A Secured Large Heterogeneous HPC Cluster System using Massive Parallel Programming Model with Accelerated GPUs

High Performace Computing (HPC) architectures are expected to develop first ExaFlops computer. This Exascale processing framework will be proficient to register ExaFlops estimation every subsequent that is thousands-overlay increment in current Petascale framework. Current advancements are confronting a few difficulties to move toward such outrageous registering framework. It has been anticipated that billion-way of parallelism will be exploited to discover Exascale level secured system that provide massive performance under predefined limitations such as processing cores and power consumption. However, the key elements of the strategies are required to develop a secured ExaFlops level energy efficient system. This study proposes a non-blocking, overlapping and GPU computation based tri-hybird model (OpenMP, CUDA and MPI) model that provide a massive parallelism through different granularity levels. We implemented the three different message passing strategies including and performed the experiments on Aziz-Fujitsu PRIMERGY CX400 supercomputer. It was observed that a comprehensive experimental study has been conducted to validate the performance and energy efficiency of our model. Experimental investigation shows that the EPC could be considered as an initiative and leading model to achieve massive performance through efficient scheme for Exascale computing systems.

@article{Alsubhi2020,
  title     = {A Secured Large Heterogeneous HPC Cluster System using Massive Parallel Programming Model with Accelerated GPUs},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {11},
  number    = {5},
  year      = {2020},
  publisher = {The Science and Information Organization},
  author    = {Khalid Alsubhi},
  doi       = {10.14569/IJACSA.2020.0110549},
  url       = {https://doi.org/10.14569/IJACSA.2020.0110549}
}