Global Hybrid Multi-core-GPUs-OpenMPs-Resources Platform in Hard Real Time System

Abstract

Interesting with technology of parallel processing and multi-core system, we present a new design for multi-core-GPUs platform system with different shared resources, as well as get the advantage of OpenMP parallel programming to design a new unit for real time system where this platform divided into two part; first: clustering the multi-core-GPUs-OpenMP unit -shared resources by a new method, where CPUs and GPUs grouped in one cluster with OpenMP unit and grouped the shared resources by unique global cluster and scheduled it by global scheduling as well as the local locking shared resources protocol. Second; present an innovative mechanism for scheduling GPUs-OpenMP unit with shared resources in multi-core system. The GPU has been tested with many operations by OpenCL language and used the GPU performance with multi-core system depending on local and distributed semaphores evaluations and compare it with MPCP protocol. The evaluations of our proposal were very good.

Mashing load balancing algorithm to boost hybrid kernels in molecular dynamics simulations

“…There have been different works related to combining heterogeneous programming models and technologies [1][2][3][4][5][6], but they usually provide explicit code inputs, isolation of technologies by tasks, focus only on CPU-GPU distribution or use non-OpenCL-based languages. Some works focus on providing load distribution for HPC simulation environments [1,[7][8][9][10][11][12][13], but most focus on distributed technologies in combination with shared memory. And those that include accelerators are centered on host-device models or task-based parallelism.…”