diff --git a/test/kernelabstractions.jl b/test/kernelabstractions.jl
index a78dfa6a..72640048 100644
--- a/test/kernelabstractions.jl
+++ b/test/kernelabstractions.jl
@@ -34,17 +34,8 @@ end
 
 @testset "launch configuration" begin
     backend = oneAPIBackend()
-    function select(kernel, ndrange, workgroupsize=nothing)
-        ndrange, workgroupsize, iterspace, _ = KA.launch_config(kernel, ndrange, workgroupsize)
-        KA.select_launch(kernel, workgroupsize, iterspace)
-    end
-
-    # kernels are launched on an N-d grid, computing indices in 32 bits
+    # a dynamic N-d range is indexed without divisions
     kernel = store_global_linear!(backend)
-    @test select(kernel, (64, 32, 16)) === KA.NDLaunch{Int32}()
-    @test select(kernel, (4, 4, 4, 4)) === KA.LinearLaunch{Int32}()
-
-    # which doesn't need divisions to compute the index of a dynamic N-d range
     A = oneAPI.zeros(Int, 64, 32, 16)
     ir = sprint(io -> oneAPI.@device_code_llvm io=io kernel(A; ndrange=size(A)))
     @test !occursin(r"\b[us](div|rem) ", ir)
@@ -53,12 +44,10 @@ end
     # tuning for more work-groups (the testsuite above uses the default)
     Testsuite.launch_testsuite(()->oneAPIBackend(; prefer_blocks=true), oneArray)
 
-    # iteration spaces that don't fit 32 bits use 64-bit indices
+    # iteration spaces that don't fit 32-bit indices
     kernel = store_last_index!(backend)
     A = oneAPI.zeros(Int, 2)
-    for (dims, launch) in (((2^16 + 1, 2^15), KA.NDLaunch{Int}()),
-                           ((2^11 + 1, 2^10, 2^10, 1), KA.LinearLaunch{Int}()))
-        @test select(kernel, dims) === launch
+    for dims in ((2^16 + 1, 2^15), (2^11 + 1, 2^10, 2^9, 2), (1, 1, 1, 2^31 + 1))
         kernel(A; ndrange=dims)
         @test Array(A) == [prod(dims), dims[2]]
     end