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FPGA-SPICE: A Simulation-Based Architecture Evaluation Framework for FPGAs

机译:FPGA-SPICE:FPGA的基于仿真的架构评估框架

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In this paper, we developed a simulation-based architecture evaluation framework for field-programmable gate arrays (FPGAs), called FPGA-SPICE, which enables automatic layout-level estimation and electrical simulations of FPGA architectures. FPGA-SPICE can automatically generate Verilog and SPICE netlists based on realistic FPGA configurations and a high-level eTtensible Markup Language-based FPGA architectural description language. The outputted Verilog netlists can be used to generate layouts of full FPGA fabrics through a semicustom design flow. SPICE simulation decks can be generated at three levels of complexity, namely, full-chip-level, grid-level, and component-level, providing different tradeoff between accuracy and simulation time. In order to enable such level of analysis, we presented two SPICE netlist partitioning techniques: loads extraction and parasitic net activity estimation. Electrical simulations showed that averaged over the selected benchmarks, the grid-/component-level approach can achieve 6.1x/7.5x execution speed-up with 9.9%/8.3% accuracy loss, respectively, compared to the full-chip level simulation. FPGA-SPICE was showcased through three different case studies: 1) an area breakdown analysis for static random access memory-based FPGAs, showing that configuration memories are a dominant factor; 2) a power breakdown comparison to analytical models, analyzing the source of accuracy loss; and 3) a robustness evaluation against process corners, studying their impact on energy consumption of full FPGA fabrics.
机译:在本文中,我们为现场可编程门阵列(FPGA)开发了一种基于仿真的架构评估框架,称为FPGA-SPICE,该框架可实现FPGA架构的自动布局级估计和电仿真。 FPGA-SPICE可以根据实际的FPGA配置和基于高级可扩展标记语言的FPGA体系结构描述语言自动生成Verilog和SPICE网表。通过半定制设计流程,输出的Verilog网表可用于生成完整FPGA架构的布局。 SPICE仿真平台可以在三个复杂度级别上生成,即全芯片级,网格级和组件级,从而在精度和仿真时间之间提供了不同的权衡。为了进行这样的分析,我们提出了两种SPICE网表分区技术:负载提取和寄生净活动估计。电气仿真表明,与全芯片级仿真相比,网格/组件级方法在选定基准进行平均后,可以实现6.1倍/7.5倍的执行速度,而精度损失分别为9.9%/ 8.3%。通过三个不同的案例研究展示了FPGA-SPICE:1)对基于静态随机存取存储器的FPGA进行区域分解分析,表明配置存储器是主要因素; 2)将功率击穿与分析模型进行比较,分析精度损失的来源; 3)针对过程角落的鲁棒性评估,研究它们对整个FPGA架构能耗的影响。

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