Abstract: Systems, apparatuses and methods may provide for technology that establishes a point of intersection based on a rate of change in a logarithmic function and generates a first linear estimation of the logarithmic function, wherein the first linear estimation has the point of intersection as an upper bound. Additionally, a second linear estimation of the logarithmic function may be generated, wherein the second linear estimation has the point of intersection as a lower bound. In one example, linear estimations of an antilogarithmic function may be similarly generated based on the rate of change of the antilogarithmic function.

Abstract: Technologies for using a shifted neural network include a compute device to determine a shift-based activation function of the shifted neural network. The shift-based activation function is a piecewise linear approximation of a transcendental activation function and is defined by a plurality of line segments such that a corresponding slope of each line segment is a power of two. The compute device further trains the shifted neural network based on shift-based input weights and the determined shift-based activation function.

Abstract: A wireless device having processor circuitry; and a hardware circuit configured to implement, during an active steady-state of a Medium Access Control/Link Layer (MAC/LL) with scheduled channel access, a MAC/LL function without processor circuitry intervention, wherein the steady-state is a state that is control packet transmission free for managed connections in connection oriented communications or a continuous broadcast or scan operation in connectionless communications.

Abstract: A wireless device having processor circuitry; and a hardware circuit configured to implement, during an active steady-state of a Medium Access Control/Link Layer (MAC/LL) with scheduled channel access, a MAC/LL function without processor circuitry intervention, wherein the steady-state is a state that is control packet transmission free for managed connections in connection oriented communications or a continuous broadcast or scan operation in connectionless communications.

Abstract: Technologies for using a shifted neural network include a compute device to determine a shift-based activation function of the shifted neural network. The shift-based activation function is a piecewise linear approximation of a transcendental activation function and is defined by a plurality of line segments such that a corresponding slope of each line segment is a power of two. The compute device further trains the shifted neural network based on shift-based input weights and the determined shift-based activation function.

Abstract: Configurable snoop filters. A memory system is coupled with one or more processing cores. A coherent system fabric couples the memory system with the one or more processing cores. The coherent system fabric comprising at least a configurable snoop filter that is configured based on workload. The configurable snoop filter having a configurable snoop filter directory and a bloom filter. The configurable snoop filter and the bloom filter include runtime configuration parameters that are used to selectively limit snoop traffic.