forked from tinygrad/tinygrad
George HotzandGitHub
ccd3428aad
* remove ptrdtype * tag instead of set * no ptrdtype * debuf like the ranges
624 lines
31 KiB
Python
624 lines
31 KiB
Python
from dataclasses import dataclass, field, replace
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from typing import cast
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import itertools
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from tinygrad.dtype import dtypes, PtrDType, AddrSpace, Invalid
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from tinygrad.uop.ops import PatternMatcher, UPat, Ops, UOp, resolve, GroupOp, KernelInfo, ParamArg, shape_to_shape_arg
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from tinygrad.uop.ops import graph_rewrite, sint, AxisType, BottomUpGate, profile_matches, identity_element
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from tinygrad.uop.symbolic import symbolic
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from tinygrad.helpers import prod, all_same, getenv, dedup, all_int, DEBUG, SPLIT_REDUCEOP, DEBUG_RANGEIFY, VIZ, MAX_KERNEL_BUFFERS
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from tinygrad.helpers import PCONTIG, FLOAT16, OPENPILOT_HACKS, argsort, partition, get_single_element
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from tinygrad.codegen.simplify import pm_flatten_range, pm_reduce_simplify
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from tinygrad.codegen.opt import Opt
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from tinygrad.schedule.indexing import run_rangeify, BufferizeOpts, IndexingContext, apply_movement_op
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from tinygrad.schedule.multi import multi_pm
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from tinygrad.schedule.allreduce import create_allreduce_function
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# creation can recurse a lot
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import sys
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sys.setrecursionlimit(10000)
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def add_ranges_to_store(ctx, x):
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if x.src[0]._shape is None or x.src[1]._shape is None or x.src[0].shape == () or x.src[0].max_numel() == x.src[1].max_numel() == 1: return None
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assert x.src[0].shape == x.src[1].shape, "bad store shape"
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idxs = [UOp.range(r, next(ctx), AxisType.LOOP) for r in x.src[0].shape]
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return UOp.store(x.src[0].index(*idxs), x.src[1].index(*idxs)).end(*idxs)
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def lower_shaped_wmma(ctx, x):
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dims, device, threads = x.arg
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dtype_in, dtype_out = x.src[0].dtype.base, x.dtype
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upcasts = [(s, UOp.range(s.shape[-1], next(ctx), axis_type=AxisType.UPCAST)) for s in x.src]
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tc_upcast_axes = tuple(((u.arg[0], s.shape[-1]),) for s, u in upcasts)
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name = f"WMMA_{'_'.join(map(str, dims))}_{dtype_in.name}_{dtype_out.name}"
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wmma_arg = (name, dims, dtype_in, dtype_out, device, threads, tc_upcast_axes, ())
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wmma = UOp(Ops.WMMA, dtype_out, tuple(s[u].contract(u) for s, u in upcasts), arg=wmma_arg)
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tmp = UOp.placeholder((x.src[2].shape[-1],), dtype_out, slot=next(ctx), addrspace=AddrSpace.REG, is_ptr=False)
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return tmp.after(UOp.group(*[tmp[e].store(wmma.index(e)) for e in range(x.src[2].shape[-1])]))
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pm_store_ranges = PatternMatcher([
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(UPat(Ops.STORE, name="x"), add_ranges_to_store),
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])
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pm_syntactic_sugar = PatternMatcher([
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# INDEX on ptr INDEX concats them
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(UPat(Ops.INDEX, name="i1").f(Ops.INDEX, name="i2", allow_any_len=True),
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lambda i1,i2: i2.replace(src=i1.src+i2.src[1:]) if isinstance(i1.dtype, PtrDType) and not isinstance(i2.dtype, PtrDType) else None),
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# early rangeify
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(UPat(Ops.INDEX, src=(UPat(GroupOp.Elementwise | {Ops.CONST}, name="x"),), allow_any_len=True, name="idx"),
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lambda idx,x: x.replace(src=tuple([s.index(*idx.src[1:]) for s in x.src]))),
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])
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def found_after(ctx:dict[UOp, UOp], after:UOp, src:UOp):
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if (x:=src).op is Ops.CAST and x.dtype == dtypes.half and FLOAT16: x, after = x.src[0], after.cast(dtypes.float)
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while True:
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if x.op is Ops.PERMUTE: x, after = x.src[0], after.permute(argsort(x.marg))
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elif x.op is Ops.RESHAPE: x, after = x.src[0], after.reshape(x.src[0].shape)
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elif x.op is Ops.WHERE and x.src[2].base.arg == Invalid and x.src[1].op is Ops.PAD:
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x, after = x.src[1].src[0], after.shrink(tuple((o, s+o) for (o,_),s in zip(x.src[1].marg, x.src[1].src[0].shape)))
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else: break
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ctx[x] = after
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# *** fold moved AFTERs (hack for openpilot) ***
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pm_fold_moved_after = PatternMatcher([
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(UPat(Ops.AFTER, src=(UPat(), UPat(Ops.STORE, src=(UPat(), UPat((*GroupOp.Movement,Ops.CAST,Ops.WHERE), name="src")))), name="after"), found_after),
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# replace ALU sources with AFTER versions found above
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(UPat(GroupOp.ALU, name="alu"), lambda ctx,alu: alu.replace(src=new_src) if (new_src:=tuple(ctx.get(s, s) for s in alu.src)) != alu.src else None),
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])
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# movement op on INDEX as a PatternMatcher
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def _mop_index(r:UOp, idx:UOp):
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idxs = idx.src[1:]
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if len(idxs) == len(r.shape):
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return r.src[0].index(*apply_movement_op(r.op, r.src[0].shape, r.marg, idxs), dtype=idx.dtype, arg=idx.arg)
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if r.op is Ops.RESHAPE:
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src_prefix = len(r.src[0].shape) - len(r.shape[len(idxs):])
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if src_prefix >= 0 and r.src[0].shape[src_prefix:] == r.shape[len(idxs):]:
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if src_prefix == 0: return r.src[0] if r.src[0].dtype == idx.dtype else None
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ret = r.src[0].index(*apply_movement_op(r.op, r.src[0].shape[:src_prefix], r.shape[:len(idxs)], idxs), dtype=idx.dtype, arg=idx.arg)
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return ret if ret.shape == idx.shape else None
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pm_mops = PatternMatcher([
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# handle movement ops on INDEX
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(UPat(GroupOp.Movement, name="r").f(Ops.INDEX, allow_any_len=True, name="idx"), _mop_index),
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# move movement ops and INDEX after AFTER (but not when AFTER has a raw STORE with shaped children — from replace_contig_with_store_after)
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(UPat(GroupOp.Movement|{Ops.INDEX}, name="r").after(name="a", allow_any_len=True),
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lambda r,a: UOp(r.op, r.dtype, (a.replace(src=(r.src[0],)+a.src[1:]),)+r.src[1:], r.arg)),
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(UPat(GroupOp.Movement, name="r").end(name="a", allow_any_len=True), lambda r,a: a.replace(src=(r.src[0],)+a.src[1:])),
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# lower SHAPED_WMMA to WMMA
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(UPat(Ops.SHAPED_WMMA, name="x"), lower_shaped_wmma),
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])
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# *****************
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# 0. do some cleanup rewrites, mostly copied from the old stuff
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def fix_store_hazard(target:UOp, src:UOp):
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# PERMUTE and FLIP reorder indices, SHRINK can have overlapping regions when dest is also shrunk
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unsafe = {Ops.PERMUTE, Ops.FLIP} | ({Ops.SHRINK} if target.op_in_backward_slice_with_self(Ops.SHRINK) else set())
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base = target.base
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reaches_base: dict[UOp, bool] = {}
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for s in src.toposort(gate=lambda s: s.op is not Ops.CONTIGUOUS):
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reaches_base[s] = s is base or any(reaches_base.get(c) for c in s.src)
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if reaches_base[s] and s.op in unsafe and not (s is target and s.op is Ops.SHRINK): return target.store(src.contiguous())
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def split_reduceop(reduce:UOp, x:UOp):
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if prod(reduce.shape) == 0: return None
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if not SPLIT_REDUCEOP or not all_int(x.shape) or (prod(x.shape)//prod(reduce.shape))<getenv("REDUCEOP_SPLIT_THRESHOLD", 32768): return None
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# if there are few globals, make some reduces into globals by splitting into two kernels
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# cap output buffer to 2**22: heuristic number of global outputs to achieve max occupancy with enough locals+upcasts for gemm
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# ~2**10 should be enough if GROUP is used
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# 256 split maximum should be "negligible reduce" for low prod(reduce.shape), 8 split minimum.
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# split is moved to the end to provide maximum locality for the second phase reduce.
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# get expanded by rangeifying the UOp x
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indexed = x.index(*[UOp.range(s, i) if resolve(s>1) else UOp.const(dtypes.weakint, 0) for i,s in enumerate(x.shape)])
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range_nums = [y.arg[0] for y in indexed.substitute({x.base:UOp(Ops.NOOP)}, extra_pm=pm_mops).ranges]
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is_expanded = [i not in range_nums for i in range(len(x.shape))]
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if not (split_candidates:=[(i,d) for i in reduce.arg[1] for d in range(min(256,2**getenv("REDUCEOP_SPLIT_SIZE",22)//prod(reduce.shape)),8-1,-1)
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if x.shape[i]%d==0 and not is_expanded[i]]): return None
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dim_to_split, divisor = split_candidates[0]
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splitted_shape = x.shape[:dim_to_split]+(divisor,)+(x.shape[dim_to_split]//divisor,)+x.shape[dim_to_split+1:]
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splitted = x.reshape(splitted_shape).permute(tuple([d for d in range(len(splitted_shape)) if d!=dim_to_split]+[dim_to_split]))
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if DEBUG >= 3: print(f"split {divisor}: {x.shape} -> {splitted.shape} -> {reduce.shape}")
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# reduce original axes, then split
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return splitted._rop(*reduce.arg).contiguous()._rop(reduce.arg[0], (len(reduce.shape),)).reshape(reduce.shape)
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mop_cleanup = PatternMatcher([
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# merge adjacent RESHAPES
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(UPat(Ops.RESHAPE, src=(UPat(Ops.RESHAPE, name="x2"), UPat()), name="x"), lambda x,x2: x.replace(src=(x2.src[0], x.src[1]))),
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# remove noop RESHAPEs
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(UPat(Ops.RESHAPE, src=(UPat(name="x2"), UPat()), name="x"), lambda x,x2: x2 if x2._shape is not None and x2.shape == x.shape else None),
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# merge PERMUTEs
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(UPat(Ops.PERMUTE, src=(UPat(Ops.PERMUTE, name="x2"),), name="x"), lambda x,x2: x2.replace(arg=tuple(x2.arg[i] for i in x.arg))),
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# remove noop PERMUTEs
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(UPat(Ops.PERMUTE, name="x"), lambda x: x.src[0] if list(x.arg) == list(range(len(x.arg))) else None),
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])
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pm_gather_params = PatternMatcher([ (UPat(Ops.PARAM, name="p"), lambda ctx, p: ctx.append(p) if p.arg.slot >= 0 else None), ])
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def resolve_function(c:UOp, allow_param_mismatch=True) -> UOp|None:
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if c.arg.precompile: return None
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params: list[UOp] = []
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graph_rewrite(c.src[0], pm_gather_params, bottom_up=True, ctx=params, name="gather params")
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params = sorted(params, key=lambda x: x.arg.slot)
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args = c.src[1:]
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# NOTE: this isn't really needed. it's okay if there's unused args in the function
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if not allow_param_mismatch:
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if [x.arg.slot for x in params] != list(range(len(params))): raise RuntimeError(f"params not in order: {[x.arg.slot for x in params]}")
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if len(params) != len(args): raise TypeError(f"expected {len(params)} args, got {len(args)}")
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dict_map = {x:args[x.arg.slot] for x in params}
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for i, (p, a) in enumerate(dict_map.items()):
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if p.axis != a.axis: raise TypeError(f"arg {i} axis mismatch: expected {p.axis}, got {a.axis}")
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if p.max_shape != a.max_shape: raise TypeError(f"arg {i} shape mismatch: expected {p.shape}, got {a.shape}")
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if p.dtype != a.dtype: raise TypeError(f"arg {i} dtype mismatch: expected {p.dtype}, got {a.dtype}")
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return c.src[0].substitute(dict_map, walk=True)
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earliest_rewrites = mop_cleanup+PatternMatcher([
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# resolve FUNCTION calls (inline the body)
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(UPat(Ops.FUNCTION, name="c"), resolve_function),
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# resolve TUPLE+GETTUPLE
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(UPat(Ops.GETTUPLE, src=(UPat(Ops.TUPLE, name="t"),), name="g"), lambda g,t: t.src[g.arg]),
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# resolve allreduce (must be bottom up)
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(UPat(Ops.ALLREDUCE, src=(UPat.var("buf"),), name="red"), create_allreduce_function),
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# split_reduceop
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(UPat(Ops.REDUCE, name="reduce", src=(UPat.var("x"),)), split_reduceop),
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# remove DETACH/CONTIGUOUS_BACKWARD (TODO: this is copied in allocations)
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(UPat((Ops.DETACH, Ops.CONTIGUOUS_BACKWARD), name="x"), lambda x: x.src[0]),
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# remove contiguous on movement ops before a copy on disk
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(UPat(GroupOp.Movement-{Ops.SHRINK, Ops.RESHAPE}, name="x").f(Ops.CONTIGUOUS).f(Ops.COPY, allow_any_len=True, name="copy"),
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lambda x,copy: copy.replace(src=(x,)+copy.src[1:]) if isinstance(x.device, str) and x.device.startswith("DISK") else None),
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# push copy past movement ops to disk
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(UPat(GroupOp.Movement-{Ops.SHRINK, Ops.RESHAPE}, name="x").f(Ops.COPY, allow_any_len=True, name="copy"),
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lambda x,copy: x.replace(src=(copy.replace(src=(x.src[0],)+copy.src[1:]),)+x.src[1:]) \
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if isinstance(x.device, str) and x.device.startswith("DISK") else None),
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# SINK only ever references the base
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(UPat(Ops.SINK, name="x"), lambda x: x.replace(src=tuple(y.base for y in x.src))),
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# ** copy rules **
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# COPY transfers a contiguous range, so materialize a source that's resized (shrink/pad/expand) or reordered (permute/flip)
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(UPat(Ops.COPY, src=(UPat(GroupOp.Movement, name="r"),), name="c"),
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lambda c,r: c.replace(src=(r.contiguous(),)) if resolve(r.numel() != r.base.numel(), False) or r.contiguous_view_offset() is None else None),
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# copying mselect to same device is just mselect (no NOOP kernel)
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(UPat(Ops.COPY, src=(UPat(Ops.MSELECT, name="ms"),), name="copy"), lambda ms,copy: ms if ms.device == copy.device else None),
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# copy only to different device
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(UPat(Ops.COPY, src=(UPat.var("x"),), name="copy"), lambda x,copy: x.f(Ops.NOOP) if x.device == copy.device else None),
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# ** store rules **
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# fix store hazard (dest is in used in src) by adding contiguous: TestAssign.test_post_flipped_assignment
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(UPat(Ops.STORE, src=(UPat(name="target"), UPat(name="src"))), fix_store_hazard),
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# remove two STOREs that store the same thing to the same place: TestSchedule.test_dedup_assign
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(UPat.var("buf").after(UPat.var("buf").store(UPat.var("src")), name="a1").after(UPat.var("a1").store(UPat.var("src"))), lambda buf,src,a1:a1),
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# store a buffer's own current contents back into itself: TestAssign.test_nested_after_contiguous_store_no_init
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(UPat.var("buf").after(UPat.var("buf").store(UPat.var("buf").after(UPat.var("buf").store(UPat.var("src")), name="a1"))), lambda buf,src,a1:a1),
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# move bitcast from store dest to source: TestAssign.test_assign_bitcast
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(UPat(Ops.STORE, src=(UPat(Ops.BITCAST, src=(UPat(name="target"),)), UPat(name="src"))),
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lambda target, src: target.store(src.bitcast(target.dtype))),
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# ** size 0 **
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# reduce of size 0 is the identity element
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(UPat(Ops.REDUCE, name="reduce", src=(UPat.var("x"),)),
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lambda reduce,x: reduce.const_like(identity_element(reduce.arg[0], reduce.dtype)) if 0 in x.shape and 0 not in reduce.shape else None),
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# handle size 0
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(UPat(GroupOp.All-{Ops.SINK}, name="x"), lambda x: x.const_like(0).rtag(x.tag) if x._shape is not None and 0 in x.shape else None),
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])
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# *****************
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# 3.5 cleanups
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ALWAYS_RUN_OPS = {Ops.CONTIGUOUS, Ops.COPY, Ops.NOOP}
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# you don't know in the first pass if axes are going to die, this happens if there's an EXPAND to the left
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def cleanup_dead_axes(b:UOp):
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# don't optimize ALWAYS_RUN_OPS or AFTER (AFTER is a buffer identity — ranges define consumer access, not computation)
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if b.src[0].op in ALWAYS_RUN_OPS or b.src[0].op is Ops.AFTER: return None
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new_rng = []
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hit = False
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reshape: list[sint] = []
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for s,rng in zip(b.shape, b.src[1:]):
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# skip for symbolic. TODO: fix this
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if rng.op is Ops.RANGE and rng.src[0].op is not Ops.CONST: return None
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# CONSTs are already dead axes
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if rng.op is Ops.CONST or (rng.op is Ops.RANGE and rng not in b.src[0].ranges):
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reshape.append(1)
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hit = True
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else:
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reshape.append(s)
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new_rng.append(rng)
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if hit:
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return b.replace(src=b.src[0:1]+tuple(new_rng)).reshape(tuple(reshape)).expand(b.shape)
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def gate_substitute(ctx, b:UOp) -> None:
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if not any(r in b.ranges for r in ctx.keys()): raise BottomUpGate()
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pm_gate_substitute = PatternMatcher([(UPat(GroupOp.All, name="b"), gate_substitute)], compiled=False)
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# if a buffer is being stored just for permutes or something, remove it
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# we want to reexpress the indexes of idx2 in terms of the implied b1
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def remove_bufferize(src:UOp, buf:UOp, idx:UOp):
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# see if we can't do it, should this ever hit?
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assert len(buf.src) == len(idx.src), f"index on wrong bufferize, {len(buf.src)} != {len(idx.src)}"
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assert all(x.op in {Ops.RANGE, Ops.CONST} for x in buf.src[1:])
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# if it's user contiguous, we never remove it
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if src.op in ALWAYS_RUN_OPS or not buf.arg.removable: return None
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# *** here is where we compute the cost ***
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# if we return None, the bufferize is kept
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accessed_buffers: list[UOp] = []
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indexes: list[UOp] = []
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reduces: list[UOp] = []
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def red_gate(x:UOp):
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if x.op is Ops.AFTER:
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accessed_buffers.append(x.buf_uop)
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return False
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if (x.op is Ops.STAGE and x.arg.addrspace == AddrSpace.GLOBAL) or x.op is Ops.MSTACK:
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accessed_buffers.append(x)
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return False
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if x.op is Ops.STORE:
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# don't look inside stores, this doesn't count toward buffer accesses
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return False
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if x.op is Ops.PARAM:
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accessed_buffers.append(x)
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if x.op is Ops.INDEX:
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indexes.append(x)
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if x.op is Ops.REDUCE: reduces.append(x)
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return True
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src.toposort(gate=red_gate)
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del red_gate
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accessed_buffers = dedup(accessed_buffers)
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# if this is generated from multiple buffers, don't remove this buffer
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if len(accessed_buffers) > 3 and not (PCONTIG > 2): return None
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# if any reduces access a buffer, don't remove this buffer
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buffer_in_reduce = False
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def buf_gate(x:UOp):
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nonlocal buffer_in_reduce
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if x.op in {Ops.PARAM, Ops.STAGE, Ops.AFTER}: buffer_in_reduce = True
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return not buffer_in_reduce
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UOp.sink(*[x.src[0] for x in reduces]).toposort(gate=buf_gate)
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del buf_gate
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if buffer_in_reduce:
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if PCONTIG > 2:
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out_in_ratio = (prod(buf.shape)+1) / (sum([x.numel() for x in accessed_buffers])+1)
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if out_in_ratio < 10: return None
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# here we have to check the indexes, we might do a partial contig here
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local_indexes = [x for x in indexes if x.src[0].op is Ops.STAGE and x.src[0].arg.addrspace == AddrSpace.LOCAL]
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exclude_ranges = UOp.group(*[UOp.group(*x.src[1:]) for x in local_indexes]).ranges
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subs = [(k,v) for k,v in zip(buf.src[1:], idx.src[1:]) if k.op is not Ops.CONST]
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# if it's bufferized or a reduce, it's pcontig
|
|
is_pcontig, is_subs = partition(subs, lambda x: x[0] in exclude_ranges or any([r.arg[-1] == AxisType.REDUCE for r in x[1].ranges]))
|
|
if not len(is_subs):
|
|
return None
|
|
if len(is_pcontig):
|
|
ret = src.substitute(dict(is_subs), extra_pm=pm_gate_substitute)
|
|
return ret.bufferize(*[x[0] for x in is_pcontig], arg=BufferizeOpts(None, AddrSpace.LOCAL)).index(*[x[1] for x in is_pcontig])
|
|
else:
|
|
return None
|
|
|
|
# if it makes it here, the bufferize is removed
|
|
# this is the ranges replaced
|
|
# NOTE: if buf src is a const, we don't replace it. if idx is Invalid (dead load), don't replace it either
|
|
replaced = {k:v for k,v in zip(buf.src[1:], idx.src[1:]) if k.op is not Ops.CONST and not (v.op is Ops.CONST and v.arg is Invalid)}
|
|
return src.substitute(replaced, extra_pm=pm_gate_substitute)
|
|
|
|
def remove_noop_bufferize(idx,b2):
|
|
if idx.src[1:] != b2.src[1:] or idx.src[0].op is Ops.SLICE: return None
|
|
return idx.src[0].shrink(tuple((0, s) for s in b2.shape)) if b2.shape else idx.src[0]
|
|
|
|
def after_all_invalid(after:UOp):
|
|
buf = after.src[0].buf_uop
|
|
# check all ranges are used (no expand), and same size (no pad and shrink)
|
|
return all(s.op is Ops.END and (st:=s.src[0]).op is Ops.STORE and st.src[1].base.arg is Invalid and st.src[0].buf_uop is buf
|
|
and all(r in st.src[0].ranges for r in s.ended_ranges)
|
|
and resolve(cast(UOp, prod(r.src[0] for r in s.ended_ranges)).eq(buf.numel()), False) for s in after.src[1:])
|
|
|
|
pm_const_buffer_folding = pm_mops+PatternMatcher([
|
|
(UPat(Ops.STAGE, name="b"), cleanup_dead_axes),
|
|
# remove noop buffers. if we look at the next index we can remove even more of these
|
|
(UPat(Ops.INDEX, name="idx").f(Ops.STAGE, allow_any_len=True, name="b2"), remove_noop_bufferize),
|
|
(UPat(Ops.INDEX, src=(UPat(Ops.STAGE),), allow_any_len=True, name="idx").f(Ops.NOOP).f(Ops.STAGE, allow_any_len=True, name="b2"),
|
|
remove_noop_bufferize),
|
|
# no buffers for const (ranges don't matter for const - it's the same value everywhere)
|
|
(UPat(Ops.CONST, name='c').f(Ops.STAGE, allow_any_len=True, name="b"), lambda c,b: b.const_like(c.arg)),
|
|
# indexing a const is a const
|
|
(UPat(Ops.INDEX, src=(UPat(Ops.CONST, name="c"),),), lambda c: c),
|
|
# indexing an after with all fully invalid stores is invalid
|
|
(UPat(Ops.INDEX, src=(UPat(Ops.AFTER, name="after"),), allow_any_len=True, name="idx"),
|
|
lambda idx,after: idx.const_like(Invalid) if after_all_invalid(after) else None),
|
|
# copy on CONST is CONST
|
|
(UPat(Ops.COPY, src=(UPat.cvar("x"),), name="copy"), lambda copy,x: copy.const_like(x.arg)),
|
|
# hack if a noop turned to a const
|
|
(UPat(Ops.NOOP, src=(UPat.cvar("c"),)), lambda c: c),
|
|
# mstack on CONST is CONST
|
|
(UPat(Ops.MSTACK, src=(UPat.var("s"),), allow_any_len=True).f(Ops.INDEX, allow_any_len=True),
|
|
lambda s: UOp.const(c.dtype, c.arg) if (c:=s.base).op is Ops.CONST else None),
|
|
])
|
|
|
|
pm_remove_bufferize = PatternMatcher([
|
|
# remove reindexing with cost function
|
|
(UPat.var("src").f(Ops.STAGE, allow_any_len=True, name="buf").f(Ops.INDEX, allow_any_len=True, name="idx"), remove_bufferize),
|
|
# STORE to self is NOOP
|
|
(UPat.var("x").store(UPat.var("x")), lambda x: UOp(Ops.NOOP)),
|
|
# END on NOOP is NOOP
|
|
(UPat(Ops.END, src=(UPat(Ops.NOOP, name="x"),), allow_any_len=True), lambda x: x),
|
|
])
|
|
|
|
def late_buffer_view(t:UOp, b:UOp):
|
|
if not (isinstance(b.device, str) and b.device.startswith(("DISK", "TINYFS"))): return b
|
|
shape = b.shape
|
|
size = prod(shape)
|
|
|
|
# walk up for the INDEX
|
|
x = t
|
|
while not any(u.op is Ops.INDEX for u in x.src):
|
|
assert x.op not in GroupOp.Elementwise, "can't buffer view elementwise"
|
|
x = x.src[0]
|
|
x = next(u for u in x.src if u.op is Ops.INDEX)
|
|
assert x.op is Ops.INDEX, "must be INDEX"
|
|
|
|
if len(shape) == 0: offset = x.src[1].arg
|
|
else: offset = max(sum(idx.vmin for idx in x.src[1:]), 0)
|
|
|
|
return b.replace(src=(UOp(Ops.SLICE, t.dtype, (x.src[0], UOp.const(dtypes.weakint, offset)), size),))
|
|
|
|
to_bufferview = PatternMatcher([
|
|
(UPat(Ops.STAGE, src=(UPat((Ops.BITCAST, Ops.CONTIGUOUS), name="t"), UPat()), name="b"), late_buffer_view),
|
|
])
|
|
|
|
DEVICE_MAX_BUFS = {"METAL": 31, "WEBGPU": 8} # TODO: get from device?
|
|
def limit_bufs(ctx:IndexingContext, root:UOp):
|
|
if (device:=root.device) is None: return None # no device, index related calculations
|
|
device = device if isinstance(device, str) else device[0].split(":")[0]
|
|
if not (MAX_BUFS:=MAX_KERNEL_BUFFERS.value or DEVICE_MAX_BUFS.get(device, 0)): return None
|
|
|
|
bufs: set[UOp] = set()
|
|
def gate_input(u:UOp):
|
|
# TODO: add cache to fix n^2
|
|
if is_load:=(u.op in {Ops.STAGE, Ops.AFTER, Ops.PARAM, Ops.MSELECT, Ops.MSTACK}): bufs.add(u)
|
|
return not is_load
|
|
root.toposort(gate=gate_input)
|
|
|
|
if len(bufs) > MAX_BUFS - 1: # NOTE: this -1 is for the output buffer
|
|
srcs = []
|
|
for s in root.src:
|
|
if s.op in GroupOp.Elementwise and s.device is not None:
|
|
# Insert bufferize: all AxisType.REDUCE before bufferize are AxisType.LOOP
|
|
orig_ranges, end_ranges = s.ranges, [x.replace(arg=(next(ctx.range_idx), AxisType.LOOP)) if x.op is Ops.RANGE else x for x in s.ranges]
|
|
s = s.substitute(dict(zip(orig_ranges, end_ranges))).bufferize(*end_ranges, arg=BufferizeOpts(device=s.device)).index(*orig_ranges)
|
|
srcs.append(s)
|
|
return root.replace(src=tuple(srcs))
|
|
pm_limit_bufs = PatternMatcher([(UPat(set.union(GroupOp.Binary, GroupOp.Ternary), name="root"), limit_bufs)])
|
|
|
|
# *****************
|
|
# 4. put in buffers for bufferize
|
|
# TODO: should BUFFERIZE look a lot more like STORE
|
|
# BUFFERIZE has device in arg
|
|
# BUFFERIZE doesn't have indexing, that's implied by the ranges it closes
|
|
# BUFFERIZE returns the BUFFER ready for INDEXing (doing this will make splitting a lot easier)
|
|
# NOTE: this has been fixed up a bit
|
|
|
|
def bufferize_to_store(ctx:itertools.count, x:UOp, idx:UOp, allow_locals=True):
|
|
size = prod(x.shape) // x.dtype.count
|
|
rngs = sorted(idx.ranges, key=lambda x: x.arg)
|
|
assert size > 0 and isinstance(size, int), f"no zero sized or symbolic sized buffers {size}"
|
|
|
|
# AFTER: add END to the existing STORE, return buffer with kernel dependency
|
|
if (after:=x.src[0]).op is Ops.AFTER:
|
|
buf = after.src[0].buf_uop.base
|
|
if not (stores := [s for s in after.src[1:] if s.op is Ops.STORE and s.src[0].op is Ops.INDEX]): return buf
|
|
# BUFFERIZE(INDEX(...)); store through the underlying global index instead.
|
|
ended_stores = []
|
|
for store in stores:
|
|
store_target = store.src[0]
|
|
if store_target.src[0].op is Ops.STAGE and store_target.src[0].src[0].op is Ops.INDEX:
|
|
store_target = store_target.src[0].src[0]
|
|
if store.src[1] is store_target: continue # skip self-assign
|
|
end_rngs = sorted(dedup(tuple(store_target.ranges) + tuple(rngs)), key=lambda x: x.arg)
|
|
ended_stores.append(store_target.store(store.src[1]).end(*end_rngs))
|
|
return buf.after(*ended_stores)
|
|
|
|
# NOTE: the local BUFFER needs to be disambiguated here
|
|
if x.arg.addrspace == AddrSpace.GLOBAL:
|
|
buf = UOp(Ops.BUFFER, x.dtype, (shape_to_shape_arg((size,)),), ParamArg(next(ctx), device=x.arg.device, addrspace=AddrSpace.GLOBAL))
|
|
if x.src[0].op is Ops.SLICE:
|
|
# no INDEX on SLICE, this could be cleaner
|
|
do_store = buf.store(x.src[0]).end(*rngs)
|
|
else:
|
|
do_store = buf.index(idx).store(x.src[0]).end(*rngs)
|
|
return buf.after(do_store)
|
|
|
|
if allow_locals:
|
|
# handle locals
|
|
buf = UOp.placeholder((size,), x.dtype, next(ctx), AddrSpace.LOCAL, is_ptr=False)
|
|
do_store = buf.broadcast(x.src[1].dtype.count).index(idx).store(x.src[0]).end(*rngs)
|
|
return buf.after(do_store.barrier())
|
|
|
|
# collapse any BUFFERIZE to single input BUFFERIZE
|
|
def flatten_bufferize(x:UOp):
|
|
if len(x.src) == 2: return None
|
|
ret = x.replace(src=(x.src[0], get_single_element(apply_movement_op(Ops.RESHAPE, (prod(x.shape),), x.shape, x.src[1:]))))
|
|
rngs = x.src[1:]
|
|
ret = ret.reshape(x.shape)
|
|
if any(r.op is Ops.RANGE and r.src[0].op is not Ops.CONST for r in rngs):
|
|
sym_shape = tuple([r.src[0] if r.op is not Ops.CONST else 1 for r in rngs])
|
|
ret = ret.shrink(tuple([(0,x) for x in sym_shape]))
|
|
return ret
|
|
pm_flatten_bufferize = PatternMatcher([(UPat(Ops.STAGE, name="x"), flatten_bufferize)])
|
|
|
|
def is_noop_after_dep(x:UOp) -> bool:
|
|
return (x.op is Ops.NOOP and len(x.src) == 0) or (x.op is Ops.END and is_noop_after_dep(x.src[0]))
|
|
|
|
def remove_noop_afters(x:UOp) -> UOp|None:
|
|
src = (x.src[0],) + tuple(s for s in x.src[1:] if not is_noop_after_dep(s))
|
|
if len(src) != len(x.src): return src[0] if len(src) == 1 else x.replace(src=src)
|
|
return None
|
|
|
|
pm_add_buffers = pm_mops+pm_flatten_bufferize+to_bufferview+PatternMatcher([
|
|
(UPat(Ops.STAGE, src=(UPat(), UPat(name="idx")), name="x"), lambda ctx,x,idx: bufferize_to_store(ctx, x, idx, allow_locals=False)),
|
|
|
|
# move RESHAPEs through MSELECT/MSTACK
|
|
(UPat((Ops.MSELECT, Ops.MSTACK), src=UPat(Ops.RESHAPE), name="m"),
|
|
lambda m: m.replace(src=tuple([x.src[0].base for x in m.src])).reshape(m.shape)),
|
|
|
|
# remove any RESHAPEs on KERNEL
|
|
(UPat(Ops.CALL, name="k"), lambda k: k.replace(src=tuple(x.src[0] if x.op is Ops.RESHAPE else x for x in k.src))),
|
|
|
|
# remove invalid writes
|
|
(UPat(Ops.STORE, src=(UPat(), UPat(Ops.CONTIGUOUS, src=(UPat(Ops.CONST, arg=Invalid),)))), lambda: UOp(Ops.NOOP)),
|
|
(UPat(Ops.STORE, src=(UPat(), UPat(Ops.CONST, arg=Invalid))), lambda: UOp(Ops.NOOP)),
|
|
(UPat(Ops.AFTER, name="x"), remove_noop_afters),
|
|
])
|
|
|
|
# *****************
|
|
# 5. split into kernels
|
|
|
|
@dataclass
|
|
class LocalAddBufferContext:
|
|
dg:int = 0
|
|
map:dict = field(default_factory=dict)
|
|
vars:dict = field(default_factory=dict)
|
|
range:int = 0
|
|
opts:tuple|None = None
|
|
|
|
def debuf(ctx:LocalAddBufferContext, buf:UOp):
|
|
param = UOp(Ops.PARAM, buf.dtype, (UOp.const(dtypes.int, prod(buf.max_shape)),),
|
|
arg=ParamArg(ctx.dg, addrspace=buf.addrspace, device=buf.device))
|
|
ret = param.reshape(buf.max_shape)
|
|
# if the buffer has symbolic shape, shrink the max-sized view to the actual shape
|
|
if buf.max_shape != buf.shape: ret = ret.shrink(tuple((0, s) for s in buf.shape))
|
|
if buf not in ctx.map: ctx.map[buf] = buf
|
|
ctx.dg += 1
|
|
return ret
|
|
|
|
def unbind_kernel(ctx:LocalAddBufferContext, b:UOp):
|
|
ctx.vars[b] = None
|
|
return b.src[0]
|
|
|
|
def handle_after(ctx:LocalAddBufferContext, after:UOp):
|
|
if after.addrspace == AddrSpace.LOCAL: return None
|
|
buf = after.buf_uop
|
|
# NOTE: this is bottom up, so we only add it once
|
|
if buf not in ctx.map: ctx.map[buf] = after
|
|
return buf
|
|
|
|
def renumber_range(ctx:LocalAddBufferContext, r:UOp):
|
|
if r.tag != (): return None
|
|
ret = r.replace(arg=(ctx.range,)+r.arg[1:], tag=None)
|
|
ctx.range += 1
|
|
return ret
|
|
|
|
def find_bufs(x:UOp):
|
|
idxs = [s for s in x.toposort(gate=lambda x: x.op is not Ops.AFTER) if s.op is Ops.INDEX]
|
|
read_from: dict[UOp, Ops] = {}
|
|
if any((buf:=idx.buf_uop).op in {Ops.BUFFER, Ops.PARAM} and read_from.setdefault(buf, op:=idx.src[0].op) is not op for idx in idxs):
|
|
raise RuntimeError(f"cycle detected while indexing {buf}")
|
|
|
|
to_define_global = PatternMatcher([
|
|
(UPat(Ops.STORE, name="x"), find_bufs),
|
|
(UPat((Ops.BUFFER, Ops.MSTACK, Ops.MSELECT), name="buf"), debuf),
|
|
(UPat(Ops.PARAM, name="v"), lambda v:
|
|
UOp.variable(v.arg.name, v.arg.vmin_vmax[0], v.arg.vmin_vmax[1], v.dtype)
|
|
if v.arg.name is not None and v.arg.vmin_vmax is not None else None),
|
|
|
|
# this renumbers the params
|
|
(UPat(Ops.PARAM, name="buf"), lambda ctx, buf:
|
|
None if buf.tag != () or isinstance(buf.dtype, PtrDType) or buf.arg.name is not None or buf._shape is None else debuf(ctx, buf)),
|
|
|
|
# ALU params are scalar symbolic values, not buffers.
|
|
(UPat(Ops.INDEX, src=(UPat(Ops.PARAM, name="v"),)), lambda v: v if v.addrspace == AddrSpace.ALU else None),
|
|
|
|
(UPat(Ops.BIND, name="b"), unbind_kernel),
|
|
(UPat(Ops.AFTER, name="after"), handle_after),
|
|
|
|
# remove device from local BUFFERIZE
|
|
(UPat(Ops.STAGE, name="b"), lambda b: b.replace(arg=replace(b.arg, device=None))),
|
|
|
|
# renumber the ranges starting with 0 so that kernel deduping works
|
|
(UPat(Ops.RANGE, name="r"), renumber_range),
|
|
])
|
|
|
|
def get_contiguous(ctx:LocalAddBufferContext, x:UOp):
|
|
if isinstance(x.arg, tuple) and all(isinstance(y, Opt) for y in x.arg): ctx.opts = x.arg
|
|
return x.src[0]
|
|
|
|
rangeify_codegen = PatternMatcher([
|
|
(UPat(Ops.CONTIGUOUS, name="x"), get_contiguous),
|
|
|
|
# no NOOP in the kernel graph
|
|
# TODO: this can be moved into codegen?
|
|
(UPat(Ops.NOOP, name="x"), lambda x: x.src[0] if len(x.src) else None),
|
|
|
|
(UPat(Ops.BUFFER).f(Ops.AFTER, allow_any_len=True).broadcast(name="dg").f(Ops.INDEX, name="idx", allow_any_len=True),
|
|
lambda dg,idx: None if dg.addrspace is not AddrSpace.LOCAL else
|
|
idx.replace(dtype=dg.dtype, arg=None).load(dtype=dg.dtype.base.scalar())),
|
|
(UPat(Ops.BUFFER).f(Ops.AFTER, allow_any_len=True).gep(name="dg").f(Ops.INDEX, name="idx", allow_any_len=True),
|
|
lambda dg,idx: None if dg.addrspace is not AddrSpace.LOCAL else
|
|
idx.replace(dtype=dg.dtype, arg=None).load(dtype=dg.dtype.base.scalar())),
|
|
])
|
|
|
|
pm_add_param_range_tags = PatternMatcher([
|
|
(UPat((Ops.PARAM, Ops.RANGE), name="x"), lambda x: x.rtag(())),
|
|
])
|
|
|
|
def split_store(x:UOp) -> UOp|None:
|
|
# if we have any open ranges here, we don't split
|
|
if x.ranges: return None
|
|
|
|
# local kernel rewrite
|
|
lctx = LocalAddBufferContext()
|
|
ret = graph_rewrite(x, to_define_global+pm_flatten_range+rangeify_codegen, ctx=lctx, name="kernel split", bottom_up=True)
|
|
|
|
# SINK requires all buffers on the same device, but COPY/SLICE are cross-device or special hardware ops
|
|
if ret.op is Ops.STORE: stored = ret.src[1]
|
|
elif ret.op is Ops.END and ret.src[0].op is Ops.STORE: stored = ret.src[0].src[1]
|
|
else: raise RuntimeError(f"unknown kernel type {ret.op}")
|
|
if stored.op in {Ops.COPY, Ops.SLICE}: ret = stored.replace(src=stored.src + ret.ended_ranges)
|
|
else: ret = ret.sink(arg=KernelInfo(opts_to_apply=lctx.opts))
|
|
|
|
kernel = ret.call(*lctx.map.values(), *lctx.vars.keys())
|
|
if ret.op is Ops.SINK and not all_same([x.device for x in kernel.src[1:] if x.op is not Ops.BIND]):
|
|
raise RuntimeError(f"all buffers must be on the same device: {tuple(b.buf_uop for b in kernel.src[1:])}")
|
|
return kernel
|
|
|
|
split_kernels = PatternMatcher([
|
|
(UPat((Ops.STORE, Ops.END), name="x"), split_store),
|
|
])
|
|
|
|
@profile_matches
|
|
def get_kernel_graph(sink:UOp) -> UOp:
|
|
tsink = graph_rewrite(sink, multi_pm, name="multi_pm")
|
|
if OPENPILOT_HACKS: tsink = graph_rewrite(tsink, pm_fold_moved_after, ctx={}, name="fold moved afters")
|
|
tsink = graph_rewrite(tsink, pm_syntactic_sugar+pm_mops+earliest_rewrites, bottom_up=True, name="earliest rewrites")
|
|
|
|
# convert movement ops to ranges
|
|
tsink, rctx = run_rangeify(tsink, bool(DEBUG_RANGEIFY))
|
|
|
|
tsink = graph_rewrite(tsink, symbolic+pm_reduce_simplify+pm_const_buffer_folding+pm_remove_bufferize, name="symbolic+reduce_collapse+debuf")
|
|
tsink = graph_rewrite(tsink, pm_limit_bufs, ctx=rctx, name="limit buffers")
|
|
|
|
if VIZ: graph_rewrite(tsink, PatternMatcher([]), name="View Rangeify")
|
|
|
|
# bufferize -> store
|
|
slots = [x.arg.slot for x in tsink.toposort() if x.op is Ops.BUFFER and isinstance(x.arg, ParamArg) and x.addrspace is AddrSpace.GLOBAL]
|
|
paramarg_start: int = max([-1]+slots) + 1
|
|
tsink = graph_rewrite(tsink, pm_add_buffers+pm_add_param_range_tags, ctx=itertools.count(paramarg_start), bottom_up=True, name="stage to store")
|
|
tsink = graph_rewrite(tsink, split_kernels, bottom_up=True, name="split kernels")
|
|
|
|
if VIZ: graph_rewrite(tsink, PatternMatcher([]), name="View Kernel Graph")
|
|
return tsink
|