A programmable address generator has an iteration variable generator for generation of an ordered set of iteration variables, which are re-ordered by an iteration variable selection fabric, which delivers the re-ordered iteration variables to one or more address generators. A configurator receives an instruction containing fields which provide configuration constants to the address generator, iteration variable selection fabric, and address generators. After configuration, the address generators provide addresses coupled to a memory. In one example of the invention, the address generators generate an input address, a coefficient address, and an output address for performing convolutional neural network inferences.

Examples described herein relate to communications with a bootable processor. Some examples include allocating memory address space to provide access to communications over general purpose input output (GPIO)-consistent pins, wherein the GPIO-consistent pins comprise pins coupled to the bootable processor and a pin of the pins coupled to the bootable processor receives or transmits communication for multiple platform GPIO pins.

A programmable address generator has an iteration variable generator for generation of an ordered set of iteration variables, which are re-ordered by an iteration variable selection fabric, which delivers the re-ordered iteration variables to one or more address generators. A configurator receives an instruction containing fields which provide configuration constants to the address generator, iteration variable selection fabric, and address generators. After configuration, the address generators provide addresses coupled to a memory. In one example of the invention, the address generators generate an input address, a coefficient address, and an output address for performing convolutional neural network inferences.

A processor having a functional slice architecture is divided into a plurality of functional units (tiles) organized into a plurality of slices. Each slice is configured to perform specific functions within the processor, which may include memory slices (MEM) for storing operand data, and arithmetic logic slices for performing operations on received operand data. The tiles of the processor are configured to stream operand data across a first dimension, and receive instructions across a second dimension orthogonal to the first dimension. The timing of data and instruction flows are configured such that corresponding data and instructions are received at each tile with a predetermined temporal relationship, allowing operand data to be transmitted between the slices of the processor without any accompanying metadata. Instead, each slice is able to determine what operations to perform on received data based upon the timing at which the data is received.

A processor having a functional slice architecture is divided into a plurality of functional units (tiles) organized into a plurality of slices. Each slice is configured to perform specific functions within the processor, which may include memory slices (MEM) for storing operand data, and arithmetic logic slices for performing operations on received operand data. The tiles of the processor are configured to stream operand data across a first dimension, and receive instructions across a second dimension orthogonal to the first dimension. The timing of data and instruction flows are configured such that corresponding data and instructions are received at each tile with a predetermined temporal relationship, allowing operand data to be transmitted between the slices of the processor without any accompanying metadata. Instead, each slice is able to determine what operations to perform on received data based upon the timing at which the data is received