Abstract: Embodiments are directed to a processor having a functional slice architecture. The processor is divided into tiles (or functional units) organized into a plurality of functional slices. The functional slices are configured to perform specific operations within the processor, which includes memory slices for storing operand data and arithmetic logic slices for performing operations on received operand data (e.g., vector processing, matrix manipulation). The processor includes a plurality of functional slices of a module type, each functional slice having a plurality of tiles. The processor further includes a plurality of data transport lanes for transporting data in a direction indicated in a corresponding instruction. The processor also includes a plurality of instruction queues, each instruction queue associated with a corresponding functional slice of the plurality of functional slices, wherein the instructions in the instruction queues comprise a functional slice specific operation code.

Abstract: Apparatuses, systems, and techniques to replace one or more corrupt neural network gradient values with one or more corresponding surrogate neural network gradient values. In at least one embodiment, faulty gradient values are identified in a transmitted data packet and are replaced according to a replacement policy with a suitable surrogate value.

Abstract: A system contains a network of processors arranged in a plurality of nodes. Each node comprises a respective plurality of processors connected via local links, and different nodes are connected via global links. The processors of the network communicate with each other to establish a global counter for the network, enabling deterministic communication between the processors of the network. A compiler is configured to explicitly schedule communication traffic across the global and local links of the network of processors based upon the deterministic links between the processors, which enable software-scheduled networking with explicit send or receive instructions executed by functional units of the processors at specific times, to establish a specific ordering of operations performed by the network of processors. In some embodiments, the processors of the network of processors are tensor streaming processors (TSPs).

Abstract: Embodiments are directed to a processor having a functional slice architecture. The processor is divided into tiles (or functional units) organized into a plurality of functional slices. The functional slices are configured to perform specific operations within the processor, which includes memory slices for storing operand data and arithmetic logic slices for performing operations on received operand data (e.g., vector processing, matrix manipulation). The processor includes a plurality of functional slices of a module type, each functional slice having a plurality of tiles. The processor further includes a plurality of data transport lanes for transporting data in a direction indicated in a corresponding instruction. The processor also includes a plurality of instruction queues, each instruction queue associated with a corresponding functional slice of the plurality of functional slices, wherein the instructions in the instruction queues comprise a functional slice specific operation code.

Abstract: A process to manage congestion in a network involves converting traffic received from the local endpoints to a bandwidth demand for one or more destination endpoint in a remote group, and determining a sum over the destination endpoints of a minimum of a maximum bandwidth of a link and a bandwidth demand to one or more of the remote endpoints.

Abstract: Embodiments are directed to a processor having a functional slice architecture. The processor is divided into tiles (or functional units) organized into a plurality of functional slices. The functional slices are configured to perform specific operations within the processor, which includes memory slices for storing operand data and arithmetic logic slices for performing operations on received operand data (e.g., vector processing, matrix manipulation). The processor includes a plurality of functional slices of a module type, each functional slice having a plurality of tiles. The processor further includes a plurality of data transport lanes for transporting data in a direction indicated in a corresponding instruction. The processor also includes a plurality of instruction queues, each instruction queue associated with a corresponding functional slice of the plurality of functional slices, wherein the instructions in the instruction queues comprise a functional slice specific operation code.

Abstract: Embodiments are directed to a deterministic streaming system with one or more deterministic streaming processors each having an array of processing elements and a first deterministic memory coupled to the processing elements. The deterministic streaming system further includes a second deterministic memory with multiple data banks having a global memory address space, and a controller. The controller initiates retrieval of first data from the data banks of the second deterministic memory as a first plurality of streams, each stream of the first plurality of streams streaming toward a respective group of processing elements of the array of processing elements. The controller further initiates writing of second data to the data banks of the second deterministic memory as a second plurality of streams, each stream of the second plurality of streams streaming from the respective group of processing elements toward a respective data bank of the second deterministic memory.

Abstract: Embodiments are directed to a deterministic streaming system with one or more deterministic streaming processors each having an array of processing elements and a first deterministic memory coupled to the processing elements. The deterministic streaming system further includes a second deterministic memory with multiple data banks having a global memory address space, and a controller. The controller initiates retrieval of first data from the data banks of the second deterministic memory as a first plurality of streams, each stream of the first plurality of streams streaming toward a respective group of processing elements of the array of processing elements. The controller further initiates writing of second data to the data banks of the second deterministic memory as a second plurality of streams, each stream of the second plurality of streams streaming from the respective group of processing elements toward a respective data bank of the second deterministic memory.

Abstract: 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.

Abstract: Embodiments are directed to a processor having a functional slice architecture. The processor is divided into tiles (or functional units) organized into a plurality of functional slices. The functional slices are configured to perform specific operations within the processor, which includes memory slices for storing operand data and arithmetic logic slices for performing operations on received operand data (e.g., vector processing, matrix manipulation). The processor includes a plurality of functional slices of a module type, each functional slice having a plurality of tiles. The processor further includes a plurality of data transport lanes for transporting data in a direction indicated in a corresponding instruction. The processor also includes a plurality of instruction queues, each instruction queue associated with a corresponding functional slice of the plurality of functional slices, wherein the instructions in the instruction queues comprise a functional slice specific operation code.

Abstract: 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.

Abstract: Embodiments are directed to a processor having a functional slice architecture. The processor is divided into tiles (or functional units) organized into a plurality of functional slices. The functional slices are configured to perform specific operations within the processor, which includes memory slices for storing operand data and arithmetic logic slices for performing operations on received operand data (e.g., vector processing, matrix manipulation). The processor includes a plurality of functional slices of a module type, each functional slice having a plurality of tiles. The processor further includes a plurality of data transport lanes for transporting data in a direction indicated in a corresponding instruction. The processor also includes a plurality of instruction queues, each instruction queue associated with a corresponding functional slice of the plurality of functional slices, wherein the instructions in the instruction queues comprise a functional slice specific operation code.

Abstract: Embodiments are directed to a processor having a functional slice architecture. The processor is divided into tiles (or functional units) organized into a plurality of functional slices. The functional slices are configured to perform specific operations within the processor, which includes memory slices for storing operand data and arithmetic logic slices for performing operations on received operand data (e.g., vector processing, matrix manipulation). The processor includes a plurality of functional slices of a module type, each functional slice having a plurality of tiles. The processor further includes a plurality of data transport lanes for transporting data in a direction indicated in a corresponding instruction. The processor also includes a plurality of instruction queues, each instruction queue associated with a corresponding functional slice of the plurality of functional slices, wherein the instructions in the instruction queues comprise a functional slice specific operation code.

Abstract: Embodiments are directed to a processor having a functional slice architecture. The processor is divided into tiles (or functional units) organized into a plurality of functional slices. The functional slices are configured to perform specific operations within the processor, which includes memory slices for storing operand data and arithmetic logic slices for performing operations on received operand data (e.g., vector processing, matrix manipulation). The processor includes a plurality of functional slices of a module type, each functional slice having a plurality of tiles. The processor further includes a plurality of data transport lanes for transporting data in a direction indicated in a corresponding instruction. The processor also includes a plurality of instruction queues, each instruction queue associated with a corresponding functional slice of the plurality of functional slices, wherein the instructions in the instruction queues comprise a functional slice specific operation code.

Abstract: Embodiments are directed to a deterministic streaming system with one or more deterministic streaming processors each having an array of processing elements and a first deterministic memory coupled to the processing elements. The deterministic streaming system further includes a second deterministic memory with multiple data banks having a global memory address space, and a controller. The controller initiates retrieval of first data from the data banks of the second deterministic memory as a first plurality of streams, each stream of the first plurality of streams streaming toward a respective group of processing elements of the array of processing elements. The controller further initiates writing of second data to the data banks of the second deterministic memory as a second plurality of streams, each stream of the second plurality of streams streaming from the respective group of processing elements toward a respective data bank of the second deterministic memory.

Abstract: A computational array is implemented in which all operands and results are loaded or output from a single side of the array. The computational array comprises a plurality of cells arranged in n rows and m columns, each configured to produce a processed value based upon a weight value and an activation value. The cells receive weight and activation values via colinear weight and activation transmission channels that each extend across a first side edge of the computational array to provide weight values and activation values to the cells of the array. In addition, result values produced at a top cell of each of the m columns of the array are routed through the array to be output from the same first side edge of the array at a same relative timing at which the result values were produced.

Abstract: Embodiments are directed to a processor having a functional slice architecture. The processor is divided into tiles (or functional units) organized into a plurality of functional slices. The functional slices are configured to perform specific operations within the processor, which includes memory slices for storing operand data and arithmetic logic slices for performing operations on received operand data (e.g., vector processing, matrix manipulation). The processor includes a plurality of functional slices of a module type, each functional slice having a plurality of tiles. The processor further includes a plurality of data transport lanes for transporting data in a direction indicated in a corresponding instruction. The processor also includes a plurality of instruction queues, each instruction queue associated with a corresponding functional slice of the plurality of functional slices, wherein the instructions in the instruction queues comprise a functional slice specific operation code.

Abstract: 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.

Abstract: 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.

Abstract: A computational array is implemented in which all operands and results are loaded or output from a single side of the array. The computational array comprises a plurality of cells arranged in n rows and m columns, each configured to produce a processed value based upon a weight value and an activation value. The cells receive weight and activation values are received via colinear weight and activation transmission channels that each extend across a first side edge of the computational array to provide weight values and activations values to the cells of the array. In addition, result values produced at a top cell of each of the m columns of the array are routed through the array to be output from the same first side edge of the array at a same relative timing at which the result values were produced.