Abstract: Methods and systems relating to the field of parallel computing are disclosed herein. The methods and systems disclosed include approaches for sparsity uniformity enforcement for a set of computational nodes which are used to execute a complex computation. A disclosed method includes determining a sparsity distribution in a set of operand data, and generating, using a compiler, a set of instructions for executing, using the set of operand data and a set of processing cores, a complex computation. Alternatively, the method includes altering the operand data. The method also includes distributing the set of operand data to the set of processing cores for use in executing the complex computation in accordance with the set of instructions. Either the altering is conducted to, or the compiler is programmed to, balance the sparsity distribution among the set of processing cores.

Abstract: A unified queue configured to perform decoupled prediction and fetch operations, and related apparatuses, systems, methods, and computer-readable media, is disclosed. The unified queue has a plurality of entries, where each entry is configured to store information associated with at least one instruction, and where the information comprises an identifier portion, a prediction information portion, and a tag information portion. The unified queue is configured to update the prediction information portion of each entry responsive to a prediction block, and to update the tag information portion of each entry responsive to a tag and TLB block. The prediction information may be updated more than once, and the unified queue is configured to take corrective action where a later prediction conflicts with an earlier prediction.

Abstract: Methods and systems relating to reducing the number of computations required to execute an artificial neural network (ANN) are disclosed herein. A disclosed method includes: generating a summary of a set of data which is an input for a composite computation; executing a simplified composite computation, using the summary, to produce a simplified output; and executing a second simplified composite computation, using the simplified output, to produce a second simplified output which is a predictor. The second simplified composite computation is a simplification of a second composite computation. The composite computations are both part of a complex computation for the directed graph. The second composite computation depends on the composite computation in the directed graph. The method further includes suppressing, while executing the complex computation, a set of component computations from the second composite computation. The set of component computations are selected for suppression based on the predictor.

Abstract: Methods and systems relating to the field of parallel computing are disclosed herein. The methods and systems disclosed include approaches for sparsity uniformity enforcement for a set of computational nodes which are used to execute a complex computation. A disclosed method includes determining a sparsity distribution in a set of operand data, and generating, using a compiler, a set of instructions for executing, using the set of operand data and a set of processing cores, a complex computation. Alternatively, the method includes altering the operand data. The method also includes distributing the set of operand data to the set of processing cores for use in executing the complex computation in accordance with the set of instructions. Either the altering is conducted to, or the compiler is programmed to, balance the sparsity distribution among the set of processing cores.