Benchmark on latest Julia and scale back large-matrix benchmarking

.github/workflows/benchmark.yml

@@ -10,7 +10,7 @@ jobs:
       - uses: actions/checkout@v2
       - uses: julia-actions/setup-julia@latest
         with:
-          version: 1.6
+          version: 1
       - name: Install dependencies
         run: julia -e 'using Pkg; pkg"add PkgBenchmark [email protected]"'
       - name: Run benchmarks

benchmark/bench_mat_mul.jl

@@ -26,7 +26,7 @@ mul_wrappers_reduced = [
     (m -> Transpose(m), "transpo"),
     (m -> Diagonal(m), "diag   ")]
 
-for N in [2, 4, 8, 10, 16]
+for N in [2, 4, 8, 10, 12]
 
     matvecstr = @sprintf("mat-vec  %2d", N)
     matmatstr = @sprintf("mat-mat  %2d", N)
@@ -205,7 +205,7 @@ function pick_best(results, mul_wrappers, size_iter; tol = 1.2)
 end
 
 function run_1()
-    return full_benchmark(mul_wrappers_reduced, [2, 3, 4, 5, 8, 9, 14, 16])
+    return full_benchmark(mul_wrappers_reduced, [2, 3, 4, 5, 8, 9, 12])
 end
 
 end #module

benchmark/bench_qr.jl

@@ -6,7 +6,7 @@ using StaticArrays
 
 const suite = BenchmarkGroup()
 
-for K = 1:22
+for K = [2, 3, 4, 8, 10, 12]
     a = rand(SMatrix{K,K,Float64,K*K})
     m = Matrix(a)
     s = suite["S=$K"] = BenchmarkGroup()