Design-Phase Buffer Allocation for Post-Silicon Clock Binning by Iterative Learning

TL;DR

This paper proposes a method for optimal placement of post-silicon clock tuning buffers during design to improve yield and profit in high-performance chips by reducing overdesign and balancing timing after manufacturing.

Contribution

It introduces an iterative learning approach using Sobol sequences for buffer placement, enhancing profit and yield with minimal buffers.

Findings

Achieves about 14% average profit improvement.

Up to 26% profit increase in some cases.

Uses fewer buffers while maintaining effectiveness.

Abstract

At submicron manufacturing technology nodes, pro- cess variations affect circuit performance significantly. To counter these variations, engineers are reserving more timing margin to maintain yield, leading to an unaffordable overdesign. Most of these margins, however, are wasted after manufacturing, because process variations cause only some chips to be really slow, while other chips can easily meet given timing specifications. To reduce this pessimism, we can reserve less timing margin and tune failed chips after manufacturing with clock buffers to make them meet timing specifications. With this post-silicon clock tuning, critical paths can be balanced with neighboring paths in each chip specifically to counter the effect of process variations. Consequently, chips with timing failures can be rescued and the yield can thus be improved. This is specially useful in high- performance designs, e.g., high-end CPUs, where clock binning makes chips with higher performance much more profitable. In this paper, we propose a method to determine where to insert post-silicon tuning buffers during the design phase to improve the overall profit with clock binning. This method learns the buffer locations with a Sobol sequence iteratively and reduces the buffer ranges afterwards with tuning concentration and buffer grouping. Experimental results demonstrate that the proposed method can achieve a profit improvement of about 14% on average and up to 26%, with only a small number of tuning buffers inserted into the circuit.

Full text

See pages 1-last of buffer_insertion_learning_TCAD_2017.pdf