Challenges in CISE: Algorithm and Implementation Co-Design for Optimizing Average Complexity/Performance: A Case-Study in High-Performance Low-Power Mobile Multimedia Comm. Design

CISE 中的挑战：优化平均复杂性/性能的算法和实现协同设计：高性能低功耗移动多媒体通信案例研究。

• 批准号: 9726391
• 负责人: Peter Beerel
• 金额: $ 23.9万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-06-01 至 2001-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9726391&HistoricalAwards=false
• 关键词: Challenges; CISE; Algorithm; Implementation; Co

We propose a new paradigm for system design in which the algorithm and circuit implementations are jointly designed to achieve high-performance while minimizing average power consumption. We propose to drive the research using a case study of an adaptive equalizer/decoder where both algorithm selection and asynchronous hardware design will be tackled using a Minimum Average Complexity (MAC) approach. In particular, we will develop a detailed asynchronous design of representative components of a MAC optimized mobile radio receiver, variable complexity algorithms for joint adaptive equalization and decoding, a characterization of the average computational load of these algorithms for a typical mobile user, general procedures for MAC algorithm optimization, an architecture for the new algorithms and a quantitative estimate of the power savings relative to a standard design.

我们提出了一种新的系统设计范例，其中算法和电路实现被联合设计，以实现高性能，同时最小化平均功耗。我们建议使用自适应均衡器/解码器的案例研究来推动研究，其中算法选择和异步硬件设计都将使用最小平均复杂度（MAC）方法来解决。 特别是，我们将开发 MAC 优化移动无线电接收器代表性组件的详细异步设计、用于联合自适应均衡和解码的可变复杂度算法、典型移动用户的这些算法的平均计算负载的表征、 MAC 算法优化、新算法的架构以及相对于标准设计的节能定量估计。