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LewisCrawfordLewisCrawford
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Add new mixed vector element tests
Add test-cases for the newly added elementwise optimizations covering vectors like <poison, Inf> and <poison, Inf, SNaN>.
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‎llvm/test/Transforms/InstSimplify/fminmax-folds.ll‎

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@@ -584,6 +584,80 @@ define void @minmax_neg_largest_nxv2f32_nnan_ninf(<vscale x 2 x float> %x, ptr %
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ret void
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}
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;###############################################################
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;# Mixed Constant Vector Elements #
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;###############################################################
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; Tests elementwise handling of different combinations of the above optimizable constants
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; Test with vector variants (v2f64) with +Inf and poison
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; Poison element allows for flexibility to choose either X or <poison, +Inf> where applicable
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define void @minmax_mixed_pos_inf_poison_v2f64_nnan(<2 x double> %x, ptr %minnum_res, ptr %maxnum_res, ptr %minimum_res, ptr %maximum_res, ptr %minimumnum_res, ptr %maximumnum_res) {
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; CHECK-LABEL: @minmax_mixed_pos_inf_poison_v2f64_nnan(
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; CHECK-NEXT: store <2 x double> [[X:%.*]], ptr [[MINNUM_RES:%.*]], align 16
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; CHECK-NEXT: store <2 x double> <double poison, double 0x7FF0000000000000>, ptr [[MAXNUM_RES:%.*]], align 16
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; CHECK-NEXT: store <2 x double> [[X]], ptr [[MINIMUM_RES:%.*]], align 16
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; CHECK-NEXT: store <2 x double> <double poison, double 0x7FF0000000000000>, ptr [[MAXIMUM_RES:%.*]], align 16
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; CHECK-NEXT: store <2 x double> [[X]], ptr [[MINIMUMNUM_RES:%.*]], align 16
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; CHECK-NEXT: store <2 x double> <double poison, double 0x7FF0000000000000>, ptr [[MAXIMUMNUM_RES:%.*]], align 16
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; CHECK-NEXT: ret void
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;
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%minnum = call nnan <2 x double> @llvm.minnum.v2f64(<2 x double> <double poison, double 0x7FF0000000000000>, <2 x double> %x)
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store <2 x double> %minnum, ptr %minnum_res
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%maxnum = call nnan <2 x double> @llvm.maxnum.v2f64(<2 x double> <double poison, double 0x7FF0000000000000>, <2 x double> %x)
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store <2 x double> %maxnum, ptr %maxnum_res
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%minimum = call nnan <2 x double> @llvm.minimum.v2f64(<2 x double> <double poison, double 0x7FF0000000000000>, <2 x double> %x)
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store <2 x double> %minimum, ptr %minimum_res
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%maximum = call nnan <2 x double> @llvm.maximum.v2f64(<2 x double> <double poison, double 0x7FF0000000000000>, <2 x double> %x)
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store <2 x double> %maximum, ptr %maximum_res
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%minimumnum = call nnan <2 x double> @llvm.minimumnum.v2f64(<2 x double> <double poison, double 0x7FF0000000000000>, <2 x double> %x)
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store <2 x double> %minimumnum, ptr %minimumnum_res
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%maximumnum = call nnan <2 x double> @llvm.maximumnum.v2f64(<2 x double> <double poison, double 0x7FF0000000000000>, <2 x double> %x)
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store <2 x double> %maximumnum, ptr %maximumnum_res
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ret void
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}
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; Tests to show that we can optimize different classes of constatn (inf/nan/poison) in different vector elements.
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; We can only optimize if the result would be choosing all elements of the input X, or all constant elements though
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; (where poison allows us to choose either).
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;
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; nnan minnum(<poison, +Inf, SNaN>, X) = <???, X1, QNaN> (Cannot mix elements from X and constant vector)
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; nnan maxnum(<poison, +Inf, SNaN>, X) = <poison +Inf, QNaN>
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; nnan minimum(<poison, +Inf, SNaN>, X) = <???, X1, QNaN> (Cannot mix elements from X and constant vector)
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; nnan maximum(<poison, +Inf, SNaN>, X) = <poison +Inf, QNaN>
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; nnan minimumnum(<poison, +Inf, SNaN>, X) = <X0, X1, X2> (Poison can be either X or constant value)
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; nnan maximumnum(<poison, +Inf, SNaN>, X) = <???, +Inf, X2>
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define void @minmax_mixed_pos_inf_poison_snan_v3f32(<3 x float> %x, ptr %minnum_res, ptr %maxnum_res, ptr %minimum_res, ptr %maximum_res, ptr %minimumnum_res, ptr %maximumnum_res) {
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; CHECK-LABEL: @minmax_mixed_pos_inf_poison_snan_v3f32(
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; CHECK-NEXT: [[MINNUM:%.*]] = call nnan <3 x float> @llvm.minnum.v3f32(<3 x float> <float poison, float 0x7FF0000000000000, float 0x7FF4000000000000>, <3 x float> [[X:%.*]])
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; CHECK-NEXT: store <3 x float> [[MINNUM]], ptr [[MINNUM_RES:%.*]], align 16
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; CHECK-NEXT: store <3 x float> <float poison, float 0x7FF0000000000000, float 0x7FFC000000000000>, ptr [[MAXNUM_RES:%.*]], align 16
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; CHECK-NEXT: [[MINIMUM:%.*]] = call nnan <3 x float> @llvm.minimum.v3f32(<3 x float> <float poison, float 0x7FF0000000000000, float 0x7FF4000000000000>, <3 x float> [[X]])
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; CHECK-NEXT: store <3 x float> [[MINIMUM]], ptr [[MINIMUM_RES:%.*]], align 16
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; CHECK-NEXT: store <3 x float> <float poison, float 0x7FF0000000000000, float 0x7FFC000000000000>, ptr [[MAXIMUM_RES:%.*]], align 16
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; CHECK-NEXT: store <3 x float> [[X]], ptr [[MINIMUMNUM_RES:%.*]], align 16
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; CHECK-NEXT: [[MAXIMUMNUM:%.*]] = call nnan <3 x float> @llvm.maximumnum.v3f32(<3 x float> <float poison, float 0x7FF0000000000000, float 0x7FF4000000000000>, <3 x float> [[X]])
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; CHECK-NEXT: store <3 x float> [[MAXIMUMNUM]], ptr [[MAXIMUMNUM_RES:%.*]], align 16
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; CHECK-NEXT: ret void
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;
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%minnum = call nnan <3 x float> @llvm.minnum.v3f32(<3 x float> <float poison, float 0x7FF0000000000000, float 0x7FF4000000000000>, <3 x float> %x)
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store <3 x float> %minnum, ptr %minnum_res
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%maxnum = call nnan <3 x float> @llvm.maxnum.v3f32(<3 x float> <float poison, float 0x7FF0000000000000, float 0x7FF4000000000000>, <3 x float> %x)
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store <3 x float> %maxnum, ptr %maxnum_res
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%minimum = call nnan <3 x float> @llvm.minimum.v3f32(<3 x float> <float poison, float 0x7FF0000000000000, float 0x7FF4000000000000>, <3 x float> %x)
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store <3 x float> %minimum, ptr %minimum_res
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%maximum = call nnan <3 x float> @llvm.maximum.v3f32(<3 x float> <float poison, float 0x7FF0000000000000, float 0x7FF4000000000000>, <3 x float> %x)
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store <3 x float> %maximum, ptr %maximum_res
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%minimumnum = call nnan <3 x float> @llvm.minimumnum.v3f32(<3 x float> <float poison, float 0x7FF0000000000000, float 0x7FF4000000000000>, <3 x float> %x)
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store <3 x float> %minimumnum, ptr %minimumnum_res
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%maximumnum = call nnan <3 x float> @llvm.maximumnum.v3f32(<3 x float> <float poison, float 0x7FF0000000000000, float 0x7FF4000000000000>, <3 x float> %x)
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store <3 x float> %maximumnum, ptr %maximumnum_res
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ret void
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}
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;###############################################################
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;# Min(x, x) / Max(x, x) #
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;###############################################################

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