Combined word-length optimization and high-level synthesis ofdigital signal processing systems
Combined word-length optimization and high-level synthesis ofdigital signal processing systems
复制标题
数字信号处理系统的组合字长优化和高级综合
DOI：
10.1109/43.936374
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发表时间：
2001
期刊：
影响因子：
--
通讯作者：
Wonyong Sung
中科院分区：
文献类型：
--
作者：
Ki;Wonyong Sung
传统的定点实现数字信号处理算法的方法需要在算法级进行缩放和字长（WL）优化，以及在架构级进行功能单元共享的高级综合。然而，算法级WL优化具有一些限制，因为它既不能利用功能单元共享信息用于信号分组，也不能准确地估计每个操作的硬件成本。在这项研究中，我们开发了一种结合WL优化和高级综合算法，不仅可以最大限度地减少硬件实现成本，而且还可以显着减少优化时间。该软件最初在信号流图的固定点模拟中找到每个信号的WL灵敏度或最小WL，执行WL意识高级合成，其中具有类似WL灵敏度的信号被分配给相同的功能单元，然后通过迭代地修改合成硬件模型的WL来进行最终WL优化。提出了基于列表调度和整数线性规划的WL意识高级综合算法。要最小化的硬件成本函数通过使用合成的硬件模型来生成。由于采用定点仿真来衡量性能，因此该方法适用于一般的数字信号处理系统，包括非线性和时变系统。使用该软件实现了四阶无限冲激响应滤波器、五阶椭圆滤波器和十二阶自适应最小均方滤波器。
Conventional approaches for fixed-point implementation of digital signal processing algorithms require the scaling and word-length (WL) optimization at the algorithm level and the high-level synthesis for functional unit sharing at the architecture level. However, the algorithm-level WL optimization has a few limitations because it can neither utilize the functional unit sharing information for signal grouping nor estimate the hardware cost for each operation accurately. In this study, we develop a combined WL optimization and high-level synthesis algorithm not only to minimize the hardware implementation cost, but also to reduce the optimization time significantly. This software initially finds the WL sensitivity or minimum WL of each signal throughout fixed-point simulations of a signal flow graph, performs the WL conscious high-level synthesis where signals having the similar WL sensitivity are assigned to the same functional unit, and then conducts the final WL optimization by iteratively modifying the WLs of the synthesized hardware model. A list-scheduling-based and an integer linear-programming-based algorithms are developed for the WL conscious high-level synthesis. The hardware cost function to minimize is generated by using a synthesized hardware model. Since fixed-point simulation is used to measure the performance, this method can be applied to general, including nonlinear and time-varying, digital signal processing systems. A fourth-order infinite-impulse response filter, a fifth-order elliptic filter, and a 12th-order adaptive least mean square filter are implemented using this software.