Optimization techniques for parallel force-decomposition algorithm in molecular dynamic simulations

The efficiency and scalability of traditional parallel force-decomposition (FD) algorithms are not good because of high communication cost which is introduced when skew-symmetric character of force matrix is applied. This paper proposed a new parallel algorithm called UTFBD (Under Triangle Force Block Decomposition), which is based on a new efficient force matrix decomposition strategy. This strategy decomposes only the under triangle force matrix and greatly reduces parallel communication cost, e.g., the communication cost of UTFBD algorithm is only one third of Taylor's FD algorithm. UTFBD algorithm is implemented on Cluster system and applied to solve a physical nucleation problem with 500,000 particles. Numerical results are analyzed and compared among three algorithms, namely, FRI, Taylor's FD and UTFBD. The efficiency of UTFBD on 105 processors is 41.3%, and the efficiencies of FRI and Taylor's FD on 100 processors are 4.3 and 35.2%, respectively. In another words, the efficiency of UTFBD on about 100 processors is 37.0 and 6.1% higher than that of FRI and Taylor's FD, respectively. Results show that UTFBD can increase the efficiency of parallel MD (Molecular Dynamics) simulation to a higher degree and has a better scalability.