Critical path optimization

The choice of computational techniques for latch placement depends on where this optimization is invoked in a physical synthesis flow. In Chap. 2 we described the major phases of physical synthesis global placement, electrical correction, legalization, timing analysis, detailed placement, critical-path optimization and compression, which may be iterated with timing-driven placement to improve solution quality. 

Fig. 3.1 The contributions in this chapter improve the state of the art in critical path optimization and timing-driven detailed placement...

Fig. 3.4 The layout in a has a poorly-placed latch, and existing critical path optimizations do not solve the problem. Repoweiing the gates may improve the timing some in b, but if it cannot fix the problem, the latch must be moved. Moving the latch up to the next buffer, shown in c, does not give optimization enough freedom. If we move the latch but do not re-buffer in d, timing may degrade. Figure3.12d shows the ideal solution to this problem...

Often the chip architecture produced by behavioral synthesis tools such as VSS contain inefficiencies such as constants that can be propagated through a design, and common subexpressions that appear multiple times in the design, each time with replicated hardware. These can partly result from the fashion in which the user wrote the behavioral description. Also, optimization must modify the design in the direction of meeting time and area constraints. Tradeoffs must be made along different paths. On critical paths optimizations that reduce... 

Lesko U The critical path of warfarin dosing Finding an optimal dosing strategy using pharmacogenetics. Clin Pharmacol Ther 2008 84 301 http //www.fda.gov/cder/genomics/publications.htm... 

The Critical Path Initiative proposed by the Food and Drug Administration (1) has emphasized the need for informative knowledge-based drug development, and there has been much focus on the optimization of early drug development (2, 3). Phase 1 studies are critical in the overall process of drug development, and the need for the implementation of informative designs has been advocated in the literature (4-8). 

D placement tools have to be able to optimize multiple cost objectives in addition to the traditional wire length and critical path delay. 

Fig. 2.2 During physical synthesis refinement, optimization is first applied to most-critical paths, then different optimizations are used to reduce the total number of critical paths...

The minimum slack is the worst slack in a subcircuit. For two subcircuits with identical worst slack, it is possible that one subcircuit has few critical paths with worst slack while the other one has many. A timing optimization has to improve both the worst slack and the overall total threshold slack (TTS) in a subcircuit. TTS is defined as the sum of all slacks below a threshold. If the slack threshold is zero, TTS is equivalent to the total negative slack. With the minimum slack as the only objective, a small improvement in the worst slack may cause a large TTS degradation. Therefore we must add a TTS component to the optimization objective. The balance between the minimum slack and the TTS is controlled by a parameter Wf, which is set to a relatively small value because the worst slack objective is more important. 

A great deal of focus has been given specifically to the constmction of cheap, incremental methods for improving timing along critical paths in an optimized design. 

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