This work tackles the performance and energy consumption analysis of a legacy scientific application, the VASP (Vienna Ab-initio Simulation Package), an application commonly used by physicists and chemists for modeling materials at the atomic scale. Many of these scientific applications have been implemented in Fortran, where energy metrics instrumentation is not straightforward. We obtained performance figures (execution time and energy consumption) by instrumenting the source code using EML. This energy measurement library has been modified to introduce Fortran interfaces for these metrics. The analysis was carried out using different matrix algebra libraries, parallelization techniques, and hardware platforms, emphasizing on the MPI, OpenMP, and CUDA parallel implementations of the algorithms used in VASP. We employ various material specifications (atomic structures) and molecular sizes of a silicon-based crystal to create a set of benchmarks for these specifications, leading to some recommendations for final users regarding performance improvements. The proposed benchmarking technique assists the user in selecting the right combination of problem size, compilers, and parallelization options available in VASP. For a given system platform, the user will be able to determine not only the architecture to use (GPU or multicore processors), but also the appropriate library and parallelization according to the atomic structure and molecular size.

这项工作解决了传统科学应用程序 VASP（维也纳从头算模拟包）的性能和能耗分析问题，这是物理学家和化学家常用的原子尺度材料建模应用程序。其中许多科学应用程序都是在 Fortran 中实现的，其中能量度量仪器并不简单。我们通过使用 EML 检测源代码来获得性能数据（执行时间和能耗）。该能源测量库经过修改，引入了这些指标的 Fortran 接口。使用不同的矩阵代数库、并行化技术和硬件平台进行分析，重点是 VASP 中使用的算法的 MPI、OpenMP 和 CUDA 并行实现。我们采用硅基晶体的各种材料规格（原子结构）和分子尺寸来为这些规格创建一组基准，从而为最终用户提供有关性能改进的一些建议。所提出的基准测试技术可帮助用户选择 VASP 中可用的问题大小、编译器和并行化选项的正确组合。对于给定的系统平台，用户不仅能够确定要使用的架构（GPU或多核处理器），还能够根据原子结构和分子大小确定适当的库和并行化。