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ΣVP: Host-GPU multiplexing for efficient simulation of multiple embedded GPUs on virtual platforms

机译:ΣVP:主机-GPU多路复用,可有效模拟虚拟平台上的多个嵌入式GPU

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Despite their proliferation across many embedded platforms, GPUs present still many challenges to embedded-system designers. In particular, GPU-optimized software actually slows down the execution of embedded applications on system simulators. This problem is worse for concurrent simulations of multiple instances of embedded devices equipped with GPUs. To address this challenge, we present ΣVP, a framework to accelerate concurrent simulations of multiple virtual platforms by leveraging the physical GPUs present on the host machine. ΣVP multiplexes the host GPUs to speed up the concurrent simulations without requiring any change to the original GPU-optimized application code. With ΣVP, GPU applications run more than 600 times faster than GPU-software emulation on virtual platforms. We also propose Kernel Interleaving and Kernel Coalescing, two techniques that further speed up the simulation by one order of magnitude. Finally, we show how ΣVP supports simulation-based functional validation and performance/power estimation.
机译:尽管GPU在许多嵌入式平台中得到了迅速发展,但它们仍对嵌入式系统设计人员提出了许多挑战。特别是,GPU优化的软件实际上会减慢系统模拟器上嵌入式应用程序的执行速度。对于同时装有GPU的嵌入式设备的多个实例的并行仿真,此问题更加严重。为了应对这一挑战,我们提出了ΣVP,这是一个通过利用主机上存在的物理GPU来加速多个虚拟平台的并发仿真的框架。 ΣVP多路复用主机GPU,以加快并发仿真的速度,而无需对原始GPU优化的应用程序代码进行任何更改。借助ΣVP,GPU应用程序的运行速度比虚拟平台上的GPU软件仿真快600倍以上。我们还提出了内核交织和内核合并,这两种技术可进一步将仿真速度提高一个数量级。最后,我们展示了ΣVP如何支持基于仿真的功能验证和性能/功耗估算。

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