Technology
Architecture-Driven PPA Optimization, Reinvented. SilicorAI's technology stack is built on a simple belief: PPA cannot be solved only at the process or EDA-tool level. It must start from the architecture. Our innovations combine patented cell-architecture design, multi-level optimization models, and AI-driven design intelligence to deliver PPA uplift that traditional flows cannot reach.
SilicorAI Technology Stack
Cross-layer optimization that connects architecture, low-power BLIB cell libraries, and the ARCEL AI-EDA platform into your existing synthesis and place-and-route flows.
Architecture Co-Design
AI-Enhanced EDA Intelligence
(ARCEL)
Multi-Level PPA Intervention
3-Layer Technology Stack
This 3-layer stack delivers cross-stage optimization without changing RTL or adding verification overhead.
Why Traditional EDA Fails at Advanced PPA
Understanding the fundamental limitations of traditional EDA approaches at the same deep level as your design lead.
EDA Optimizes Within Stages, Not Across Them
Traditional EDA tools optimize within individual stages (synthesis, place-and-route) but cannot see the full architecture-to-gate picture. This creates suboptimal decisions that miss cross-stage PPA opportunities.
Foundry Libraries Are Generic, Not Workload-Aware
Standard foundry libraries are designed for general-purpose use, not optimized for specific datapath workloads. This leads to leakage imbalance and inefficient cell selection for compute-intensive blocks.
No Architecture-Level Intelligence
Existing flows lack the intelligence to analyze datapath architecture and workload patterns, leading to missed opportunities for optimal architecture selection and cell-level optimization.
Leakage Dominates at 16nm & 7nm
At advanced nodes, leakage power becomes the dominant factor, but traditional flows lack leakage-aware architecture and cell-level optimization, leading to significant power inefficiency.
SilicorAI's Architecture-to-Gate Solution
Our patented technology addresses these fundamental limitations by optimizing across architecture, library, and EDA stages—delivering the global PPA optimum that traditional flows cannot achieve.
Architecture-Level Co-Design
Traditional cell libraries use generic architectures optimized primarily for timing.
SilicorAI redesigns this paradigm by co-optimizing:
- Datapath architecture
- Cell micro-architecture
- Netlist structure
- Interconnect awareness
- Leakage vs dynamic trade-offs
This enables "one-node equivalent PPA uplift"—achieving higher efficiency without changing the process node.
Cell/Datapath Interaction
AI-Enhanced EDA Intelligence Layer
ARCEL is an AI-guided optimization layer that reads workload and architecture context, then guides synthesis and place-and-route tools toward globally optimal solutions—with zero RTL changes and zero additional verification.
Predicts optimal PPA paths
AI-driven prediction of optimal design paths
Adapts to chip domain
AI, IoT, GPU, networking, compute
Evaluates thousands of combinations
Architecture + library combinations
Guides synthesis & physical design
Toward globally optimal solutions
Key Outcomes
Multi-Level PPA Intervention
SilicorAI's technology intervenes at levels traditional EDA tools cannot access:
| Stage | Traditional Tools | SilicorAI Advantage |
|---|---|---|
| Post-RTL | Limited architecture insight | Architecture-guided datapath selection |
| Post-Synthesis | Generic logic optimization | Custom cell substitution & remapping |
| Post-PD | Tool heuristics only | AI-driven placement/routing tuning |
| Sign-Off | Timing/IR only | Domain-aware PPA stabilization |
Multi-Node Results
Key Technical Capabilities
Architecture modeling: capture and explore alternative datapath and micro-architectural choices.
Workload-driven optimization: tune architectures and libraries based on real application traces and use-cases.
Library co-design: co-optimize BLIB cells with target datapaths for leakage, switching power, and timing.
Post-synthesis optimization: remap logic and substitute cells after synthesis without touching RTL.
Post-PnR power & area tuning: guide placement, routing, and buffering to reduce dynamic power and area hot-spots.
Compatibility & Nodes
EDA Flows
Synopsys: DC, Fusion Compiler, PrimeTime (PT) & related flows
Cadence: Genus, Innovus, Tempus
Siemens: Aprisa
Nodes & Technologies
Proven across Bulk, FD-SOI, and FinFET technologies, from 65nm to 7nm and beyond. Validated across multiple foundries including GF14, TSMC16, TSMC28, and TSMC65—confirming relevance to the diverse technology portfolios of major semiconductor manufacturers.
Problems We Solve
Leakage: BLIB cells and architecture co-design reduce standby and active leakage in datapath-heavy logic.
Switching power: Optimized datapaths and cell choices cut unnecessary toggling and glitch power.
Cell inefficiency: Replace generic cells with workload-aware alternatives tuned for your design style.
Datapath bottlenecks: Identify and restructure hot arithmetic and memory-access paths for better PPA.
Grid-level inefficiencies: Shape power and timing across the floorplan to ease IR drop and congestion without re-architecting RTL.
Verification-Neutral Optimization
A core innovation is that none of SilicorAI's changes affect functional correctness, RTL behavior, or your existing verification environment.
Zero Verification Overhead
This is one of SilicorAI's strongest differentiators and a major reason customers adopt ARCEL rapidly: no RTL edits, no functional ECOs, and no new testbenches.
"Plug-and-play solution with zero verification overhead"