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Variation-aware high-level DSP circuit design optimisation framework for FPGAs

机译:用于FpGa的变异感知高级Dsp电路设计优化框架

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摘要

The constant technology shrinking and the increasing demand for systems that operate under different power profiles with the maximum performance, have motivated the work in this thesis. Modern design tools that target FPGA devices take a conservative approach in the estimation of the maximum performance that can be achieved by a design when it is placed on a device, accounting for any variability in the fabrication process of the device.udThe work presented here takes a new view on the performance improvement of DSP designs by pushing them into the error-prone regime, as defined by the synthesis tools, and by investigating methodologies that reduce the impact of timing errors at the output of the system.udIn this work two novel error reduction techniques are proposed to address this problem. One is based on reduced-precision redundancy and the other on an error optimisation framework that uses information from a prior characterisation of the device. The first one is a generic architecture that is appended to existing arithmetic operators. The second defines the high-level parameters of the algorithm without using extra resources. Both of these methods allow to achieve graceful degradation whilst variation increases.udA comparison of the new methods is laid against the existing methodologies, and conclusions drawn on the tradeoffs between their cost, in terms of resources and errors, and their benefits in terms of throughput.udIn some cases it is possible to double the performance of the design while still producing valid results.
机译:不断的技术萎缩和对在不同功率曲线下以最大性能运行的系统的需求不断增加,促使了本文的工作。针对FPGA器件的现代设计工具采用保守的方法来估计将设计放置在器件上时可以实现的最大性能,这说明了器件制造过程中的任何可变性。 ud此处介绍的工作通过将DSP设计推入综合工具定义的易于出错的状态,并研究减少时序误差对系统输出影响的方法,从而对DSP设计的性能有了新的看法。提出了两种新颖的减少错误的技术来解决这个问题。一种基于降低精度的冗余,另一种基于错误优化框架,该框架使用来自设备先前特性的信息。第一个是附加到现有算术运算符的通用体系结构。第二个定义了算法的高级参数,而无需使用额外的资源。这两种方法都可以实现顺畅的降级,而变化却会增加。 ud。在某些情况下,有可能使设计性能加倍,同时仍能产生有效的结果。

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    Policarpo Duarte Rui;

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