Abstract: Described is a neural network accelerator tile. It includes an activation memory interface for interfacing with an activation memory to receive a set of activation representations and a weight memory interface for interfacing with a weight memory to receive a set of weight representations, and a processing element. The processing element is configured to implement a one-hot encoder, a histogrammer, an aligner, a reducer, and an accumulation sub-element which process the set of activation representations and the set of weight representations to produce a set of output representations.

Abstract: The present application relates to network routing between networks where private routing tables are in use and remote networks. Overlapping IP address ranges may be in use in private networks, which may result IP clashes in the remote network. A system (400) for routing internet protocol, IP, traffic is provided. The system (400) comprises one or more consumer networks (410) each comprising a gateway (420) and one or more private networks (430). Each of the plurality of private networks serves one or more endpoints (440). The system (400) further comprises a remote network (450) comprising a router (460) for each of the plurality of private networks (430) in the consumer network (410).

Abstract: A system and method for using sparsity to accelerate deep learning networks. The method includes: communicating a bit vector to a scheduler identifying which values in an input tensor are non-zero; for each lane of the input tensor, determining which values are to be communicated for multiply-accumulate (MAC) operations, the determination including directing performance of one of: communicating the current value in the lane; communicating the next value in the same lane where such value is non-zero; communicating a value from a step ahead in time where such value is non-zero; and communicating a value from a neighboring lane where such value is non-zero; and outputting the values of the MAC operations.

Abstract: A processor-implemented method implementing a convolution neural network includes: determining a plurality of differential groups by grouping a plurality of raw windows of an input feature map into the plurality of differential groups; determining differential windows by performing, for each respective differential group of the differential groups, a differential operation between the raw windows of the respective differential group; determining a reference element of an output feature map corresponding to a reference raw window among the raw windows by performing a convolution operation between a kernel and the reference raw window; and determining remaining elements of the output feature map by performing a reference element summation operation based on the reference element and each of a plurality of convolution operation results determined by performing respective convolution operations between the kernel and each of the differential windows.

Abstract: A system and method for accelerating multiply-accumulate (MAC) floating-point units during training of deep learning networks. The method including: receiving a first input data stream A and a second input data stream B; adding exponents of the first data stream A and the second data stream B in pairs to produce product exponents; determining a maximum exponent using a comparator; determining a number of bits by which each significand in the second data stream has to be shifted prior to accumulation by adding product exponent deltas to the corresponding term in the first data stream and using an adder tree to reduce the operands in the second data stream into a single partial sum; adding the partial sum to a corresponding aligned value using the maximum exponent to determine accumulated values; and outputting the accumulated values.

Abstract: A system and method for using sparsity to accelerate deep learning networks. The method includes: communicating a bit vector to a scheduler identifying which values in an input tensor are non-zero; for each lane of the input tensor, determining which values are to be communicated for multiply-accumulate (MAC) operations, the determination including directing performance of one of: communicating the current value in the lane; communicating the next value in the same lane where such value is non-zero; communicating a value from a step ahead in time where such value is non-zero; and communicating a value from a neighboring lane where such value is non-zero; and outputting the values of the MAC operations.

Abstract: Natural killer (NK)-lysin peptides from chicken, bovine and human species are used as an antimicrobial or antiviral agent alone or in combination with other agents. A pharmaceutical composition comprising NK-lysin peptides was effective against Rotavirus and various gram-negative and gram-positive bacteria that were tested. Combinations of NK-lysin peptides plus silver nanoparticles or IL-2 were also effective against Salmonella typhimurium. Treatment with the NK-lysin peptides repressed ?-lactam-resistance genes (CTX-M-1, CTX-M-8 and CTX-M-9) in bacterial species tested and thus can be used to augment treatment with ?-lactams and increase bacterial sensitivity to this important class of antibiotics.

Abstract: Natural killer (NK)-lysin peptides from chicken, bovine and human species are used as an antimicrobial or antiviral agent alone or in combination with other agents. A pharmaceutical composition comprising NK-lysin peptides was effective against Rotavirus and various gram-negative and gram-positive bacteria that were tested. Combinations of NK-lysin peptides plus silver nanoparticles or IL-2 were also effective against Salmonella typhimurium. Treatment with the NK-lysin peptides repressed ?-lactam-resistance genes (CTX-M-1, CTX-M-8 and CTX-M-9) in bacterial species tested and thus can be used to augment treatment with ?-lactams and increase bacterial sensitivity to this important class of antibiotics.

Abstract: Methods, systems, and computer readable media to control a cyber physical system using an observer-based controller are described.

Abstract: Methods, computer readable media, and systems for systems and methods for multi-agent system control using consensus and saturation constraints are described.

Abstract: Natural killer (NK)-lysin peptides from chicken, bovine and human species are used as an antimicrobial or antiviral agent alone or in combination with other agents. A pharmaceutical composition comprising NK-lysin peptides was effective against Rotavirus and various gram-negative and gram-positive bacteria that were tested. Combinations of NK-lysin peptides plus silver nanoparticles or IL-2 were also effective against Salmonella typhimurium. Treatment with the NK-lysin peptides repressed ?-lactam-resistance genes (CTX-M-1, CTX-M-8 and CTX-M-9) in bacterial species tested and thus can be used to augment treatment with ?-lactams and increase bacterial sensitivity to this important class of antibiotics.

Abstract: Methods, computer readable media, and systems for systems and methods for multi-agent system control using consensus and saturation constraints are described.

Abstract: Methods, systems, and computer readable media to control a cyber physical system using an observer-based controller are described.

Abstract: Described is a neural network accelerator tile. It includes an activation memory interface for interfacing with an activation memory to receive a set of activation representations and a weight memory interface for interfacing with a weight memory to receive a set of weight representations, and a processing element. The processing element is configured to implement a one-hot encoder, a histogrammer, an aligner, a reducer, and an accumulation sub-element which process the set of activation representations and the set of weight representations to produce a set of output representations.

Abstract: Described is a neural network accelerator tile for exploiting input sparsity. The tile includes a weight memory to supply each weight lane with a weight and a weight selection metadata, an activation selection unit to receive a set of input activation values and rearrange the set of input activation values to supply each activation lane with a set of rearranged activation values, a set of multiplexers including at least one multiplexer per pair of activation and weight lanes, where each multiplexer is configured to select a combination activation value for the activation lane from the activation lane set of rearranged activation values based on the weight lane weight selection metadata, and a set of combination units including at least one combination unit per multiplexer, where each combination unit is configured to combine the activation lane combination value with the weight lane weight to output a weight lane product.

Abstract: A processor-implemented method implementing a convolution neural network includes: determining a plurality of differential groups by grouping a plurality of raw windows of an input feature map into the plurality of differential groups; determining differential windows by performing, for each respective differential group of the differential groups, a differential operation between the raw windows of the respective differential group; determining a reference element of an output feature map corresponding to a reference raw window among the raw windows by performing a convolution operation between a kernel and the reference raw window; and determining remaining elements of the output feature map by performing a reference element summation operation based on the reference element and each of a plurality of convolution operation results determined by performing respective convolution operations between the kernel and each of the differential windows.

Abstract: Apparatus and methods for measuring a dynamic deformation characteristic of a deformable target surface during a deformation interval. The measurement principles may be applied to a large variety of organic and inorganic materials having a surface that can be deformed by an applied non-contact force. The surface may be light diffusing and non-transparent or non-diffusing and transparent. A device for measuring a dynamic deformation characteristic of an in-vivo cornea during a deformation interval includes a corneal topographer and an air puff generator that are operationally integrated. Use of the inventive device enables a method for making a measurement of a deformation characteristic of the in-vivo cornea during a deformation interval, further allowing a determination of spatially-resolved in-vivo corneal biomechanical and biodynamic properties such as corneal elasticity and corneal viscosity.

Abstract: Apparatus and methods for measuring a dynamic deformation characteristic of a deformable target surface during a deformation interval. The measurement principles may be applied to a large variety of organic and inorganic materials having a surface that can be deformed by an applied non-contact force. The surface may be light diffusing and non-transparent or non-diffusing and transparent. A device for measuring a dynamic deformation characteristic of an in-vivo cornea during a deformation interval includes a corneal topographer and an air puff generator that are operationally integrated. Use of the inventive device enables a method for making a measurement of a deformation characteristic of the in-vivo cornea during a deformation interval, further allowing a determination of spatially-resolved in-vivo corneal biomechanical and biodynamic properties such as corneal elasticity and corneal viscosity.