Executing a neural network includes generating an output tile of a first layer of the neural network by processing an input tile to the first layer and storing the output tile of the first layer in an internal memory of a processor. An output tile of a second layer of the neural network can be generated using the processor by processing the output tile of the first layer stored in the internal memory.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method of executing a neural network, comprising: generating an output tile of a first layer of the neural network by processing an input tile to the first layer; storing the output tile of the first layer in an internal memory of a processor; and generating, using the processor, an output tile of a second layer of the neural network by processing the output tile of the first layer stored in the internal memory. 2. The method of claim 1, wherein each tile consists of a portion of each feature map of a feature map set. 3. The method of claim 1, wherein the neural network is partitioned into a plurality of frustums processed independently. 4. The method of claim 3, wherein a plurality of compute units process the plurality of frustums in parallel. 5. The method of claim 1, wherein the first layer and the second layer are feature extraction layers configured to process a plurality of images to generate a plurality of output feature maps, the method further comprising: processing the plurality of output feature maps for the plurality of images through a feature classification layer of the neural network in batch. 6. The method of claim 5, wherein the processing the plurality of output feature maps of the plurality of images through the feature classification layer comprises: loading a first plurality of weights of the feature classification layer from an external memory into the internal memory of the processor; and processing each of the plurality of output feature maps using the first plurality of weights of the feature classification layer prior to loading, from the external memory, a second plurality of weights of the feature classification layer or weights of a next feature classification layer. The method of claim 6, further comprising: responsive to the processing of each of the plurality of output feature maps using the first plurality of weights of the feature classification layer, loading the second plurality of weights of the feature classification layer into the internal memory; wherein the second plurality of weights for the feature classification layer overwrite the first plurality of weights for the feature classification layer. 8. An apparatus for executing a neural network, comprising: an internal memory within a processor; a first compute unit, within the processor, coupled to the internal memory and configured to initiate executable operations including: generating an output tile of a first layer of the neural network by processing an input tile to the first layer; storing the output tile of the first layer in the internal memory; and generating an output tile of a second layer of the neural network by processing the output tile of the first layer stored in the internal memory. 9. The apparatus of claim 8, wherein each tile consists of a portion of each feature map of a feature map set. 10. The apparatus of claim 8, wherein the neural network is partitioned into a plurality of frustums processed independently. 11. The apparatus of claim 10, wherein the compute unit is one of a plurality of compute units of the processor that process the plurality of frustums in parallel. 12. The apparatus of claim 8, wherein the first layer and the second layer are feature extraction layers configured to process a plurality of images to generate a plurality of output feature maps, wherein the first compute unit is configured to initiate executable operations further comprising: processing the plurality of output feature maps for the plurality of images through a feature classification layer of the neural network in batch. 13. The apparatus of claim 12, further comprising: an external memory coupled to the first compute unit; wherein the processing the plurality of output feature maps for the plurality of images through the feature classification layer comprises loading a first plurality of weights of the feature classification layer from the external memory into the internal memory and processing each of the plurality of output feature maps using the first plurality of weights of the feature classification layer prior to loading, from the external memory, a second plurality of weights for the feature classification layer or weights of a next feature classification layer. 14. The apparatus of claim 13, wherein the first compute unit is programmed to initiate executable operations further comprising: responsive to the processing of each of the plurality of output feature maps using the first plurality of weights of the feature classification layer, loading the second plurality of weights of the feature classification layer into the internal memory; wherein the second plurality of weights for the feature classification layer overwrite the first plurality of weights for the feature classification layer. 15. A computer program product comprising a computer readable storage medium having program code stored thereon for executing a neural network, the program code executable by a processor to perform operations comprising: generating an output tile of a first layer of the neural network by processing an input tile to the first layer; storing the output tile of the first layer in an internal memory of a processor; and generating, using the processor, an output tile of a second layer of the neural network by processing the output tile of the first layer stored in the internal memory. 16. The computer program product of claim 15, wherein each tile consists of a portion of each feature map of a feature map set. 17. The computer program product of claim 15, wherein the neural network is partitioned into a plurality of frustums processed independently. 18. The computer program product of claim 15, wherein the first layer and the second layer are feature extraction layers configured to process a plurality of images to generate a plurality of output feature maps, wherein the program code is executable by the processor to perform operations further comprising: processing the plurality of output feature maps for the plurality of images through a feature classification layer of the neural network in batch. 19. The computer program product of claim 18, wherein the processing the plurality of output feature maps of the plurality of images through the feature classification layer comprises: loading a first plurality of weights of the feature classification layer from an external memory into the internal memory of the processor; and processing each of the plurality of output feature maps using the first plurality of weights of the feature classification layer prior to loading, from the external memory, a second plurality of weights of the feature classification layer or weights of a next feature classification layer. 20. The computer program product of claim 19, wherein the program code is executable by the processor to perform operations further comprising: responsive to the processing of each of the plurality of output feature maps using the first plurality of weights of the feature classification layer, loading the second plurality of weights of the feature classification layer into the internal memory; wherein the second plurality of weights for the feature classification layer overwrite the first plurality of weights for the feature classification layer.