Merge pull request #2291 from JuliaGPU/tb/julia_1.11

Towards supporting Julia 1.11

Author: maleadt

.buildkite/pipeline.yml

@@ -27,8 +27,12 @@ steps:
               - "1.8"
               - "1.9"
               - "1.10"
+              - "1.11"
               - "nightly"
           adjustments:
+            - with:
+                julia: "1.11"
+              soft_fail: true
             - with:
                 julia: "nightly"
               soft_fail: true

lib/cusolver/linalg.jl

@@ -34,7 +34,7 @@ function Base.:\(_A::CuMatOrAdj, _B::CuOrAdj)
     if n < m
         # LQ decomposition
         At = CuMatrix(A')
-        F, tau = CUSOLVER.geqrf!(At)  # A = RᴴQᴴ
+        F, tau = geqrf!(At)  # A = RᴴQᴴ
         if B isa CuVector{T}
             CUBLAS.trsv!('U', 'C', 'N', view(F,1:n,1:n), B)
             X = CUDA.zeros(T, m)
@@ -45,15 +45,15 @@ function Base.:\(_A::CuMatOrAdj, _B::CuOrAdj)
             X = CUDA.zeros(T, m, p)
             view(X, 1:n, :) .= B
         end
-        CUSOLVER.ormqr!('L', 'N', F, tau, X)
+        ormqr!('L', 'N', F, tau, X)
     elseif n == m
         # LU decomposition with partial pivoting
-        F, p, info = CUSOLVER.getrf!(A)  # PA = LU
-        X = CUSOLVER.getrs!('N', F, p, B)
+        F, p, info = getrf!(A)  # PA = LU
+        X = getrs!('N', F, p, B)
     else
         # QR decomposition
-        F, tau = CUSOLVER.geqrf!(A)  # A = QR
-        CUSOLVER.ormqr!('L', 'C', F, tau, B)
+        F, tau = geqrf!(A)  # A = QR
+        ormqr!('L', 'C', F, tau, B)
         if B isa CuVector{T}
             X = B[1:m]
             CUBLAS.trsv!('U', 'N', 'N', view(F,1:m,1:m), X)
@@ -307,9 +307,22 @@ end
 
 ## LU
 
-function LinearAlgebra.lu!(A::StridedCuMatrix{T}, ::RowMaximum; check::Bool = true) where {T}
+function _check_lu_success(info, allowsingular)
+    if VERSION >= v"1.11.0-DEV.1535"
+        if info < 0 # zero pivot error from unpivoted LU
+            LinearAlgebra.checknozeropivot(-info)
+        else
+            allowsingular || LinearAlgebra.checknonsingular(info)
+        end
+    else
+        LinearAlgebra.checknonsingular(info)
+    end
+end
+
+function LinearAlgebra.lu!(A::StridedCuMatrix{T}, ::RowMaximum;
+                           check::Bool=true, allowsingular::Bool=false) where {T}
     lpt = getrf!(A)
-    check && LinearAlgebra.checknonsingular(lpt[3])
+    check && _check_lu_success(lpt[3], allowsingular)
     return LU(lpt[1], lpt[2], Int(lpt[3]))
 end
 

test/base/sorting.jl

@@ -1,10 +1,8 @@
 using Random
 using DataStructures
 
-@testset "quicksort" begin
-
-import CUDA.QuickSortImpl: flex_lt, find_partition, quicksort!,
-        partition_batches_kernel, consolidate_batch_partition, bubble_sort
+import CUDA.QuickSortImpl: flex_lt, find_partition, quicksort!, partition_batches_kernel,
+                           consolidate_batch_partition, bubble_sort
 
 @testset "integer functions" begin
     @test flex_lt(1, 2, false, isless, identity) == true
@@ -279,9 +277,6 @@ end
     end
 end
 
-# XXX: some tests here make compute-sanitizer hang, but only on CI.
-#      maybe related to the container set-up? try again once we use Sandbox.jl.
-
 @testset "interface" begin
     @testset "quicksort" begin
         # pre-sorted
@@ -389,7 +384,7 @@ end
     @test check_sortperm(Float64, 1000000; rev=true)
     @test check_sortperm(Float64, 1000000; by=x->abs(x-0.5))
     @test check_sortperm(Float64, 1000000; rev=true, by=x->abs(x-0.5))
-    
+
     if VERSION >= v"1.9"
         # Base.jl didn't implement sortperm(;dims) until 1.9
         @test check_sortperm(Float32, (100_000, 16); dims=1)
@@ -406,5 +401,3 @@ end
     # mismatched types (JuliaGPU/CUDA.jl#2046)
     @test check_sortperm!(collect(UInt64(1):UInt64(1000000)), Int64, 1000000)
 end
-
-end

test/libraries/cusolver/dense_generic.jl

@@ -128,20 +128,20 @@ p = 5
         A = rand(elty,m,n)
         d_A = CuMatrix(A)
         U, Σ, V, err_sigma = CUSOLVER.Xgesvdp!('V', 0, d_A)
-        @test A ≈ collect(U[:,1:n] * Diagonal(Σ) * V')
+        @test A ≈ collect(U[:,1:n]) * Diagonal(collect(Σ)) * collect(V)'
 
         d_A = CuMatrix(A)
         U, Σ, V, err_sigma = CUSOLVER.Xgesvdp!('V', 1, d_A)
-        @test A ≈ collect(U * Diagonal(Σ) * V')
+        @test A ≈ collect(U) * Diagonal(collect(Σ)) * collect(V)'
 
         A = rand(elty,n,m)
         d_A = CuMatrix(A)
         U, Σ, V, err_sigma = CUSOLVER.Xgesvdp!('V', 0, d_A)
-        @test A ≈ collect(U * Diagonal(Σ) * V[:,1:n]')
+        @test A ≈ collect(U) * Diagonal(collect(Σ)) * collect(V[:,1:n])'
 
         d_A = CuMatrix(A)
         U, Σ, V, err_sigma = CUSOLVER.Xgesvdp!('V', 1, d_A)
-        @test A ≈ collect(U * Diagonal(Σ) * V')
+        @test A ≈ collect(U) * Diagonal(collect(Σ)) * collect(V)'
     end
 
     # @testset "gesvdr!" begin

test/setup.jl

@@ -93,8 +93,15 @@ function runtests(f, name, time_source=:cuda)
         else
             missing
         end
-        passes,fails,error,broken,c_passes,c_fails,c_errors,c_broken =
-            Test.get_test_counts(data[1])
+        if VERSION >= v"1.11.0-DEV.1529"
+            tc = Test.get_test_counts(data[1])
+            passes,fails,error,broken,c_passes,c_fails,c_errors,c_broken =
+                tc.passes, tc.fails, tc.errors, tc.broken, tc.cumulative_passes,
+                tc.cumulative_fails, tc.cumulative_errors, tc.cumulative_broken
+        else
+            passes,fails,errors,broken,c_passes,c_fails,c_errors,c_broken =
+                Test.get_test_counts(data[1])
+        end
         if data[1].anynonpass == false
             data = ((passes+c_passes,broken+c_broken),
                     data[2],