scheduling

# Scheduling Halide Pipelines Halide splits every program into an **algorithm** (what each value is) and a **schedule** (when and where each value is computed and stored). The schedule can't change the result — it only moves three levers, and nearly all performance comes from them: - the **order** values are computed in, - how much **redundant recomputation** happens, and - how much **temporary storage** the pipeline needs. This skill routes to a detailed in-repo guide rather than reproducing it. Read the chapter a task actually needs *before* writing or changing a schedule: the directives have precise, easy-to-misuse semantics (`store_at` and `compute_at` control storage and compute *independently*; a misplaced `parallel` can serialize, race, or explode memory; `For` loops carry an inclusive `min`/`max`, not `min`/`extent`). Confirm the result with `print_loop_nest()` rather than assuming. ## Start here Read the landing page first — it has the full table of contents and the four-part structure: - **`references/guide/README.md`** For a fast, one-screen lookup — every directive's signature and effect, the tail strategies, and the common gotchas — without opening a chapter, read the bundled **`references/directive-cheatsheet.md`** (alongside this skill). The chapters live under **`references/guide/`**. The guide and cheat-sheet paths below are relative to this skill; the `src/`, `tutorial/`, and `python_bindings/` paths are relative to the repository root. ## Which chapter to read Jump to what the task needs instead of reading front to back. **The model** (what is being scheduled) - `references/guide/01-introduction.md` — algorithm vs schedule; the three levers. - `references/guide/02-the-programming-model.md` — Funcs, stages, RDoms, the graph. - `references/guide/03-realizing-a-pipeline.md` — when computation runs; JIT vs AOT. - `references/guide/04-bounds-inference.md` — how buffers and loops get sized. **Making it fast** (start here for "make this faster") - `references/guide/05-scheduling-for-cpus.md` — the canonical fast-CPU shape. - `references/guide/06-scheduling-for-gpus.md` — mapping loops onto blocks/threads. - `references/guide/07-what-to-schedule.md` — inline vs compute_at vs compute_root. - `references/guide/08-benchmarking-and-profiling.md` — measure; read the profile. - `references/guide/09-reading-the-stmt-file.md` — check the vectorization shape. - `references/guide/10-recipes.md` — sliding windows, tiling, pyramids, stencils, histograms. - `references/guide/11-pitfalls.md` — recurrences, parallel placement, recompute traps. **Directive mechanics** (what a directive does to the loop nest) - `references/guide/12-reading-a-loop-nest.md` — the `print_loop_nest` notation. - `references/guide/13-defaults-and-inlining.md` — the inline default; three compute levels. - `references/guide/14-placement-compute-root-and-compute-at.md` — where a Func is built. - `references/guide/15-storage-levels.md` — `store_at`, `store_root`, `hoist_storage`. - `references/guide/16-reshaping-loops.md` — `split`, `fuse`, `reorder`, `tile`. - `references/guide/17-loop-types.md` — serial, parallel, vectorized, unrolled, GPU. - `references/guide/18-advanced-directives.md` — `rfactor`, `in`/`clone_in`, `compute_with`, `specialize`. - `references/guide/19-how-the-loop-nest-is-built.md` — the full assembly order. **Reference** - `references/guide/20-directive-reference.md` — every directive, its signature and effect. - `references/guide/21-checklist-and-worked-example.md` — pre-flight checklist + end-to-end example. ## Inspecting a schedule - `Func::print_loop_nest()` prints the loop nest a schedule produces — the fastest way to confirm it did what you meant. Chapter 12 explains the notation. - `HL_DEBUG_CODEGEN=1` (raise for more detail) prints the IR after key lowering passes; `HL_JIT_TARGET` / `HL_TARGET` set the target being scheduled for. - The built-in profiler and the `.stmt` file (chapters 8–9) show where time goes and whether the hot loop is a unit-stride vector store. ## Related material in this repo - **Tutorials:** `tutorial/lesson_05_scheduling_1.cpp`, `tutorial/lesson_08_scheduling_2.cpp`, `tutorial/lesson_12_using_the_gpu.cpp`, `tutorial/lesson_18_parallel_associative_reductions.cpp`. - **Scheduling API:** directive declarations live in `src/Func.h` and `src/Schedule.h`; the passes that consume a schedule are in `src/ScheduleFunctions.cpp`, `src/Bounds.cpp`, and `src/BoundsInference.cpp`. - **Autoschedulers** (let Halide propose a schedule via `Pipeline::apply_autoscheduler`): `src/autoschedulers/` — `mullapudi2016`, `adams2019`, `li2018`, `anderson2021`. - **Python bindings:** the guide's examples are C++, but the scheduling API is identical in Python — the same directives are methods on `halide.Func`, so a C++ schedule maps over directly. Python tutorials mirror the C++ ones under `python_bindings/halide/tutorial/`.