Tiered CUDA acceleration for routed experts (opt-in, CPU default untouched) + REPLAY fixture harness (#16)

* feat: add experimental CUDA backend for resident tensors

* feat: promote pinned experts to a bounded VRAM tier

* feat: preload the GPU expert tier at startup

* fix: harden CUDA backend failure handling

* feat: add deterministic multi-GPU tensor placement

* test: add deterministic CUDA benchmark fixture

* perf: make routed experts the default CUDA path

.gitignore

@@ -9,12 +9,15 @@ c/glm
 c/olmoe
 c/iobench
 c/tok_test
+c/backend_cuda.o
+c/backend_cuda_test
 
 # oracoli tiny generati (make_glm_oracle.py) e dati benchmark scaricati
 c/glm_tiny/
 c/glm_tiny_i2/
 c/glm_tiny_i4/
 c/glm_tiny_mix/
+c/glm_bench_medium/
 c/bench/
 
 # pesi modello / artefatti di run