Abstract: A system and method of docking an information handling system to an intelligent wireless fan dock comprising a docking sensor to detect a docking event, a wireless module to establish a wireless link of the intelligent wireless fan dock with the docked information handling system upon detection of a docking event and to receive a dynamic fan speed request command to adjust extended fan cooling airflow from fan dock control system operating at the docked information handling system, where the fan dock control system has determined that the docked information handling system and the intelligent wireless fan dock pairing enables an increased performance mode and altered power draw limitations for the docked information handling system relative to the information handling system in an undocked state, and increasing the extended fan cooling airflow of a cooling fan based on the dynamic fan speed request command from the docked information handling system.

Abstract: A voice event detection apparatus is disclosed. The apparatus comprises a vibration to digital converter and a computing unit. The vibration to digital converter is configured to convert an input audio signal into vibration data. The computing unit is configured to trigger a downstream module according to a sum of vibration counts of the vibration data for a number X of frames. In an embodiment, the voice event detection apparatus is capable of correctly distinguishing a wake phoneme from the input vibration data so as to trigger a downstream module of a computing system. Thus, the power consumption of the computing system is saved.

Abstract: There is provided a smart engine including a profile collector and a main processing module. The profile collector is configured to store a plurality of profiles, one or more suitable profiles being dynamically selected according to an instruction from a user or an automatic selector. The main processing module is connected to the profile collector and directly or indirectly connected to a sensor, and configured to perform a detailed analysis to determine detailed properties of features, objects, or scenes based on suitable sensor data from the sensor.

Abstract: An in-memory computing memory device is disclosed. The memory device comprises an array of memory cells, a plurality of word lines, a plurality of bit lines, (M+1) input circuits, a wordline driver and an evaluation circuitry. The array is divided into (M+1) lanes and each lane comprises P memory cell columns and an input circuit. The input circuit in each lane charges a predefined bit line with a default amount of charge proportional to an input synapse value and then distributes the default amount of charge to the other second bit lines with a predefined ratio based on a constant current. The evaluation circuitry couples a selected number of the bit lines to an accumulate line and convert an average voltage at the accumulate line into a digital value in response to a set of (M+1) input synapse values and the activated word line.

Abstract: A processing apparatus applied in an artificial neuron is disclosed. The processing apparatus comprises a parser, a lookup array, a summing circuit and a MAC circuit. The parser parses one of M packets to extract a non-zero weight value from a header of the one packet, to identify a plurality of bit positions with a specified digit from a payload of the one packet, and to output the non-zero weight value and the bit positions in parallel. The lookup array contains N synapse values and is indexed by the bit positions in parallel to generate a plurality of match values. The summing circuit sums up the match values to generate a sum value. The MAC circuit generates a product of the non-zero weight value and the sum value, and generates an accumulate value based on the product and at least one previous accumulate value.

Abstract: A voice event detection apparatus is disclosed. The apparatus comprises a vibration to digital converter and a computing unit. The vibration to digital converter is configured to convert an input audio signal into vibration data. The computing unit is configured to trigger a downstream module according to a sum of vibration counts of the vibration data for a number X of frames. In an embodiment, the voice event detection apparatus is capable of correctly distinguishing a wake phoneme from the input vibration data so as to trigger a downstream module of a computing system. Thus, the power consumption of the computing system is saved.

Abstract: Examples of methods of synchronized mode of flow table and apparatus using the same are described. A method may involve receiving a first key associated with a first flow engine through a first port and a second key associated with a second flow engine through a second port. The method may also involve utilizing a match key in one or more flow entries in a flow table to obtain a first instruction for the first flow engine and a second instruction for the second flow engine.

Abstract: An acceleration apparatus applied in an artificial neuron is disclosed. The acceleration apparatus comprises an AND gate array, a first storage device, a second storage device and a multiply-accumulate (MAC) circuit. The AND gate array with plural AND gates receives a first bitmap and a second bitmap to generate an output bitmap. The first storage device stores a first payload and outputs a corresponding non-zero first element according to a first access address associated with a result of comparing the first bitmap with the output bitmap. The second storage device stores a second payload and outputs a corresponding non-zero second element according to a second access address associated with a result of comparing the second bitmap with the output bitmap. The MAC circuit calculates a dot product of two element sequences from the first storage device and the second storage device.

Abstract: An integrated circuit applied in a deep neural network is disclosed. The integrated circuit comprises at least one processor, a first internal memory, a second internal memory, at least one MAC circuit, a compressor and a decompressor. The processor performs a cuboid convolution over decompression data for each cuboid of an input image fed to any one of multiple convolution layers. The MAC circuit performs multiplication and accumulation operations associated with the cuboid convolution to output a convoluted cuboid. The compressor compresses the convoluted cuboid into one compressed segment and store it in the second internal memory. The decompressor decompresses data from the second internal memory segment by segment to store the decompression data in the first internal memory. The input image is horizontally divided into multiple cuboids with an overlap of at least one row for each channel between any two adjacent cuboids.

Abstract: Examples of methods of synchronized mode of flow table and apparatus using the same are described. A method may involve receiving a first key associated with a first flow engine through a first port and a second key associated with a second flow engine through a second port. The method may also involve utilizing a match key in one or more flow entries in a flow table to obtain a first instruction for the first flow engine and a second instruction for the second flow engine.

Abstract: There is provided a smart engine including a profile collector and a main processing module. The profile collector is configured to store a plurality of profiles, one or more suitable profiles being dynamically selected according to an instruction from a user or an automatic selector. The main processing module is connected to the profile collector and directly or indirectly connected to a sensor, and configured to perform a detailed analysis to determine detailed properties of features, objects, or scenes based on suitable sensor data from the sensor.

Abstract: An in-memory computing memory device is disclosed. The memory device comprises an array of memory cells, a plurality of word lines, a plurality of bit lines, (M+1) input circuits, a wordline driver and an evaluation circuitry. The array is divided into (M+1) lanes and each lane comprises P memory cell columns and an input circuit. The input circuit in each lane charges a predefined bit line with a default amount of charge proportional to an input synapse value and then distributes the default amount of charge to the other second bit lines with a predefined ratio based on a constant current. The evaluation circuitry couples a selected number of the bit lines to an accumulate line and convert an average voltage at the accumulate line into a digital value in response to a set of (M+1) input synapse values and the activated word line.

Abstract: An acceleration apparatus applied in an artificial neuron is disclosed. The acceleration apparatus comprises an AND gate array, a first storage device, a second storage device and a multiply-accumulate (MAC) circuit. The AND gate array with plural AND gates receives a first bitmap and a second bitmap to generate an output bitmap. The first storage device stores a first payload and outputs a corresponding non-zero first element according to a first access address associated with a result of comparing the first bitmap with the output bitmap. The second storage device stores a second payload and outputs a corresponding non-zero second element according to a second access address associated with a result of comparing the second bitmap with the output bitmap. The MAC circuit calculates a dot product of two element sequences from the first storage device and the second storage device.

Abstract: A communications apparatus in a communications system includes a processor and a power scheme controller. The processor determines a predetermined adjustment offset for a zone according to a frame structure of the communications system. The power scheme controller is coupled to the processor, obtains information regarding the predetermined adjustment offset for the zone, determines a predetermined scaling factor for the zone, and determines a target frequency or a target voltage for the processor to operate in according to the predetermined adjustment offset and the predetermined scaling factor.

Abstract: Examples of efficient MAC address storage are described, including methods and an apparatus. A method may involve obtaining a plurality of identifications associated with one or more applications executed on a computing apparatus, with each identification of the plurality of identifications different from one another. The method may also involve storing an identification entry representative of the plurality of identifications associated with the one or more applications. The identification entry may require an amount of memory space for storage less than an amount of memory space required to store the plurality of identifications associated with the one or more applications. The plurality of identifications may be a plurality of MAC addresses. The one or more applications may be one or more virtual machines.

Abstract: A processing apparatus applied in an artificial neuron is disclosed. The processing apparatus comprises a parser, a lookup array, a summing circuit and a MAC circuit. The parser parses one of M packets to extract a non-zero weight value from a header of the one packet, to identify a plurality of bit positions with a specified digit from a payload of the one packet, and to output the non-zero weight value and the bit positions in parallel. The lookup array contains N synapse values and is indexed by the bit positions in parallel to generate a plurality of match values. The summing circuit sums up the match values to generate a sum value. The MAC circuit generates a product of the non-zero weight value and the sum value, and generates an accumulate value based on the product and at least one previous accumulate value.

Abstract: An electronic device has a management data input/output (MDIO) bus, a control unit, and an MDIO master. The control circuit receives a host command from a host device, and outputs a plurality of MDIO commands in response to the host command. The MDIO master receives the MDIO commands from the control circuit, and transmits the MDIO commands to the MDIO bus.

Abstract: A table lookup apparatus has a content-addressable memory (CAM) based device and a scope mask circuit. The CAM based device has CAM entries that are used to vertically store a plurality of tables in a word-wise aggression fashion, wherein the CAM entries are responsive to a valid bit input including valid bits of the CAM entries, and a CAM entry is invalid when receiving a corresponding valid bit set by a predetermined logic value. The scope mask circuit masks a portion of the valid bit input by assigning the predetermined logic value to each valid bit included in the portion of the valid bit input, wherein the portion of the valid bit input corresponds to non-selected table (s).

Abstract: An electronic device includes a control circuit and a bus interface. The control circuit packs a plurality of commands in a compound command frame. The bus interface communicates with another electronic device via a bus between the electronic device and the another electronic device, and packs the compound command frame in a single packet and transmits the single packet over the bus.

Abstract: Examples of packet header deflation for network virtualization are described. A method may involve receiving a data packet having a first length. The method may also involve abbreviating a header of the data packet to deflate the data packet into a deflated data packet having a second length shorter than the first length. The method may further involve forwarding the shortened data packet.