The heterogeneous nature of MACO, with its parallel execution of CPU and MMAE, presents an opportunity to optimize the performance of applications that combine GEMM and non-GEMM workloads. By leveraging the parallel computing capabilities of both components, MACO can effectively distribute the computational load between the CPU cores and MMAE, maximizing overall system throughput. To optimize performance, task scheduling algorithms can be implemented to dynamically allocate GEMM and non-GEMM tasks to the most suitable processing units based on workload characteristics and resource availability. Furthermore, efficient data sharing mechanisms and synchronization protocols can be employed to facilitate seamless communication between the CPU and MMAE, ensuring coordinated execution of diverse workloads. By intelligently orchestrating the parallel execution of GEMM and non-GEMM tasks, MACO can achieve superior performance and efficiency in handling complex computational workloads.