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GPUs have been shown to deliver impressive computing performance, while also providing high energy efficiency, across a wide range of high-performance and embedded system workloads.
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#Rocm vs opencl benchmark software
The tests are, as the rest of the package, open source software, and can be adapted for other software packages. It is, to our knowledge, the first major molecular mechanics software package to run such validation routinely. We have implemented such a validation for the GROMACS software package, ensuring that every major release passes a number of physical sanity checks performed on selected representative systems before shipping. We therefore propose to include physical validation tests in the code-checking mechanism of MD software packages. While unphysical behavior can be due to poor or incompatible choices of parameters by the user, it can just as well originate in coding errors within the program.
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#Rocm vs opencl benchmark code
The second part of the approach involves testing for code correctness.
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To make the usage as easy as possible, we have developed an open-source and platform-independent Python library () implementing these tests. These tests are shown to significantly increase the reliability of MD simulations by catching a number of common simulation errors violating physical assumptions, such as non-conservative integrators, deviations from the Boltzmann ensemble, and lack of ergodicity between degrees of freedom. We present a number of tests of different complexity, ranging from simple post-processing analysis to more involved tests requiring additional simulations. The first part of this approach involves tests which can be performed by the users of MD programs on their respective systems and setups. Motivated by such examples, we propose a two-fold approach to increase the robustness of molecular simulations. Unphysical behavior of simulations can have significant influence on the results and reproducibility of these simulations, such as folding of proteins and DNA or properties of lipid bilayers determined by cutoff treatment, dynamics of peptides and polymers affected by the choice of thermostat, or liquid properties depending on the simulation time step. However, the quality of any prediction based on molecular dynamics results will strongly depend on the validity of underlying physical assumptions. Increase in terms of the number of atoms simulated to date.Īdvances in recent years have made molecular dynamics (MD) and Monte Carlo (MC) simulations powerful tools in molecular-level research, allowing the prediction of experimental observables in the study of systems such as proteins, membranes, and polymeric materials. Trillion atoms is simulated at up to 88% weak scaling efficiency running at up to 1.33 PFLOPS. On Hazel Hen, strong scaling efficiency of up toĨ1% and 189 billion molecule updates per second is attained, when scaling from 8 to 7168 nodes. Weak scaling performance is increasedīy up to 40% and strong scaling performance by up to more than 220%. Compared to the preceding version of ls1 mardyn on theĮntire set of 9216 nodes of SuperMUC, Phase 1, 27% more atoms are simulated. Supercomputers, maximizing the number of sampled atoms. The present version of ls1 mardyn is used to run simulations on entire Viability of the linked cell-based approach. Schemes for the linked cell-based force calculation are presented, which are able to retain Newton’s third law optimization.Ĭomparisons to well-optimized Verlet list-based codes, such as LAMMPS and GROMACS, demonstrate the Redesign of the SIMD vectorization via wrappers, MPI improvements and a software redesign to allow memory-efficientĮxecution with the production trunk to increase portability and extensibility. Simulating a large number of small, rigid molecules with application areas in chemical engineering. Significant improvements are presented for the molecular dynamics code ls1 mardyn - a linked cell-based code for