After being compiled by the Vitis AI compiler, the neural network model is transformed into an
equivalent DPU assembly file, which is then assembled into one ELF
object file by Deep Neural Network Assembler (DNNAS). The DPU ELF
object file is regarded as DPU kernel, which then becomes one execution unit from the
perspective of runtime N2Cube after invoking the API dpuLoadKernel().
N2Cube loads the DPU kernel, including the DPU instructions and network parameters, into
the DPU dedicated memory space and allocate hardware resources. After that, each DPU
kernel can be instantiated into several DPU tasks by calling
dpuCreateTask() to enable the multithreaded programming.