Abstract: Examples of systems and method described herein or generating, in a memory controller and/or memory device, access codes for memory regions of the memory device using authentication logic, and for accessing the memory device using the access codes. For example, a memory controller and/or a coupled memory device may generate access codes that a host computing device may include in a memory access request to access one or more memory regions of the memory device. Data read or written at the memory device may in some examples only be accessed in accordance with the access codes for memory regions of the memory device. Accordingly, the systems and methods described herein may provide security for specific memory regions of a memory device because the access code are updated periodically (e.g., based on obtained reset indication) or in accordance with an updated count value from a counter.

Abstract: Methods, apparatuses, and systems for implementing data flows in a processor are described herein. A data flow manager may be configured to generate a configuration packet for a compute operation based on status information regarding multiple processing elements of the processor. Accordingly, multiple processing elements of a processor may concurrently process data flows based on the configuration packet. For example, the multiple processing elements may implement a mapping of processing elements to memory, while also implementing identified paths, through the processor, for the data flows. After executing the compute operation at certain processing elements of the processor, the processing results may be provided. In speech signal processing operations, the processing results may be compared to phonemes to identify such components of human speech in the processing results.

Abstract: Examples of systems and method described herein provide for accessing memory devices and, concurrently, generating access codes using an authenticated stream cipher at a memory controller. For example, a memory controller may use a memory access request to, concurrently, perform translation logic and/or error correction on data associated with the memory access request; while also utilizing the memory address as an initialization vector for an authenticated stream cipher to generate an access code. The error correction may be performed subsequent to address translation for a write operation (or prior to address translation for a read operation) to improve processing speed of memory access requests at a memory controller; while the memory controller also generates the encrypted access code.

Abstract: Apparatuses and methods for managing a coherent memory are described. These may include one or more algorithmic logic units (ALUs) and an input/output (I/O) interface. The I/O interface may receive one or more commands and retrieve data from or write data to a memory device. Each command may contain a memory address portion associated with a memory device. The apparatus may also include a memory mapping unit and a device controller. The memory mapping unit may map the memory address to a memory portion of the memory device, and the device controller may communicate with the memory device to retrieve data from or write data to the memory device. The apparatus may be implemented as a processing element in a configurable logic block network, which may additionally include a control logic unit that receives programming instructions from an application and generate the one or more commands based on the instructions.

Abstract: Examples of systems and method described herein provide for the processing of image codes (e.g., a binary embedding) at a memory system including a Hamming processing unit. Such images codes may generated by various endpoint computing devices, such as Internet of Things (IoT) computing devices, Such devices can generate a Hamming processing request, having an image code of the image, to compare that representation of the image to other images (e.g., in an image dataset) to identify a match or a set of neural network results. Advantageously, examples described herein may be used in neural networks to facilitate the processing of datasets, so as to increase the rate and amount of processing of such datasets. For example, comparisons of image codes can be performed “closer” to the memory devices, e.g., at a processing unit having memory devices.

Abstract: Methods, systems, and devices for signal processing and wireless communication are described. For example, a device may include a plurality of antennas operable to transmit and receive communication packets via a plurality of communication protocols and an integrated circuit chip coupled to the plurality of antennas. The integrated circuit chip may comprise a first and a second plurality of processing elements. The first plurality of processing elements may be operable to receive communication packets via a first one of a plurality of communication protocols and process an optimal route. The second plurality of processing elements may be communicatively coupled to the first plurality of processing elements and operable to determine the optimal route to transmit the communication packets from a source device to a destination device based, at least in part, on transmission characteristics associated with at least one of the source or destination devices.

Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of configuration modes for baseband units (BBU) and remote radio heads (RRH). For example, a computing system including a BBU and a RRH may receive a configuration mode selection including information indicative of a configuration mode for respective processing units of the BBU and the RRH. The computing system may allocate the respective processing units to perform wireless processing stages associated with a wireless protocol. The BBU and/or the RRH may generate an output data stream based on the mixing of coefficient data with input data at the BBU and/or the RRH. Examples of systems and methods described herein may facilitate the processing of data for 5G (e.g., New Radio (NR)) wireless communications in a power-efficient and time-efficient manner.

Abstract: Examples of systems and method described herein provide for the processing of image codes (e.g., a binary embedding) at a memory die. Such images codes may generated by various endpoint computing devices, such as Internet of Things (IoT) computing devices. Such devices can generate a Hamming processing command, having an image code of the image, to compare that representation of the image to other images (e.g., in an image dataset) to identify a match or a set of neural network results. Advantageously, examples described herein may be used in neural networks to facilitate the processing of datasets, so as to increase the rate and amount of processing of such datasets. For example, comparisons of image codes can be performed on a memory die itself, like a memory die of a NAND memory device.

Abstract: Methods and apparatus for utilizing non-traditional (e.g., probabilistic or statistically-based) refresh schemes in non-volatile memory. In one embodiment, the memory is characterized in terms of its performance, such as based on BER (bit error rate) as a function of refresh rate based on statistical data for decay of capacitance within the cells of the device with time. In one variant, error-tolerant applications make use of the non-traditionally refreshed (or unrefreshed) memory with enhanced memory bandwidth, since refresh operations have been reduced or eliminated. In another variant, an extant refresh scheme is modified based on a specified minimum allowable performance level for the memory device, In yet another embodiment, error-intolerant applications operate the memory with a reduced or eliminated refresh, and cells or regions of the memory not adequately refreshed by presumed random read/write operations of the memory over time are actively refreshed.

Abstract: Examples of systems and method described herein provide for the processing of image codes (e.g., a binary embedding) at a memory system including a Hamming processing unit. Such images codes may generated by various endpoint computing devices, such as Internet of Things (IoT) computing devices, Such devices can generate a Hamming processing request, having an image code of the image, to compare that representation of the image to other images (e.g., in an image dataset) to identify a match or a set of neural network results. Advantageously, examples described herein may be used in neural networks to facilitate the processing of datasets, so as to increase the rate and amount of processing of such datasets. For example, comparisons of image codes can be performed “closer” to the memory devices, e.g., at a processing unit having memory devices.

Abstract: Examples of systems and method described herein provide for the processing of image codes (e.g., a binary embedding) at a memory controller with various memory devices. Such images codes may generated by various endpoint computing devices, such as Internet of Things (IoT) computing devices, Such devices can generate a Hamming processing request, having an image code of the image, to compare that representation of the image to other images (e.g., in an image dataset) to identify a match or a set of neural network results. Advantageously, examples described herein may be used in neural networks to facilitate the processing of datasets, so as to increase the rate and amount of processing of such datasets. For example, comparisons of image codes can be performed “closer” to the memory devices, e.g., at the memory controller coupled to memory devices.

Abstract: Methods, apparatuses, and systems for implementing data flows in a processor are described herein. A data flow manager may be configured to generate a configuration packet for a compute operation based on status information regarding multiple processing elements of the processor. Accordingly, multiple processing elements of a processor may concurrently process data flows based on the configuration packet. For example, the multiple processing elements may implement a mapping of processing elements to memory, while also implementing identified paths, through the processor, for the data flows. After executing the compute operation at certain processing elements of the processor, the processing results may be provided. In speech signal processing operations, the processing results may be compared to phonemes to identify such components of human speech in the processing results.

Abstract: Methods, apparatuses, and systems for repairing defective memory cells in regions of a memory array associated with high or low priority levels are disclosed. A repair address generator may be configured to generate a memory address map for repair (e.g., blowing fuses at a fuse circuit), depending on whether certain applications may operate at a high priority level indicative of a low bit error rate or a low priority level indicative of a higher bit error rate. For example, a specified error rate associated with a low priority level may correspond to a threshold error rate for certain applications, such as a neural network application that stores trained weights. Such neural network applications may access trained weights being partially stored in defective memory cells, with the least significant bits of such trained weights being stored in defective memory cells that are not repaired according to the memory address map.

Abstract: A device comprising a plurality of antennas operable to transmit and receive communication packets via a plurality of communication protocols and an integrated circuit chip coupled to the plurality of antennas. The integrated circuit chip comprises a first and a second plurality of processing elements. The first plurality of processing elements operable to receive communication packets via a first one of a plurality of communication protocols and process an optimal route. The second plurality of processing elements communicatively coupled to the first plurality of processing elements and operable to determine the optimal route to transmit the communication packets from a source device to a destination device based, at least in part, on transmission characteristics associated with at least one of the source or destination devices.

Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of an autocorrelation calculator. An electronic device including an autocorrelation calculator may be configured to calculate an autocorrelation matrix including an autocorrelation of symbols indicative of a first narrowband Internet of Things (IoT) transmission and a second narrowband IoT transmission. The electronic device may calculate the autocorrelation matrix based on a stored autocorrelation matrix and the autocorrelation of symbols indicative of the first narrowband IoT transmission and symbols indicative of the second narrowband IoT transmission. The stored autocorrelation matrix may represent another received signal at a different time period than a time period of the first and second narrowband IoT transmission.

Abstract: An apparatus, and a method therefore, are described, the apparatus according to one embodiment including a security manager and a plurality of clusters of processing elements. Each cluster of the plurality of clusters includes a respective plurality of processing elements. A controller of the apparatus, which may include a security manager, may be configured to control the plurality of clusters to receive a first data stream and a second data stream, control a first plurality of processing elements in a first cluster to process the first data stream using a first security protocol, and control a second plurality of processing elements in a second cluster to process the second data stream using a second security protocol.

Abstract: Systems, methods, and apparatuses for wireless communication are described. Input data for in-phase branch/quadrature branch (I/Q) imbalance or mismatch may be compensated for or non-linear power amplifier noise may be used to generate compensated input data. In some examples, a transmitter may be configured to transmit communications signaling via a first antenna, the transmitter including a filter configured for digital mismatch correction; a receiver may be configured to receive communications signaling via a second antenna; and a switch may be configured to selectively activate a first switch path to couple the transmitter and the first antenna and a second switch path to couple the receiver and the transmitter to provide communications signaling received via the transmitter as feedback for the filter through the receiver.

Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of full duplex compensation with a self-interference noise calculator that compensates for the self-interference noise generated by power amplifiers at harmonic frequencies of a respective wireless receiver. The self-interference noise calculator may be coupled to antennas of a wireless device and configured to generate the adjusted signals that compensate self-interference. The self-interference noise calculator may include a network of processing elements configured to combine transmission signals into sets of intermediate results. Each set of intermediate results may be summed in the self-interference noise calculator to generate a corresponding adjusted signal.

Abstract: Examples described herein include systems and methods which include wireless devices and systems with examples of an autocorrelation calculator. An electronic device including an autocorrelation calculator may be configured to calculate an autocorrelation matrix including an autocorrelation of symbols indicative of a first radio frequency (“RF”) signal and a second RF signal. The electronic device may calculate the autocorrelation matrix based on a stored autocorrelation matrix and the autocorrelation of symbols indicative of the first RF signal and symbols indicative of the second RF signal. The stored autocorrelation matrix may represent another received signal at a different time period than a time period of the first and second RF signals. Examples of the systems and methods may facilitate the processing of data for wireless and may utilize less memory space than a device than a scheme that stores and calculates autocorrelation from a large dataset computed from various time points.

Abstract: A device comprising a plurality of antennas operable to transmit and receive communication packets via a plurality of communication protocols and an integrated circuit chip coupled to the plurality of antennas. The integrated circuit chip comprises a first and a second plurality of processing elements. The first plurality of processing elements operable to receive communication packets via a first one of a plurality of communication protocols and process an optimal route. The second plurality of processing elements communicatively coupled to the first plurality of processing elements and operable to determine the optimal route to transmit the communication packets from a source device to a destination device based, at least in part, on transmission characteristics associated with at least one of the source or destination devices.