[PATCH] D106963: [RISCV] Optimize floating-point "dominant value" BUILD_VECTORs
Fraser Cormack via Phabricator via llvm-commits
llvm-commits at lists.llvm.org
Thu Jul 29 01:31:55 PDT 2021
This revision was automatically updated to reflect the committed changes.
Closed by commit rG02dd4b59bc0d: [RISCV] Optimize floating-point "dominant value" BUILD_VECTORs (authored by frasercrmck).
Repository:
rG LLVM Github Monorepo
CHANGES SINCE LAST ACTION
https://reviews.llvm.org/D106963/new/
https://reviews.llvm.org/D106963
Files:
llvm/lib/Target/RISCV/RISCVISelLowering.cpp
llvm/test/CodeGen/RISCV/rvv/fixed-vectors-fp-buildvec.ll
Index: llvm/test/CodeGen/RISCV/rvv/fixed-vectors-fp-buildvec.ll
===================================================================
--- llvm/test/CodeGen/RISCV/rvv/fixed-vectors-fp-buildvec.ll
+++ llvm/test/CodeGen/RISCV/rvv/fixed-vectors-fp-buildvec.ll
@@ -101,8 +101,8 @@
ret void
}
-; FIXME: We "optimize" this one 2-element load from the constant pool to two
-; loads from the constant pool.
+; We don't want to lower this to the insertion of two scalar elements as above,
+; as each would require their own load from the constant pool.
define void @buildvec_dominant1_v2f32(<2 x float>* %x) {
; CHECK-LABEL: buildvec_dominant1_v2f32:
@@ -110,12 +110,7 @@
; CHECK-NEXT: lui a1, %hi(.LCPI3_0)
; CHECK-NEXT: addi a1, a1, %lo(.LCPI3_0)
; CHECK-NEXT: vsetivli zero, 2, e32, mf2, ta, mu
-; CHECK-NEXT: vlse32.v v25, (a1), zero
-; CHECK-NEXT: lui a1, %hi(.LCPI3_1)
-; CHECK-NEXT: flw ft0, %lo(.LCPI3_1)(a1)
-; CHECK-NEXT: vsetvli zero, zero, e32, mf2, tu, mu
-; CHECK-NEXT: vfmv.s.f v25, ft0
-; CHECK-NEXT: vsetvli zero, zero, e32, mf2, ta, mu
+; CHECK-NEXT: vle32.v v25, (a1)
; CHECK-NEXT: vse32.v v25, (a0)
; CHECK-NEXT: ret
store <2 x float> <float 1.0, float 2.0>, <2 x float>* %x
Index: llvm/lib/Target/RISCV/RISCVISelLowering.cpp
===================================================================
--- llvm/lib/Target/RISCV/RISCVISelLowering.cpp
+++ llvm/lib/Target/RISCV/RISCVISelLowering.cpp
@@ -1704,6 +1704,13 @@
unsigned NumUndefElts =
count_if(Op->op_values(), [](const SDValue &V) { return V.isUndef(); });
+ // Track the number of scalar loads we know we'd be inserting, estimated as
+ // any non-zero floating-point constant. Other kinds of element are either
+ // already in registers or are materialized on demand. The threshold at which
+ // a vector load is more desirable than several scalar materializion and
+ // vector-insertion instructions is not known.
+ unsigned NumScalarLoads = 0;
+
for (SDValue V : Op->op_values()) {
if (V.isUndef())
continue;
@@ -1711,6 +1718,9 @@
ValueCounts.insert(std::make_pair(V, 0));
unsigned &Count = ValueCounts[V];
+ if (auto *CFP = dyn_cast<ConstantFPSDNode>(V))
+ NumScalarLoads += !CFP->isExactlyValue(+0.0);
+
// Is this value dominant? In case of a tie, prefer the highest element as
// it's cheaper to insert near the beginning of a vector than it is at the
// end.
@@ -1726,7 +1736,7 @@
// Don't perform this optimization when optimizing for size, since
// materializing elements and inserting them tends to cause code bloat.
- if (!DAG.shouldOptForSize() &&
+ if (!DAG.shouldOptForSize() && NumScalarLoads < NumElts &&
((MostCommonCount > DominantValueCountThreshold) ||
(ValueCounts.size() <= Log2_32(NumDefElts)))) {
// Start by splatting the most common element.
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