The optimization of performance of complex simulation codes with high computational demands, such as Octo-Tiger, is an ongoing challenge. Octo-Tiger is an astrophysics code simulating the evolution of star systems based on the fast multipole method on adaptive octrees. It was implemented using high-level C++ libraries, specifically HPX and Vc, which allows its use on different hardware platforms. Recently, we have demonstrated excellent scalability in a distributed setting. In this paper, we study Octo-Tiger’s node-level performance on an Intel Knights Landing platform. We focus on the fast multipole method, as it is Octo-Tiger’s computationally most demanding component. By using HPX and a futurization approach, we can efficiently traverse the adaptive octrees in parallel. On the core-level, threads process sub-grids using multiple 743-element stencils. In numerical experiments, simulating the time evolution of a rotating star on an Intel Xeon Phi 7250 Knights Landing processor, Octo-Tiger shows good parallel efficiency and achieves up to 408 GFLOPS. This results in a speedup of 2x compared to a 24-core Skylake-SP platform, using the same high-level abstractions.