In general, molecular dynamics simulations are computationally expensive tasks so that efficient algorithms are applied to accelerate the simulation as much as possible. Furthermore, high-performant programming languages are necessary to develop high-performant code. Typically, these languages are rather complex which leads to a decrease in productivity. Julia is a high-performant programming language and is also used to write high-level code. In this thesis, we use Julia to implement a simulator and use functions of the C++ library AutoPas as a backend. Additionally, we apply shared memory parallelization strategies to speed up the Julia simulator. After running performance tests and comparing the results to a C++ reference implementation, we discover that for small simulations and quick tests, the Julia simulator is a convenient choice to use because of its low initial compile time. Moreover, the Julia simulator is able to beat the C++ implementation in the force calculation in our chosen scenario.     «

In general, molecular dynamics simulations are computationally expensive tasks so that efficient algorithms are applied to accelerate the simulation as much as possible. Furthermore, high-performant programming languages are necessary to develop high-performant code. Typically, these languages are rather complex which leads to a decrease in productivity. Julia is a high-performant programming language and is also used to write high-level code. In this thesis, we use Julia to implement a simulato...     »