Rationalize and try to fix failing ldiv tests

[kshyatt]

Trying to fix intermittently failing CI. Doesn't make sense to have these checks for only one of the inplace/not-inplace versions. Hopefully this helps stability.

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diff --git a/test/libraries/cusparse/interfaces.jl b/test/libraries/cusparse/interfaces.jl
index fa25d8330..34f9d75f8 100644
--- a/test/libraries/cusparse/interfaces.jl
+++ b/test/libraries/cusparse/interfaces.jl
@@ -258,7 +258,7 @@ nB = 2
                                 end
                             end
                             @testset "\\ -- CuMatrix" begin
-                                C  = triangle(opa(A)) \ opb(B)
+                                C = triangle(opa(A)) \ opb(B)
                                 dC = triangle(opa(dA)) \ opb(dB)
                                 @test C ≈ collect(dC)
                                 if CUSPARSE.version() < v"12.0"

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CUDA.jl Benchmarks

Benchmark suite	Current: 5db6744	Previous: fb0a528	Ratio
latency/precompile	43353735535.5 ns	43329572726 ns	1.00
latency/ttfp	7064329610 ns	7031277701 ns	1.00
latency/import	3452525802 ns	3465549489 ns	1.00
integration/volumerhs	9609113.5 ns	9597721 ns	1.00
integration/byval/slices=1	146862 ns	147057 ns	1.00
integration/byval/slices=3	425687 ns	426256 ns	1.00
integration/byval/reference	144957 ns	145230 ns	1.00
integration/byval/slices=2	286192.5 ns	286757 ns	1.00
integration/cudadevrt	103494 ns	103670 ns	1.00
kernel/indexing	14279 ns	14524 ns	0.98
kernel/indexing_checked	14912 ns	15000.5 ns	0.99
kernel/occupancy	754.2209302325581 ns	741.6906474820144 ns	1.02
kernel/launch	2269.8888888888887 ns	2251.3333333333335 ns	1.01
kernel/rand	18036 ns	14919 ns	1.21
array/reverse/1d	19937 ns	19819 ns	1.01
array/reverse/2d	24174 ns	25017 ns	0.97
array/reverse/1d_inplace	10330 ns	10579 ns	0.98
array/reverse/2d_inplace	11826 ns	12305 ns	0.96
array/copy	21210 ns	21174 ns	1.00
array/iteration/findall/int	159709.5 ns	158557 ns	1.01
array/iteration/findall/bool	140129 ns	139738 ns	1.00
array/iteration/findfirst/int	162678 ns	157479 ns	1.03
array/iteration/findfirst/bool	163518.5 ns	158520.5 ns	1.03
array/iteration/scalar	73054 ns	73433 ns	0.99
array/iteration/logical	215506.5 ns	217515.5 ns	0.99
array/iteration/findmin/1d	45938 ns	46904 ns	0.98
array/iteration/findmin/2d	95981 ns	96886 ns	0.99
array/reductions/reduce/Int64/1d	42305 ns	43179 ns	0.98
array/reductions/reduce/Int64/dims=1	55110.5 ns	47755.5 ns	1.15
array/reductions/reduce/Int64/dims=2	61831 ns	62189 ns	0.99
array/reductions/reduce/Int64/dims=1L	89151 ns	89100 ns	1.00
array/reductions/reduce/Int64/dims=2L	86599.5 ns	87187.5 ns	0.99
array/reductions/reduce/Float32/1d	34392 ns	35302 ns	0.97
array/reductions/reduce/Float32/dims=1	51824 ns	41632 ns	1.24
array/reductions/reduce/Float32/dims=2	59683 ns	59745 ns	1.00
array/reductions/reduce/Float32/dims=1L	53027 ns	53265 ns	1.00
array/reductions/reduce/Float32/dims=2L	69910.5 ns	70365 ns	0.99
array/reductions/mapreduce/Int64/1d	41808 ns	42192.5 ns	0.99
array/reductions/mapreduce/Int64/dims=1	45499.5 ns	55413.5 ns	0.82
array/reductions/mapreduce/Int64/dims=2	61577 ns	62472 ns	0.99
array/reductions/mapreduce/Int64/dims=1L	89162 ns	89096 ns	1.00
array/reductions/mapreduce/Int64/dims=2L	86429 ns	87031 ns	0.99
array/reductions/mapreduce/Float32/1d	34423 ns	34963.5 ns	0.98
array/reductions/mapreduce/Float32/dims=1	41823 ns	42410 ns	0.99
array/reductions/mapreduce/Float32/dims=2	60232 ns	60141 ns	1.00
array/reductions/mapreduce/Float32/dims=1L	53392 ns	53371 ns	1.00
array/reductions/mapreduce/Float32/dims=2L	70498 ns	70585 ns	1.00
array/broadcast	20874 ns	21207 ns	0.98
array/copyto!/gpu_to_gpu	11337 ns	11289 ns	1.00
array/copyto!/cpu_to_gpu	215316 ns	217320 ns	0.99
array/copyto!/gpu_to_cpu	284614 ns	283093 ns	1.01
array/accumulate/Int64/1d	125256 ns	125220 ns	1.00
array/accumulate/Int64/dims=1	83748 ns	83742 ns	1.00
array/accumulate/Int64/dims=2	157761 ns	158355 ns	1.00
array/accumulate/Int64/dims=1L	1709202.5 ns	1709296 ns	1.00
array/accumulate/Int64/dims=2L	966206 ns	966418.5 ns	1.00
array/accumulate/Float32/1d	109184 ns	109589 ns	1.00
array/accumulate/Float32/dims=1	80881.5 ns	80692 ns	1.00
array/accumulate/Float32/dims=2	147791 ns	148042 ns	1.00
array/accumulate/Float32/dims=1L	1618440 ns	1618330 ns	1.00
array/accumulate/Float32/dims=2L	698196 ns	698511 ns	1.00
array/construct	1283.9 ns	1255.2 ns	1.02
array/random/randn/Float32	47374 ns	43548 ns	1.09
array/random/randn!/Float32	24964 ns	25021 ns	1.00
array/random/rand!/Int64	27404 ns	27406 ns	1.00
array/random/rand!/Float32	8755.666666666666 ns	8860.333333333334 ns	0.99
array/random/rand/Int64	29882 ns	38250 ns	0.78
array/random/rand/Float32	13077.5 ns	13162 ns	0.99
array/permutedims/4d	61086 ns	61907 ns	0.99
array/permutedims/2d	54866.5 ns	55440 ns	0.99
array/permutedims/3d	56006 ns	56158 ns	1.00
array/sorting/1d	2756544 ns	2757412.5 ns	1.00
array/sorting/by	3343162 ns	3361155 ns	0.99
array/sorting/2d	1084151 ns	1088259 ns	1.00
cuda/synchronization/stream/auto	1052.4 ns	1030.8 ns	1.02
cuda/synchronization/stream/nonblocking	7722.1 ns	8005.9 ns	0.96
cuda/synchronization/stream/blocking	828.0882352941177 ns	853.1914893617021 ns	0.97
cuda/synchronization/context/auto	1215.8 ns	1178.1 ns	1.03
cuda/synchronization/context/nonblocking	7555.7 ns	7403.6 ns	1.02
cuda/synchronization/context/blocking	913.1162790697674 ns	914.6428571428571 ns	1.00

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