Entanglements between polymer chains are demonstrated as one of the key factors to modulate the macroscopic physical properties of polymeric fluids. During the last half century, comprehensive understandings of this topology-property relation have been pushed forward via extensive theoretical and experimental studies. However, the bottom-up prediction of the dynamical and rheological behavior of polymers at high molecular weight continues a major challenge. As the recent development of computational material science, all-atomistic (AA) molecular dynamics simulations have emerged as one of the most powerful tools to attain the molecular-level understanding of structure-property relations in rich areas of polymeric materials. However, the profound increase in relaxation times and viscosity of polymers with increasing molecular weight essentially limits the usage of AA simulations. This requires modeling techniques that can access extended time and length scales while retaining chemical specificity, such as the atomistic-derived coarse-grained (CG) modeling. The hybrid particle-field (hPF) simulation is becoming a promising candidate for modeling large-scale polymeric systems with chemical details mainly because of its efficient computation of non-bonded interactions between particles. However, the entangled dynamics of polymer melts is lost due to chain cross ability. Chains cross, because the field-treatment of the interactions makes them effectively soft-core. We introduce a multi-chain slip-spring model into the hPF scheme to mimic the topological constraints of entanglements. The study of long-chain entangled polymers and a large parameter space of the slip-spring models require large simulation systems and multiple runs for testing the influence of each parameter. These prerequisites can only be met on high-performance computers (such as Lichtenberg).