04 / JIT FINE-TUNING

Make more
of your GPU.

Specialize the work to the hardware and workload in front of it. An online compilation path connects symbolic expressions to reusable kernel artifacts.

01

Compile for the actual workload.

Shape extents, reduction structure and backend identity matter. The symbolic compiler lowers supported expressions, emits source and derives launch plans instead of treating every workload as an identical kernel.

02

Reuse what is still valid.

Tenant-scoped memoization keys include canonical expressions and compiler, backend and ABI fingerprints. Repeated requests can reuse emitted source; changed identities invalidate that reuse.

03

Measure execution on hardware.

The isolated adapter constructs artifacts without launching kernels. CUDA execution needs the existing runtime integration and a CUDA host. Utilization and optimality must be measured on the target workload; source reuse alone does not prove either.

REPOSITORY MAP
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