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Oasys-RTL 逻辑综合
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Oasys-RTL 逻辑综合
Oasys-RTL Logic Synthesis, now integrated into the Aprisa digital implementation platform, delivers physically-aware RTL synthesis optimized for advanced process nodes. The solution provides faster design closure and more predictable power, performance, and area (PPA) results through a detail-route-centric architecture.
Leveraging AI and machine learning at every stage, Oasys-RTL synthesis offers a 10x productivity boost for designers through ML/RL exploration, generative AI for tool assistance, and AI agents for design tasks, enabling timing closure in days rather than weeks.
Key Oasys-RTL Logic Synthesis Solutions:
- Physically-aware RTL synthesis
- Faster, predictable PPA closure
- AI-powered synthesis automation
- In-hierarchy optimization (iHO)
- Power-first implementation mode
- Signoff tool correlation for STA and DRC
- Timing closure in days not weeks
- Shared foundation with P&R engines
RTL-to-GDS Logic Synthesis
Complete RTL-to-GDS synthesis providing faster, more predictable PPA closure and better power results for power-centric designs, with a unified hierarchical data model shared across synthesis, placement, CTS, and routing.
- Faster and more predictable PPA closure
- Unified hierarchical data model
- Shared foundation engines across synthesis and P&R
- In-hierarchy optimization (iHO) for top and block levels
AI-Powered Synthesis
Built-in AI-powered technology extends Siemens industrial-grade AI capabilities into logic synthesis, including generative AI for tool assistance, AI agents for design task automation, and ML/RL for design space exploration.
- 10x productivity boost via ML/RL exploration
- Generative AI for tool assistance
- AI agents for design task automation
- 10% better design PPA results
Power-First Synthesis
PowerFirst mode enables power-first implementation by converging on power objectives before performance, delivering highly efficient RTL synthesis for power-centric SoC designs targeting AI/ML, mobile, and IoT applications.
- PowerFirst mode for power-centric designs
- Power optimization before performance convergence
- Reduced ECO iterations
- Signoff-correlated timing and DRC results








