- Vectorize adam_update with vDSP batch ops (stories_cpu_ops.h)
Replaces scalar per-element loop with vDSP_vsmul/vsma/vsq/vdiv
Expected ~3-4x faster for 2.4M parameter updates
- Vectorize model_adam_step ADAM_UPDATE macro with vDSP (backward.h)
Same batch ops pattern for the train.m model pipeline
- Replace cpu_accum_dW with cblas_sgemm (backward.h)
dW += dy^T @ x is a standard BLAS GEMM operation
Expected 5-10x faster for weight gradient accumulation
- Replace cpu_matmul_backward_dx with cblas_sgemm (backward.h)
dx = dy @ W^T is also a standard BLAS GEMM
- Add -framework Accelerate to train target (Makefile)
Alvaro GPT
maderix