This paper presents a novel approach to mapping quantum circuits onto multi-core quantum processors, focusing on minimizing non-local communications between cores. Quantum computing offers the potential to solve complex problems intractable for classical computers, but current quantum processors are limited to a few hundred qubits. Modular quantum computing architectures are seen as a promising solution to scale quantum systems. The paper introduces the Hungarian Qubit Assignment (HQA) algorithm, a multi-core mapping algorithm designed to optimize qubit assignments to cores and reduce inter-core communications. The authors evaluate HQA against state-of-the-art circuit mapping algorithms for modular architectures and find that it achieves a 4.9× improvement in execution time and a 1.6× improvement in non-local communications compared to the best performing algorithm. The paper also derives theoretical bounds on the number of non-local communications needed for random quantum circuits and analyzes the challenges of multi-core quantum computing architectures, including the need for efficient communication networks and benchmarking metrics. The results show that HQA is a promising scalable approach for mapping quantum circuits into multi-core architectures, positioning it as a valuable tool for harnessing the potential of quantum computing at scale.This paper presents a novel approach to mapping quantum circuits onto multi-core quantum processors, focusing on minimizing non-local communications between cores. Quantum computing offers the potential to solve complex problems intractable for classical computers, but current quantum processors are limited to a few hundred qubits. Modular quantum computing architectures are seen as a promising solution to scale quantum systems. The paper introduces the Hungarian Qubit Assignment (HQA) algorithm, a multi-core mapping algorithm designed to optimize qubit assignments to cores and reduce inter-core communications. The authors evaluate HQA against state-of-the-art circuit mapping algorithms for modular architectures and find that it achieves a 4.9× improvement in execution time and a 1.6× improvement in non-local communications compared to the best performing algorithm. The paper also derives theoretical bounds on the number of non-local communications needed for random quantum circuits and analyzes the challenges of multi-core quantum computing architectures, including the need for efficient communication networks and benchmarking metrics. The results show that HQA is a promising scalable approach for mapping quantum circuits into multi-core architectures, positioning it as a valuable tool for harnessing the potential of quantum computing at scale.