Multi-Die IC Layout Timing Optimization via Mix-and-Match Partitioning
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Solution Overview
Problem
Existing methods for designing three-dimensional integrated circuits (3DICs) and 2.5D ICs do not address design-stage optimization and signoff for mix-and-match die integration, failing to incorporate holistic design approaches that maximize timing slack during the design compilation process.
Innovation Solution
The method involves partitioning a netlist into partitions aware of mix-and-match die integration, synthesizing a clock tree, and routing nets to optimize timing slack, using integer linear programming and heuristic approaches like Fiduccia-Mattheyses optimization, which considers mix-and-match die stacking or tiling during design compilation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional independent die design approaches are used, then design simplicity is maintained, but timing performance and parametric yield are suboptimal
Solution Approach 1:
The patent segments the design process into distinct phases: die partitioning, placement, routing, and timing optimization. By dividing the complex multi-die design into manageable segments that can be independently optimized and then integrated, the approach achieves improved timing performance while keeping the overall design process tractable through systematic decomposition of the design space
Solution Approach 2:
The patent performs preliminary actions by pre-determining die partitioning schemes and stacking configurations before detailed placement and routing. Timing constraints and performance targets are established early in the design flow, allowing subsequent design steps to be guided by these pre-defined parameters, thereby achieving optimal timing without exhaustive exploration of all design possibilities
2Reliability
If all die combinations are evaluated for stacking, then optimal parametric yield is achieved, but computational runtime increases exponentially
Solution Approach 1:
The patent applies partial action by evaluating only the most promising die combinations for stacking rather than all possible combinations. By using heuristics and machine learning models to identify candidate die pairs that are likely to meet timing and performance targets, the approach achieves good parametric yield while avoiding the exponential runtime growth that would result from exhaustive evaluation of all die combinations
Solution Approach 2:
The patent uses machine learning models trained on representative die combinations to predict timing performance of unseen die stacks. By creating surrogate models that copy the behavior of complex timing analysis tools, the system can rapidly evaluate multiple die combinations without performing full timing simulations for each, thereby achieving high parametric yield assessment speed
3Measurement precision
If thermal simulation is performed for all die stacks, then accurate thermal yield prediction is achieved, but computational cost becomes prohibitive
Solution Approach 1:
The patent employs machine learning models that are trained on a subset of thermal simulations to create surrogate models for thermal prediction. These copied models can then rapidly predict thermal behavior of die stacks without requiring full thermal simulations, achieving acceptable thermal yield prediction accuracy while reducing computational energy consumption by orders of magnitude compared to exhaustive simulation approaches
Solution Approach 2:
The patent performs thermal simulation on only a selected subset of die stack configurations that are most critical for thermal yield assessment. By identifying and focusing computational resources on the most thermally challenging die combinations rather than simulating all possible stacks, the approach achieves accurate thermal yield prediction for the critical cases while avoiding prohibitive computational costs
4Reliability
If design optimization is performed after manufacturing, then manufacturing flexibility is maintained, but timing performance cannot be maximized
Solution Approach 1:
The patent performs timing optimization and die partitioning as preliminary actions during the design compilation phase, before manufacturing. By determining the optimal die stacking configuration, placement, and routing upfront, the approach maximizes timing performance while generating manufacturable design data that can be directly used in fabrication, thereby achieving both timing optimization and manufacturing feasibility simultaneously rather than requiring post-manufacturing optimization
Data Source
AI summary
A method for optimizing a multi die implementation flow that is aware of mix-and-match die integration for implementing multi-die integrated circuits includes partitioning a netlist into partitions comprehending mix-and-match die integration, wherein each partition will be assigned to a die. Each partition is placed into a corresponding die. A clock tree of the integrated circuit is synthesized. Nets of the integrated circuit in are routed in accordance the placing and synthesizing.