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This direction is important: moving high-level languages closer to heterogeneous hardware is necessary, but it exposes a deeper scaling issue.
When abstraction layers thin, performance depends on:
memory movement invariants
scheduling stability across parallel units
numerical drift under aggressive optimization
cross-layer coherence (language → compiler → runtime → hardware)
Today optimization is mostly local (kernel / memory / scheduling).
Future bottleneck will be structural stability across the full stack.
High-performance compute will need not only faster transforms, but diagnostics for:
invariant preservation across compilation stages
saturation zones under parallel load
hidden lock-in patterns in optimization loops
This is where representation-agnostic structural measurement becomes relevant for heterogeneous compute stacks as well:
github.com/Tuttotorna/lon…
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