Broadening the Scope of Multi-Objective Optimizations in Physical Synthesis of Integrated Circuits.

Physical Synthesis;Timing Closure;Timing-Driven Placement;Circuit Optimization;Mathematical Programming;Multi-Objective Optimization;Computer Science;Electrical Engineering;Engineering;Science;Computer Science & Engineering

Papa, David AnthonySylvester, Dennis Michael ;

University of Michigan

关键词: Physical Synthesis;    Timing Closure;    Timing-Driven Placement;    Circuit Optimization;    Mathematical Programming;    Multi-Objective Optimization;    Computer Science;    Electrical Engineering;    Engineering;    Science;    Computer Science & Engineering;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/78744/iamyou_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

In modern VLSI design, physical synthesis tools are primarily responsible for satisfying chip-performance constraints by invoking a broad range of circuit optimizations, such as buffer insertion, logic restructuring, gate sizing and relocation. This process is known as timing closure. Our research seeks more powerful and efficient optimizations to improve the state of the art in modern chip design. In particular, we integrate timing-driven relocation, retiming, logic cloning, buffer insertion and gate sizing in novel ways to create powerful circuit transformations that help satisfy setup-time constraints.State-of-the-art physical synthesis optimizations are typically applied at two scales: i) global algorithms that affect the entire netlist and ii) local transformations that focus on a handful of gates or interconnections. The scale of modern chip designs dictates that only near-linear-time optimization algorithms can be applied at the global scope — typically limited to wirelength-driven placement and legalization. Localized transformations can rely on more time-consuming optimizations with accurate delay models. Few techniques bridge the gap between fully-global and localized optimizations. This dissertation broadens the scope of physical synthesis optimization to include accurate transformations operating between the global and local scales. In particular, we integrate groups of related transformations to break circular dependencies and increase the number of circuit elements that can be jointly optimized to escape local minima.Integrated transformations in this dissertation are developed by identifying and removing obstacles to successful optimizations. Integration is achieved through mapping multiple operations to rigorous mathematical optimization problems that can be solved simultaneously. We achieve computational scalability in our techniques by leveraging analytical delay models and focusing optimization efforts on carefully selected regions of the chip. In this regard, we make extensive use of a linear interconnect-delay model that accounts for the impact of subsequent repeated insertion. Our integrated transformations are evaluated on high-performance circuits with over 100,000 gates. Integrated optimization techniques described in this dissertation ensure graceful timing-closure process and impact nearly every aspect of a typical physical synthesis flow. They have been validated in EDA tools used at IBM for physical synthesis of high-performance CPU and ASIC designs, where they significantly improved chip performance.