嵌入式系统综合设计:以数字神经网络为例

D. Lettnin, A. Braun, M. Bogdan, J. Gerlach, W. Rosenstiel
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引用次数: 13

摘要

本文用systemC系统规范语言描述了整个单片系统的设计流程。本研究利用systemC设计多层感知器神经网络,并将其应用于心电图模式识别系统。这项工作的目的是举例说明rtl和行为集成系统的综合。为了实现这一目标,采用预处理方法优化硬件神经网络(HNN)设计的三个主要约束:精度、空间和处理速度。这允许在单个现场可编程门阵列(FPGA)上实现复杂的HNN。高级systemC综合允许直接将系统级转换为硬件级,避免容易出错和费时的转换为另一种硬件描述语言。
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Synthesis of embedded systemC design: a case study of digital neural networks
This work presents the whole system-on-silicon design flow using systemC system specification language. In this study, systemC is used to design a multilayer perceptron neural network, which is applied to an electrocardiogram pattern recognition system. The objective of this work is to exemplify the synthesis of RTL-and behavioral integrated systems. To achieve this, a preprocessing methodology was used to optimize the three main constraints of hardware neural network (HNN) design: accuracy, space and processing speed. This allows a complex HNN to be implemented on a single field programmable gate array (FPGA). The high level systemC synthesis allows the straightforward translation of system level into hardware level, avoiding the error prone and the time consuming translation into another hardware description language.
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