Stochastic & Neuromorphic Computing  /  Explore  /  Compiler intelligence

The intelligent compiler
it advises, not just translates

A conventional compiler lowers one representation to another and stops. SC-NeuroCore's does that — and then reasons about the result: it recommends a hardware target from your constraints, classifies how hard the model is, checks that its equations are stable, plans how to split it across devices, scores the supply-chain risk, estimates heat and carbon, and emits the provenance and compliance evidence. Dozens of design-time analyses, from the same pass that generates the RTL.

Auto-target recommender

Start from constraints, not a chip. Give the compiler a power budget, a clock floor and a datapath width, and it ranks the targets that fit — the same idea as its recommend_target() call. Adjust the sliders and watch the recommendation change.

Illustrative, with representative target envelopes; the real recommender scores against the full hardware-profile database and also weighs cost and supply-chain risk. Targets that miss a constraint are shown with the reason, not hidden.

01  Choosing where to run it

Before generating anything, the compiler can tell you where the design belongs: an auto-target recommender ranks hardware by your constraints, a model-complexity classifier sizes the problem, a supply-chain risk scorer flags geopolitical, sole-source and ITAR exposure per target, and a portability scorer says how easily the model moves between them.

Deeper: constraints over chips
The point is to invert the usual workflow. Instead of picking a chip and hoping the model fits, you state the envelope — power, clock, width, cost, risk tolerance — and the compiler returns the targets that satisfy it, ranked, with the trade-offs visible. Complexity classification then sets expectations (a trivial model and a stiff biophysical one are not the same deployment), and the risk scorer keeps procurement realities in the loop from the first decision rather than the last.
02  Design assurance

The compiler screens the design for the ways it can go wrong. An ODE-stability verifier checks that a neuron's equations will not blow up in fixed point; a formal-equivalence sketch relates the generated RTL to the model; a clock-domain-crossing analyzer, a fault-tree generator and an auto-testbench cover the hardware hazards; and a regression watchdog guards against silent drift between builds.

03  Physical planning

It also plans the physics. A thermal-envelope estimator predicts junction temperature, a power-intent generator emits the UPF the back-end needs, a memory-map and a multi-die floorplanner place the design, a partial-reconfiguration planner stages it, and a heterogeneous-dispatch planner decides which parts run on which fabric.

04  Provenance, compliance & drift

Finally it produces the paperwork a serious deployment needs: a provenance chain tying the artefact back to its source, a compliance matrix and a license-compliance checker, an energy and carbon schedule, a side-channel lint, and a drift compensator that corrects for how a physical device ages away from its calibration.

One pass, many answers

These are not separate tools bolted together — they are analyses over the same intermediate representation the compiler already builds to generate hardware. Several of them are the engines behind other pages here: the carbon estimate, the security lint, the NIR import and the thermal envelope all live in this layer. What ties them together is a stance: the compiler should hand you a decision with its evidence, not just a netlist.

These are design-time analyses and recommendations — advisory outputs to inform a decision, each with its own evidence boundary, not a substitute for target-specific validation and sign-off.