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Emulation based high-accuracy throughput estimation for high-speed connectivities: Case study of USB2.0

机译:基于仿真的高速连接的高精度吞吐量估算:USB2.0的案例研究

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When designing an SoC (system-on-chip), one should ensure that the chip's architecture delivers optimal data throughput for high-speed connectivity blocks on practical use, taking of several layers of software into account. Previous works such as simulation based estimation method or analytical method that focused on estimation of low level throughput in link layer are not adequate for accurately estimating throughput of the real silicon SoC because practical use cases of such complex connectivity blocks typically require extensive software operation on top of platform operating systems like Linux. FPGA-based emulation, therefore, is commonly used to verify functional correctness of complex connectivity blocks in a more realistic usage scenario with real connectivity devices like USB 2.0 mass storage devices. Speed of FPGA emulation, though, is scaled down significantly because of inherent limitation of FPGA emulation while speed of interface to real connectivity devices is required to be at-speed for compliance with connectivity specification standards. For this reason, scaling factors of speed are not uniform and, thus, measurement of performance is not accurate. This paper proposes a method to compensate errors due to the non-uniform scaling factors. In the proposed method, measurements of various parameters in FPGA emulation are applied to a high-accuracy estimation model that we created. Our method was applied to USB2.0, and the experimental result shows 4.1% of estimation error.
机译:在设计SoC(片上系统)时,应考虑到多层软件,确保芯片的体系结构为实际使用中的高速连接模块提供最佳的数据吞吐量。诸如基于仿真的估计方法或专注于估计链路层中低水平吞吐量的分析方法之类的先前工作不足以准确地估计实际硅SoC的吞吐量,因为此类复杂连接模块的实际使用案例通常需要在顶部进行大量软件操作Linux之类的平台操作系统。因此,基于FPGA的仿真通常用于通过诸如USB 2.0大容量存储设备之类的实际连接设备,在更现实的使用场景中验证复杂连接模块的功能正确性。但是,由于FPGA仿真的固有局限性,因此FPGA仿真的速度已显着降低,同时要求与真实连接设备的接口速度必须与连接规范标准保持一致。因此,速度的比例因数不一致,因此性能的测量不准确。本文提出了一种补偿因比例因子不均匀而引起的误差的方法。在提出的方法中,将FPGA仿真中各种参数的测量值应用于我们创建的高精度估计模型。我们的方法应用于USB2.0,实验结果表明估计误差为4.1%。

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