitry. The extended result residue less both the first partial result residue and a second portion residue of the extended result received from the residue check path as a second partial result residue is compared with a second result residue of the second operation circuitry.