diff --git a/tinygrad/codegen/__init__.py b/tinygrad/codegen/__init__.py
index cc7c2b9d53..428218408f 100644
--- a/tinygrad/codegen/__init__.py
+++ b/tinygrad/codegen/__init__.py
@@ -1,30 +1,30 @@
 from dataclasses import replace
-import itertools
+import itertools, functools
 from tinygrad.helpers import DISABLE_FAST_IDIV, TRANSCENDENTAL, SPEC, DEBUG, VIZ, IMAGE, NOOPT, EMULATED_DTYPES, NOLOCALS, USE_TC
-from tinygrad.helpers import ALLOW_TF32, TracingKey, Context, panic
+from tinygrad.helpers import ALLOW_TF32, TracingKey, Context, panic, all_same, flatten
 from tinygrad.uop.ops import PatternMatcher, graph_rewrite, UOp, pm_lower_index_dtype, Ops, UPat, track_rewrites, KernelInfo, ProgramInfo, GroupOp
 from tinygrad.uop.render import pyrender
 from tinygrad.uop.spec import type_verify, spec_tensor, spec_program
 from tinygrad.renderer import Renderer, Estimates
 from tinygrad.renderer.isa import ISARenderer, IselContext, PreRegAllocContext
-from tinygrad.dtype import dtypes, PtrDType, ImageDType
+from tinygrad.dtype import dtypes, PtrDType, ImageDType, AddrSpace
 
 # import all pattern matchers here
 from tinygrad.codegen.gpudims import pm_add_gpudims
-from tinygrad.uop.symbolic import sym, symbolic_simple, gep_pushing, symbolic, pm_move_where_on_load, pm_clean_up_group_sink, pm_remove_invalid
+from tinygrad.uop.symbolic import sym, symbolic_simple, symbolic, pm_move_where_on_load, pm_clean_up_group_sink
 from tinygrad.codegen.decomp.dtype import pm_dtype_decomps
 from tinygrad.codegen.decomp.op import get_late_rewrite_patterns, get_simplifying_rewrite_patterns
 from tinygrad.codegen.decomp.transcendental import get_transcendental_patterns
 from tinygrad.codegen.late.expander import expander, pm_pre_expander, pm_group_for_reduce
-from tinygrad.codegen.late.devectorizer import load_store_folding, indexing_simplify, devectorize_buf_and_index, devectorize_alu, pm_reduce, \
-  ReduceContext, pm_render, pm_add_loads
+from tinygrad.codegen.late.devectorizer import indexing_simplify, ReduceContext, pm_render, merge_reduce_ends
 from tinygrad.codegen.opt.postrange import apply_opts
 from tinygrad.codegen.late.gater import pm_move_gates_from_index
 from tinygrad.codegen.simplify import pm_simplify_ranges, pm_flatten_range, pm_split_ranges, pm_load_collapse
-from tinygrad.schedule.rangeify import pm_add_buffers_local, rangeify_codegen, pm_mops, pm_syntactic_sugar, pm_store_ranges
+from tinygrad.schedule.rangeify import pm_mops, pm_syntactic_sugar, pm_store_ranges
 from tinygrad.codegen.late.linearizer import CFGContext, pm_split_ends, pm_add_control_flow, linearize
 from tinygrad.codegen.late.regalloc import LinearScanRegallocContext, pm_regalloc_rewrite
 from tinygrad.codegen.late.coalese import memory_coalesing, pm_simplify_add_image
+from tinygrad.uop.ops import identity_element
 
 pm_remove_vec_dtypes = PatternMatcher([
   # rewrite PARAM to non pointer
@@ -36,6 +36,9 @@ pm_remove_vec_dtypes = PatternMatcher([
    lambda x: x.replace(dtype=x.dtype.base.scalar().base)),
   # rewrite GEP to INDEX
   (UPat(Ops.GEP, name="x"), lambda x: x.replace(op=Ops.INDEX, src=x.src+(UOp.const(dtypes.int, x.arg if len(x.arg) > 1 else x.arg[0]),), arg=None)),
+  # don't stack PARAMs/BUFFERs on INDEX. TODO: this is an expander bug
+  (UPat(Ops.INDEX, src=(UPat(Ops.STACK, src=UPat((Ops.PARAM, Ops.BUFFER), name="b")),), allow_any_len=True, name="idx"),
+   lambda b,idx: idx.replace(src=(b,)+idx.src[1:])),
 ])+pm_clean_up_group_sink
 
 def do_number_param(ctx:list[int], x:UOp):
@@ -51,6 +54,80 @@ pm_no_weakints = PatternMatcher([
   (UPat(GroupOp.All, dtype=dtypes.weakint, name="x"), lambda x: x.replace(dtype=dtypes.int))
 ])
 
+def maybe_load(u:UOp): return u.load() if u.addrspace in (AddrSpace.GLOBAL, AddrSpace.LOCAL, AddrSpace.REG) else u
+pm_move_regs = PatternMatcher([
+  # BITCAST?
+  (UPat(GroupOp.Elementwise|{Ops.REDUCE}, name="x"), lambda x: x.replace(src=tuple([maybe_load(u) for u in x.src]))),
+  (UPat(Ops.STORE, name="x"), lambda x: x.replace(src=(x.src[0], maybe_load(x.src[1]))+x.src[2:])),
+])
+
+def do_devectorize(b:UOp):
+  if b.shape == (): return None
+  # broadcasting needs to be already unpacked
+  if not all_same([x.shape for x in b.src]): return None
+  src = []
+  for idx in itertools.product(*[range(x) for x in b.shape]):
+    idx_c = [UOp.const(dtypes.weakint, i) for i in idx]
+    src.append(b.replace(src=tuple([x.index(*idx_c) for x in b.src])))
+  return UOp.vectorize(*src).reshape(b.shape) if b.op is not Ops.STORE else UOp.group(*src)
+
+devectorizer2 = pm_mops+PatternMatcher([
+  # unpack broadcasting
+  (UPat(GroupOp.Elementwise|{Ops.LOAD,Ops.STORE}, name="b"), do_devectorize),
+  # const INDEX into STACK is src
+  (UPat(Ops.INDEX, src=(UPat(Ops.STACK, name="a"), UPat.cvar("i"))), lambda a,i: a.src[i.arg]),
+  # stacked INDEX is many INDEX
+  (UPat(Ops.INDEX, src=(UPat((Ops.PARAM, Ops.BUFFER), name="b"), UPat(Ops.STACK, name="s"))),
+   lambda b,s: UOp.vectorize(*[b.index(u) for u in s.src])),
+  # INDEX into RESHAPE moves the RESHAPE
+  (UPat(Ops.INDEX, src=(UPat((Ops.PARAM, Ops.BUFFER), name="b"), UPat(Ops.RESHAPE, name="s"))),
+   lambda b,s: b.index(s.src[0]).reshape(s.shape)),
+  # RESHAPE a void is removed (hack for AFTER)
+  (UPat(Ops.RESHAPE, dtype=dtypes.void, name="x"), lambda x: x.src[0]),
+  # reshape of a single element shaped value to scalar is an index
+  (UPat(Ops.RESHAPE, name="x"), lambda x: x.src[0].index(UOp.const(dtypes.weakint, 0)) if x.marg == () and x.src[0].shape == (1,) else None),
+  # INDEX without src is nothing
+  (UPat(Ops.INDEX, src=(UPat.var('x'),)), lambda x: x),
+  # RESHAPE+EXPAND -> STACK
+  (UPat(Ops.EXPAND, src=(UPat(Ops.RESHAPE, src=(UPat.var("x"), UPat())), UPat()), name="out"),
+   lambda x,out: UOp.vectorize(*([x]*out.max_numel())) if out.shape == (out.max_numel(),) else None),
+  # INDEX on INDEX is INDEX
+  (UPat(Ops.INDEX, src=(UPat(Ops.INDEX, name="idx1", allow_any_len=True),), allow_any_len=True, name="idx2"),
+   lambda idx1, idx2: idx1.src[0].index(*idx1.src[1:], *idx2.src[1:])),
+])
+
+def reduce_ranges_to_acc(ctx:ReduceContext, r:UOp):
+  acc = UOp.placeholder_like(r, ctx.acc_num, AddrSpace.REG)
+  ctx.acc_num += 1
+  topo = r.src[0].toposort()
+  ended_ranges = flatten([x.ended_ranges for x in topo if x.op is Ops.END])
+  input_ranges = tuple(x for x in topo if x.op is Ops.RANGE and x not in r.src[1:] and x not in ended_ranges)
+  acc_init = acc.after(*input_ranges).store(identity_element(r.arg[0], r.dtype.scalar()))
+  acc_initted = acc.after(acc_init, *r.src[1:])
+  inp = r.src[0].reduce(arg=r.arg) if r.arg[1] else r.src[0]
+  acc_out = acc_initted.store(acc_initted.alu(r.arg[0], inp)).end(*r.src[1:]).rtag("mergeable")
+  return acc.after(acc_out)
+
+def expand_horizontal_reduce(r:UOp):
+  axes = r.arg[1]
+  vals = [r.src[0].shrink(tuple((idx[axes.index(i)], idx[axes.index(i)]+1) if i in axes else None for i in range(r.src[0].ndim)))
+          for idx in itertools.product(*[range(r.src[0].max_shape[a]) for a in axes])]
+  return functools.reduce(lambda x,y: x.alu(r.arg[0], y), vals)
+
+pm_reduce_local = PatternMatcher([
+  (UPat(Ops.REDUCE, src=(UPat(), UPat()), allow_any_len=True, name="r"), reduce_ranges_to_acc),
+  (UPat(Ops.REDUCE, src=(UPat(),), name="r"), expand_horizontal_reduce),
+  (UPat(Ops.SINK, name="sink"), merge_reduce_ends),
+])+pm_clean_up_group_sink
+
+def add_local_buffer(ctx, x:UOp):
+  buf = UOp.placeholder(x.max_shape, x.dtype, slot=next(ctx), addrspace=x.arg.addrspace)
+  return buf.after(buf.index(*x.src[1:]).store(x.src[0]).end(*x.src[1:]).barrier())
+
+pm_add_local_buffers = PatternMatcher([
+  (UPat(Ops.STAGE, name="x"), add_local_buffer),
+])+pm_mops
+
 def full_rewrite_to_sink(ast:UOp, ren:Renderer, optimize:bool=True) -> UOp:
   if VIZ: graph_rewrite(ast, PatternMatcher([]), name="View Base AST")
   if DEBUG >= 5: print(pyrender(ast))
@@ -82,12 +159,22 @@ def full_rewrite_to_sink(ast:UOp, ren:Renderer, optimize:bool=True) -> UOp:
   # expand
   sink = graph_rewrite(sink, sym+pm_pre_expander+pm_group_for_reduce+expander, name="expander")
 
+  # this is new style (TODO: this should all be removed)
+  sink = graph_rewrite(sink, pm_render, name="pm_render gep/stack")
+  sink = graph_rewrite(sink, pm_remove_vec_dtypes, name="transform to new style")
+
+  # ****** new style ******
+
   # add locals
-  sink = graph_rewrite(sink, pm_add_buffers_local+rangeify_codegen, ctx=itertools.count(0), name="add local buffers")
+  sink = graph_rewrite(sink, pm_add_local_buffers, ctx=itertools.count(0), name="add local buffers")
+  sink = graph_rewrite(sink, pm_reduce_local, ctx=ReduceContext(), name="remove_reduce")
+
+  # add locals
+  #sink = graph_rewrite(sink, pm_add_buffers_local+rangeify_codegen, ctx=itertools.count(0), name="add local buffers")
 
   # ** devectorizer (full_graph_rewrite) **
   # remove reduce
-  sink = graph_rewrite(sink, pm_reduce+gep_pushing, ctx=ReduceContext(), name="remove_reduce")
+  #sink = graph_rewrite(sink, pm_reduce+gep_pushing, ctx=ReduceContext(), name="remove_reduce")
 
   # add gpu dims (late). this works after devectorize, but it's faster here
   sink = graph_rewrite(sink, pm_add_gpudims, ctx=ren, name="add gpudims")
@@ -95,14 +182,16 @@ def full_rewrite_to_sink(ast:UOp, ren:Renderer, optimize:bool=True) -> UOp:
   # **** optimizations are done, now we lower to actual code ****
 
   # add loads and remove invalids
-  sink = graph_rewrite(sink, pm_add_loads+pm_remove_invalid, name="** add loads (code)")
+  #sink = graph_rewrite(sink, pm_add_loads+pm_remove_invalid, name="** add loads (code)")
 
   # devectorize
-  sink = graph_rewrite(sink, sym+devectorize_alu+devectorize_buf_and_index+load_store_folding, ctx=ren, name="devectorize")
+  #sink = graph_rewrite(sink, sym+devectorize_alu+devectorize_buf_and_index+load_store_folding, ctx=ren, name="devectorize")
 
-  # this is new style (TODO: this should all be removed)
-  sink = graph_rewrite(sink, pm_render, name="pm_render gep/stack")
-  sink = graph_rewrite(sink, pm_remove_vec_dtypes, name="transform to new style")
+  # add loads
+  sink = graph_rewrite(sink, pm_move_regs, name="** add loads")
+
+  # devectorize
+  sink = graph_rewrite(sink, symbolic_simple+devectorizer2, ctx=ren, name="devectorize2")
 
   # simplify indexing
   sink = graph_rewrite(sink, indexing_simplify, name="simplify load/store indexing")
diff --git a/tinygrad/codegen/gpudims.py b/tinygrad/codegen/gpudims.py
index 7ffd44c2cc..5282af4bb4 100644
--- a/tinygrad/codegen/gpudims.py
+++ b/tinygrad/codegen/gpudims.py
@@ -96,7 +96,7 @@ def add_gpudims(ctx:Renderer, s:UOp):
       if len(missing_locals):
         assert len(idx.src) == 2, "index has 2 sources"
         mask: UOp = UOp.uprod(*[x.eq(0) for x in missing_locals])
-        subs[idx] = idx.replace(src=(idx.src[0], mask.broadcast(idx.src[1].dtype.count).where(idx.src[1], Invalid)))
+        subs[idx] = idx.replace(src=(idx.src[0], mask.broadcast(idx.src[1].max_numel()).where(idx.src[1], Invalid)))
     if r.op is not Ops.RANGE: continue
     try:
       ii = (global_dims+local_dims).index(r.arg[0:-1])
diff --git a/tinygrad/uop/ops.py b/tinygrad/uop/ops.py
index 4ef821d952..3794fe73a6 100644
--- a/tinygrad/uop/ops.py
+++ b/tinygrad/uop/ops.py
@@ -303,10 +303,6 @@ class UOp(RandMixin, metaclass=UOpMetaClass):
       case Ops.MSTACK | Ops.MSELECT | Ops.DETACH | Ops.CONTIGUOUS | Ops.CONTIGUOUS_BACKWARD | Ops.AFTER | Ops.LOAD | \
            Ops.COPY | Ops.ALLREDUCE | Ops.STORE | Ops.END:
         return self.src[0]._shape
-      # REDUCE with empty axis is passthrough (lowered form)
-      case Ops.REDUCE if len(self.arg[1]) == 0:
-        # these can mismatch if there's a horizonal reduce
-        return (self.dtype.count,) if self.dtype.count > 1 else ()
 
       # TODO: disallow shape changing bitcast
       case Ops.BITCAST: