Integrated Circuit Partitioning for Static Timing Analysis
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Solution Overview
Problem
The increasing complexity and size of integrated circuit designs lead to prolonged runtime and high machine memory requirements for static timing analysis (STA), making existing STA tools a bottleneck in the design flow, while current methods fail to provide fast and accurate timing estimations without significant computational resources.
Innovation Solution
The method employs hierarchy-driven and fine-grain topological clustering to partition integrated circuit designs, allowing for parallel analysis by clustering objects based on their hierarchical relations and propagating partition assignments, which includes redundancy to ensure complete timing paths and optimize STA performance without compromising accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full chip static timing analysis is performed on increasingly complex integrated circuit designs, then timing analysis accuracy is maintained, but runtime increases and machine memory requirements increase
Solution Approach 1:
The patent divides the integrated circuit design into multiple partitions using topological clustering algorithms (such as METIS). The design is segmented into balanced partitions with controlled inter-partition connectivity, allowing parallel STA execution on each partition while maintaining overall timing accuracy. This segmentation reduces the computational burden on individual processing units and enables parallel processing to overcome the runtime bottleneck.
2Measurement precision
If full chip static timing analysis is performed on increasingly complex integrated circuit designs, then timing analysis accuracy is maintained, but machine memory capacity requirements increase
Solution Approach 1:
By partitioning the design into smaller sub-circuits, the memory required for each individual STA execution is significantly reduced. Each partition can be analyzed with limited memory resources, and the results are aggregated to provide full-chip timing accuracy. This segmentation approach allows STA to scale to larger designs without requiring proportionally larger memory capacity.
3Adaptability or versatility
If design complexity increases due to system integration advancements, then design functionality is improved, but STA runtime increases
Solution Approach 1:
The patent applies topological clustering to divide complex designs into manageable partitions that can be processed in parallel. This segmentation strategy maintains the ability to handle increasingly complex designs with advanced functionality while preventing STA runtime from scaling linearly with design complexity. The parallel processing of partitions provides near-linear speedup for large designs.
Solution Approach 2:
The patent employs dynamic partitioning strategies that adapt to the specific characteristics of each design. The topological clustering algorithms dynamically adjust partition boundaries based on design topology, timing constraints, and interconnect patterns. This dynamic approach ensures optimal partitioning for diverse design types and complexity levels, maintaining efficient STA performance as designs evolve.
4Adaptability or versatility
If design complexity increases due to system integration advancements, then design functionality is improved, but machine memory requirements increase
Solution Approach 1:
The partitioning approach allows complex designs with advanced functionality to be analyzed using limited memory resources by processing smaller partitions in parallel. The memory requirements scale with individual partition size rather than total design size, enabling STA on large complex designs with standard hardware resources.
Data Source
AI summary
Partitioning of a design allows static timing analysis (STA), signal integrity, and noise analysis to be performed in parallel on multiple, less demanding, and more available hardware resources. Therefore, runtime and throughput of the analysis can be significantly shortened. Notably, the partitioning can include redundancy. That is, partitions are allowed to share objects in order to preserve the timing path completeness and design structural integrity. Due to this redundancy, these partitions can account for many constraints specifically imposed by STA and ensure minimal inter-partition data dependency during the analysis. Once these partitions are populated, analysis can be performed on those partitions in parallel to generate the same timing results as if the design had been analyzed flat as a single unit. Therefore, the performance of the analysis can be optimized without compromising the accuracy and quality of results.