TT-CoSign
Tensor-Train Co-Design & Signoff
Import, compress, search, and sign off — in one six-stage flow with a verifiable certificate at the end.
Key benefitReusable IP-block surrogates via Die Model Studio
NEXT-GENERATION EDA
Design automation that thinks in tensors, not tables.
TensorEDA replaces the corner sweeps, canonical Boolean tables, and independent-variance assumptions at the core of legacy EDA with a unified mathematical foundation — tensor-train decomposition, rigorous uncertainty quantification, compiled Boolean execution, adaptive parasitic extraction, power integrity and reliability analysis, and exact formal proof engines — applied across co-design, timing signoff, functional simulation, parasitic extraction, and equivalence checking.
8production modules
10–200xfewer characterization runs
ExactGF(2) proof engine, no approximation
THE PLATFORM
One mathematical core. Eight production modules.
Every TensorEDA module is a different application of the same underlying research program — not eight disconnected point tools. Explore the live platform demo →
DTCO
Design-Technology Co-Optimization
Technology and circuit design explored together, not in separate loops that fight each other.
Key benefitFaster Pareto search across SRAM, LNA, ADC, SiC/GaN
QUINSIM
Real-SPICE Uncertainty Quantification
Genuine ngspice-driven UQ, cross-validated against brute-force Monte Carlo on every run.
Key benefitHeld-out accuracy reported, not just training fit
NEW
TensorTA
Correlated PVT&A Timing Analysis
Process, Voltage, Temperature, and Activity modeled as one correlated tensor — not disconnected corners.
Key benefit10–200x fewer characterization runs
NEW
TensorEQC
Adaptive Tensorized Equivalence Checking
Exact full-chip equivalence proofs that dynamically hand hard regions to SAT, datapath, or sequential engines.
Key benefitIndependently re-verifiable proof certificates
NEW
TensorSIM
Adaptive Compiled Boolean Simulation
Compiles the circuit, not just the simulator — routing each region to packed BitSlice, LUT, GF(2), or gate-fallback execution based on workload and hardware.
Key benefitDifferentially verified against exact scalar reference output
NEW
TensorPEX
Adaptive Tensor-Network Parasitic Extraction
Compiles the layout, not just the field solver — routing each region to a closed-form analytic model or a real boundary-element solve based on structure.
Key benefitEvery capacitance matrix guaranteed symmetric positive semi-definite
NEW
TensorPWR
Power Integrity & Reliability Analysis
Compiles the power grid, not just the field solver — combining coupling-aware spectral graph cuts, exact Schur-complement macromodels, static IR drop, vectorless worst-case analysis, and electromigration checks.
Key benefitMeasured 29–59% fewer coupling-cut edges on included PDN benchmarks
THE RESEARCH PROGRAM
Advanced mathematics, not another heuristic.
Four techniques. Applied consistently across every module — not reinvented per product.
01
Tensor-Train & Tensor-Network Methods
Compresses high-dimensional variation and logic spaces exponentially. More succinct than canonical BDDs for the routing-style functions common in modern datapaths and NPU logic.
02
Uncertainty Quantification
Polynomial chaos and adaptive sampling replace brute-force Monte Carlo — an order of magnitude fewer simulation runs for the same accuracy.
03
Exact Formal Methods
GF(2) relation tensors and worst-case-optimal joins. Live rank monitoring triggers dynamic handoff — never floating-point approximation in the final proof.
04
AI-Assisted Design Exploration
Sparse-PCE-guided co-optimization and treewidth-aware partitioning turn combinatorial spaces into tractable Pareto search.
OUR VISION
EDA software should think in the same mathematics as the problems it solves.
Semiconductor innovation — AI accelerators, chiplets, wide-bandgap power devices — is advancing faster than the corner-based, canonical-table architecture underneath most signoff tools was ever designed for. TensorEDA is building the next generation of design automation on a different foundation: structural tensor compression, rigorous uncertainty quantification, and exact algorithmic proof, so engineering teams can see the correlated, high-dimensional reality of modern designs instead of a handful of disconnected sample points.
WHY TENSOREDA
Three commitments that shape every module.
Correlated by construction
Variation and design space are modeled jointly wherever the math is correlated — never decomposed for implementation convenience, then patched back together with margin.
Measured, not marketed
Every claim ships with a reproducible benchmark: real ngspice runs, real netlists, real bug-injection tests — limitations included.
Drop-in, not rip-and-replace
Standard Liberty, SDC, SPEF, and structural Verilog in. An additional signoff layer out — not a flow your team re-architects around.
Help Shape the Next Generation of Semiconductor Engineering
Whether you're looking for early access, exploring partnership opportunities, or want to evaluate TensorEDA solutions, we'd love to hear from you.