Pre-exascale High Performance Computers (HPC) can reach more than 400 Pflop/s real perfor-mance according the HPLinpack benchmarks. For nanoscience and quantum biology there are requirements for those program codes based on quantum physics algorithms which is difficult to ideally parallelize. Such parallel codes reach their limitations at terascale performance clus-ters. The standard Amdahl's law suggestions for code parallelization complicates focusing and planning for the next step the parallel code developments. In this report we focused on a three key applications domain which are highly parallelizable: HPC benchmarks, quantum compu-ting simulators and Car-Parinello molecular dynamics. According the results we summarize the Amdahl's Law & Parallel Speedup performance achievements with supercomputer with pre-petascale homogeneous HPC hardware. We conclude as an universal computer the pre-petascale supercomputing performance homogeneous hardware still has the basic challeng-es which must be addressed by the researchers or developer in order efficiently to use them.
翻译:超高级高级性能计算机(HPC)在HPLinpack基准下可以达到400多个Pflop/s real perf-mance 。 对于纳米科学和量子生物学来说,根据量子物理算法,这些程序代码的要求是以难以理想的平行法算法为基础。这些平行代码达到其在梯度性能闭塞器的限制。标准的Amdahl关于代码平行化的法律建议使平行代码开发的下一个步骤的重点和规划复杂化。 在本报告中,我们侧重于三个高度平行的关键性应用领域: HPC基准、量子合成模拟器和汽车- Parinello分子动态。 根据我们总结的结果,Amadahl的法律和平行加速性能成绩与超计算机的预性能同质性能HPC硬件相匹配。 我们得出结论,作为通用计算机,模型前的超级合成性能同质性能硬件仍然拥有基本的拼图元素,研究人员或开发者必须加以研究,以便有效使用这些硬件。