Abstract: A system and method may generate code to be used when executing neural networks (NNs), for example convolutional neural networks (CNNs) which may include one or more convolutional layers. For at least one convolutional layer, for each non-zero element in a kernel tensor or matrix associated with the convolutional layer, instructions may be generated or issued. For example, for each non-zero element, a vector broadcast instruction may be generated, and a fused multiply-add (FMA) instruction may be generated, having as parameters a register representing a portion of the output for the convolutional layer, a register storing input data for the convolutional layer, and a register or reference to memory storing the non-zero element. The software or code produced may be executed during convolutional operations, for example as part of a larger application such as a NN inference application.

Abstract: A system and method may generate code to be used when executing neural networks (NNs), for example convolutional neural networks (CNNs) which may include one or more convolutional layers. For at least one convolutional layer, for each non-zero element in a kernel tensor or matrix associated with the convolutional layer, instructions may be generated or issued. For example, for each non-zero element, a vector broadcast instruction may be generated, and a fused multiply-add (FMA) instruction may be generated, having as parameters a register representing a portion of the output for the convolutional layer, a register storing input data for the convolutional layer, and a register or reference to memory storing the non-zero element. The software or code produced may be executed during convolutional operations, for example as part of a larger application such as a NN inference application.

Abstract: A system and method may generate code to be used when executing neural networks (NNs), for example convolutional neural networks (CNNs) which may include one or more convolutional layers. For at least one convolutional layer, for each non-zero element in a kernel tensor or matrix associated with the convolutional layer, instructions may be generated or issued. For example, for each non-zero element, a vector broadcast instruction may be generated, and a fused multiply-add (FMA) instruction may be generated, having as parameters a register representing a portion of the output for the convolutional layer, a register storing input data for the convolutional layer, and a register or reference to memory storing the non-zero element. The software or code produced may be executed during convolutional operations, for example as part of a larger application such as a NN inference application.

Abstract: A system and method of inferring a neural network (NN) on one or more target computing devices. The NN may include a plurality of layers, where at least one layer includes one or more kernels. Embodiments may include: receiving a data structure representing the NN; analyzing the data structure to produce one or more tasks, where each task may include computations pertaining to a kernel of the NN; selecting a sparse version of at least one kernel and replacing the at least one kernel with the sparse version; and compiling the one or more tasks to produce one or more respective tensor columns, The one or more tensor columns are adapted to fit in respective one or more cache memories of the one or more target computing devices, and include task instruction code that represents at least one computation of the kernel of the NN.

Abstract: A system and method may generate code to be used when executing neural networks (NNs), for example convolutional neural networks (CNNs) which may include one or more convolutional layers. For at least one convolutional layer, for each non-zero element in a kernel tensor or matrix associated with the convolutional layer, instructions may be generated or issued. For example, for each non-zero element, a vector broadcast instruction may be generated, and a fused multiply-add (FMA) instruction may be generated, having as parameters a register representing a portion of the output for the convolutional layer, a register storing input data for the convolutional layer, and a register or reference to memory storing the non-zero element. The software or code produced may be executed during convolutional operations, for example as part of a larger application such as a NN inference application.