Remove Requires.jl

[JamesWrigley]

This should not be needed now that our minimum supported version is 1.10, which has package extension support.

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 89.32%. Comparing base (5d9474a) to head (6c36f39).

Additional details and impacted files

@@            Coverage Diff             @@
##           master    #2999      +/-   ##
==========================================
+ Coverage   89.28%   89.32%   +0.04%     
==========================================
  Files         148      148              
  Lines       12998    12991       -7     
==========================================
- Hits        11605    11604       -1     
+ Misses       1393     1387       -6     

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[github-actions]

CUDA.jl Benchmarks

Details

Benchmark suite	Current: 6c36f39	Previous: 5d9474a	Ratio
latency/precompile	55278827065.5 ns	55510377029.5 ns	1.00
latency/ttfp	7798851585 ns	7790703567 ns	1.00
latency/import	4128376681 ns	4122189304 ns	1.00
integration/volumerhs	9624158.5 ns	9624973 ns	1.00
integration/byval/slices=1	146710 ns	147064 ns	1.00
integration/byval/slices=3	425584 ns	425893 ns	1.00
integration/byval/reference	145103 ns	145082 ns	1.00
integration/byval/slices=2	286085 ns	286384 ns	1.00
integration/cudadevrt	103651.5 ns	103602 ns	1.00
kernel/indexing	14190 ns	14225 ns	1.00
kernel/indexing_checked	14707 ns	14969 ns	0.98
kernel/occupancy	682.4516129032259 ns	732.5227272727273 ns	0.93
kernel/launch	2216 ns	2249.4444444444443 ns	0.99
kernel/rand	14906 ns	18642 ns	0.80
array/reverse/1d	20027 ns	19990 ns	1.00
array/reverse/2dL_inplace	66762 ns	66917 ns	1.00
array/reverse/1dL	70250 ns	70158 ns	1.00
array/reverse/2d	21886 ns	21954 ns	1.00
array/reverse/1d_inplace	11486 ns	9677 ns	1.19
array/reverse/2d_inplace	13178 ns	11077 ns	1.19
array/reverse/2dL	73904 ns	74051.5 ns	1.00
array/reverse/1dL_inplace	66815.5 ns	66880 ns	1.00
array/copy	20590 ns	20660 ns	1.00
array/iteration/findall/int	157138 ns	158373 ns	0.99
array/iteration/findall/bool	139428 ns	140139 ns	0.99
array/iteration/findfirst/int	160632 ns	161271 ns	1.00
array/iteration/findfirst/bool	161578 ns	162049 ns	1.00
array/iteration/scalar	72738 ns	72812.5 ns	1.00
array/iteration/logical	214887.5 ns	216894.5 ns	0.99
array/iteration/findmin/1d	50041 ns	50981 ns	0.98
array/iteration/findmin/2d	96124 ns	96704 ns	0.99
array/reductions/reduce/Int64/1d	42581 ns	43491 ns	0.98
array/reductions/reduce/Int64/dims=1	45834 ns	52642.5 ns	0.87
array/reductions/reduce/Int64/dims=2	61252 ns	61484 ns	1.00
array/reductions/reduce/Int64/dims=1L	89156 ns	88879 ns	1.00
array/reductions/reduce/Int64/dims=2L	87724 ns	87977 ns	1.00
array/reductions/reduce/Float32/1d	37224 ns	37248.5 ns	1.00
array/reductions/reduce/Float32/dims=1	42289.5 ns	43278 ns	0.98
array/reductions/reduce/Float32/dims=2	59625 ns	60066 ns	0.99
array/reductions/reduce/Float32/dims=1L	52160 ns	52282 ns	1.00
array/reductions/reduce/Float32/dims=2L	71795 ns	72365.5 ns	0.99
array/reductions/mapreduce/Int64/1d	43033 ns	43561 ns	0.99
array/reductions/mapreduce/Int64/dims=1	55050.5 ns	44306 ns	1.24
array/reductions/mapreduce/Int64/dims=2	61218 ns	61482 ns	1.00
array/reductions/mapreduce/Int64/dims=1L	89037 ns	89001 ns	1.00
array/reductions/mapreduce/Int64/dims=2L	87689 ns	88320 ns	0.99
array/reductions/mapreduce/Float32/1d	35850 ns	38092.5 ns	0.94
array/reductions/mapreduce/Float32/dims=1	41689 ns	41962 ns	0.99
array/reductions/mapreduce/Float32/dims=2	59833 ns	60039 ns	1.00
array/reductions/mapreduce/Float32/dims=1L	52416 ns	52636 ns	1.00
array/reductions/mapreduce/Float32/dims=2L	71713 ns	72310 ns	0.99
array/broadcast	19901 ns	20127 ns	0.99
array/copyto!/gpu_to_gpu	11252 ns	12738 ns	0.88
array/copyto!/cpu_to_gpu	214740.5 ns	217857 ns	0.99
array/copyto!/gpu_to_cpu	283991 ns	287088 ns	0.99
array/accumulate/Int64/1d	124582 ns	124778 ns	1.00
array/accumulate/Int64/dims=1	83227 ns	83708 ns	0.99
array/accumulate/Int64/dims=2	157898 ns	158367 ns	1.00
array/accumulate/Int64/dims=1L	1718938 ns	1710164 ns	1.01
array/accumulate/Int64/dims=2L	967614 ns	967254 ns	1.00
array/accumulate/Float32/1d	108632 ns	109314 ns	0.99
array/accumulate/Float32/dims=1	80081 ns	80184 ns	1.00
array/accumulate/Float32/dims=2	147532 ns	147922 ns	1.00
array/accumulate/Float32/dims=1L	1618110 ns	1618786 ns	1.00
array/accumulate/Float32/dims=2L	697985.5 ns	698724 ns	1.00
array/construct	1266.1 ns	1295.5 ns	0.98
array/random/randn/Float32	42390.5 ns	47861 ns	0.89
array/random/randn!/Float32	24743 ns	24875 ns	0.99
array/random/rand!/Int64	27438 ns	27408 ns	1.00
array/random/rand!/Float32	8776 ns	8909.666666666666 ns	0.98
array/random/rand/Int64	30105 ns	30055 ns	1.00
array/random/rand/Float32	12908 ns	13184 ns	0.98
array/permutedims/4d	55005 ns	55109 ns	1.00
array/permutedims/2d	53875.5 ns	53832 ns	1.00
array/permutedims/3d	54580 ns	54841 ns	1.00
array/sorting/1d	2756828 ns	2757534 ns	1.00
array/sorting/by	3343866 ns	3344541 ns	1.00
array/sorting/2d	1080648.5 ns	1081521 ns	1.00
cuda/synchronization/stream/auto	1040.3 ns	1036.5 ns	1.00
cuda/synchronization/stream/nonblocking	8128.9 ns	7410.8 ns	1.10
cuda/synchronization/stream/blocking	804.0105263157894 ns	820.6336633663366 ns	0.98
cuda/synchronization/context/auto	1178.4 ns	1154.3 ns	1.02
cuda/synchronization/context/nonblocking	7135.5 ns	7124.4 ns	1.00
cuda/synchronization/context/blocking	904.3235294117648 ns	887.4107142857143 ns	1.02

This comment was automatically generated by workflow using github-action-benchmark.