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A Novel Power Estimation Framework for SRAM-Based FPGAs

机译:基于SRAM的FPGA的新型功率估计框架

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Field Programmable Gate Arrays (FPGAs) is becoming one of the most widely used electronics devices. Because of its unique architecture, power estimation is a complicated task for FPGAs. This paper presents a novel power estimation framework for SRAM-based FPGAs. Considering both dynamic power and static power, a gate-level power model for configuration logic blocks (CLBs) and a transistor-level power model for interconnect resources is developed for power estimation of SRAM-based FPGAs. To achieve the accuracy and efficiency, we use the transition density method includes glitches filtering in our proposed power estimation framework. 20 MCNC benchmark circuits have been applied to our proposed power estimation framework, and the detailed power dissipation distribution obtained from the experimental results is presented. The proposed framework is also quite flexible, which is capable of estimating power for a wide variety of SRAM-based FPGA architectures.
机译:现场可编程门阵列(FPGA)成为最广泛使用的电子设备之一。由于其独特的架构,功率估计是FPGA的复杂任务。本文介绍了基于SRAM的FPGA的新型功率估计框架。考虑到动态功率和静态功率,为基于SRAM的FPGA的功率估计开发了用于配置逻辑块(CLB)的门级功率模型和用于互连资源的晶体管级功率模型。为了实现准确性和效率,我们使用过渡密度方法包括在我们所提出的功率估计框架中过滤的故障。 20 MCNC基准电路已应用于我们所提出的功率估计框架,并提出了从实验结果中获得的详细功耗分布。所提出的框架也非常灵活,能够估算各种基于SRAM的FPGA架构的功率。

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