Abstract: Computing resources are optimally allocated for a multipath neural network using a multipath neural network analyzer that includes an interface and a processing device. The interface receives a multipath neural network that includes two or more paths. A first path includes one or more layers. A first layer of the first path corresponds to a first kernel that runs on a compute unit that includes two or more cores. The processing device allocates to the first kernel a minimum number of cores of the compute unit and a maximum number of cores of the compute unit. The minimum number of cores of the compute unit is allocated based on the first kernel being run concurrently with at least one other kernel on the compute unit and the maximum number of cores of the compute unit is allocated based on the first kernel being run alone on the compute unit.

Abstract: Computing resources may be optimally allocated for a multipath neural network using a multipath neural network analyzer that includes an interface and a processing device. The interface receives a multipath neural network. The processing device generates the multipath neural network to include one or more layers of a critical path through the multipath neural network that are allocated a first allocation of computing resources that are available to execute the multipath neural network. The critical path limits throughput of the multipath neural network. The first allocation of computing resources reduces an execution time of the multipath neural network to be less than a baseline execution time of a second allocation of computing resources for the multipath neural network. The first allocation of computing resources for a first layer of the critical path is different than the second allocation of computing resources for the first layer of the critical path.