Biomolecular networks alignment is an important field, and it is an effective way to study biomolecular phenomenon. Adaptive Hungary Greedy Algorithm (AHGA) is one of the valid biomolecular networks alignment algorithms. Commonly, biomolecular networks have large scale and biological background, so the data of biomolecular networks are special. In order to get the alignment results of biomolecular networks in acceptable time, considering the biological significance when aligning them, two methods including MPI (Message Passing Interface) and CUDA (Compute Unified Device Architecture) were used to parallelize the adaptive hybrid algorithm. The methods were analyzed and compared to find the suitable one for biomolecular networks alignment.