| Popis: |
Cellulose is one of the most promising energy resources that is waiting to be tapped. Harvesting energy from cellulose requires decoding its atomic structure. Some structural information can be exposed by modeling data produced by X-ray scattering. Forward simulation can be used to explore structural parameters of cellulose, including the diameter, twist and coiling, but modeling fiber scattering is computationally challenging. In this paper, we explore how to accelerate a molecular scattering algorithm by leveraging a modern high-end Graphic Processing Unit (GPU). A step-wise optimization approach is described in this work that considers memory utilization, math intrinsics, concurrent kernel execution and workload partitioning. Different caching strategies to manage the state of the atom volume in memory are taken into account. We have developed optimized cluster solutions for both CPUs and GPUs. Different workload distribution schemes and con- current execution approaches for both CPUs and GPUs have been investigated. Leveraging accelerators hosted on a cluster, we have reduced days/weeks of intensive simulation to parallel execution of just a few minutes/seconds. Our GPU-integrated cluster solution can potentially support concurrent modeling of hundreds of cellulose fibril structures, opening up new avenues for energy research. |
