Grid/skills/ref_accelerator_for.md

name, description, metadata

name	description	metadata
ref_accelerator_for	Grid accelerator_for usage — converting block-strided thread_for to GPU-portable oSites loops	node_type type originSessionId memory reference 956e80aa-401d-481a-80bb-17f8abe1c131

Pattern: block-strided thread_for → accelerator_for over oSites

Old CPU-only pattern (block-strided over orthog dimension):

thread_for(r, rd, {
  int so = r * grid->_ostride[orthogdim];
  for (int n = 0; n < e1; n++)
  for (int b = 0; b < e2; b++) {
    int ss = so + n * stride + b;
    // work on site ss
  }
});

GPU-portable replacement:

accelerator_for(ss, grid->oSites(), Nsimd, {
  // work on site ss — one SIMT thread per (osite, lane) on GPU
  // one thread per osite (lane loop implicit via GRID_SIMT) on CPU
});

Key rules:

• accelerator_for(iter, count, Nsimd, body) — Nsimd is vobj::Nsimd() or grid->Nsimd()
• On CPU: expands to thread_for over count, acceleratorSIMTlane always returns 0 — must use #ifdef GRID_SIMT pattern if iterating lanes explicitly (see ref_grid_simt_pattern)
• On GPU: one SIMT thread per (iter × lane), acceleratorSIMTlane(Nsimd) returns actual lane
• Loop body must capture only scalar/POD by value or via device-accessible pointers; no std::vector or host containers inside the body
• Coordinate inside accelerator_for must be AcceleratorVector<int, MaxDims> (stack-allocated, device-safe) — Grid's Coordinate typedef already satisfies this

Where defined

Grid/threads/Accelerator.h — CPU path ~line 607; GPU paths in conditional blocks above.

Model file

Grid/algorithms/blas/MomentumProject.h — ImportVector is the canonical example of correct accelerator_for + SIMD lane extraction.