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Parallel simulation of mixed-abstraction SystemC models on GPUs and multicore CPUs

机译:在GPU和多核CPU上对混合抽象SystemC模型进行并行仿真

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This work presents a methodology that parallelizes the simulation of mixed-abstraction level SystemC models across multicore CPUs, and graphics processing units (GPUs) for improved simulation performance. Given a SystemC model, we partition it into processes suitable for GPU execution and CPU execution. We convert the processes identified for GPU execution into GPU kernels with additional SystemC wrapper processes that invoke these kernels. The wrappers enable seamless communication of events in all directions between the GPUs and CPUs. We alter the OSCI SystemC simulation kernel to allow parallel execution of processes. Hence, we co-simulate in parallel, the SystemC processes on multiple CPUs, and the GPU kernels on the GPUs; exploit both the CPUs, and GPUs for faster simulation. We experiment with synthetic benchmarks and a set-top box case study.
机译:这项工作提出了一种方法,该方法可并行化跨多核CPU和图形处理单元(GPU)的混合抽象级别SystemC模型的仿真,以提高仿真性能。给定一个SystemC模型,我们将其划分为适合GPU执行和CPU执行的进程。我们使用调用这些内核的其他SystemC包装器进程将为GPU执行确定的进程转换为GPU内核。包装器使GPU和CPU之间各个方向的事件无缝通信。我们更改OSCI SystemC仿真内核以允许并行执行进程。因此,我们并行地共同仿真多个CPU上的SystemC进程,以及多个GPU上的GPU内核。利用CPU和GPU进行更快的仿真。我们尝试使用综合基准和机顶盒案例研究。

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