Using a multi-scale model, we simulated the dynamics of blood circulation within a comprehensive, global closed-loop network encompassing arterial, venous, and portal venous systems, along with the heart-pulmonary circulation and micro-circulation in capillaries. The circulation of blood in the human body involves all the components above, with blood flowing simultaneously through various vessels, constituting a closed-loop network [1]. The primary features of this study are the detailed portal venous system encompassed in the cardiovascular model and the parallel computations applied to simulate the entire human blood circulation. The distinctive feature related to the portal venous system is that it clarifies details of blood circulation in this system and its related organs: the liver, stomach, spleen, pancreas, and intestine. Coupled with the convection–diffusion equation system, this feature holds the potential for investigating how different substances of interest, such as insulin and glucose, will be transferred via blood vessels throughout the human body over time until reaching a steady state. Regarding numerical methodologies, blood flow into large blood vessels was simulated using one-dimensional models, enabling analysis of the evolutions of cross-sectional area A, blood flow Q, and mean pressure P for each interested vessel in the temporal field and spatial field [1]. For the simulations of time-varying Q and P in each vascular subsystem corresponding to peripheral arteries and organs, we employed zero-dimensional lumped-parameter models. The other feature contributes to implementing an iterative procedure that allows for parallel computations, prioritizing both execution time and computational stability through the incorporation of shortest job first (SJF) scheduling and interval partitioning strategies [2]. Our analysis indicates that the proposed efficient parallel algorithms for multicore environments solve the equation systems much faster than serial computations. Global multiscale models of the entire blood circulation networks, which encompass numerous blood vessels and junctions, typically demand substantial computational resources. Therefore, our emphasis on high-efficiency computations for this model is of utmost importance within a multicore environment.