.

Author: Quafadas

vecxt/src-jvm/arrays.scala

@@ -337,6 +337,40 @@ object arrays:
       end while
     end +=
 
+    inline def minSIMD =
+      var i = 0
+      var acc = IntVector.broadcast(spi, Int.MaxValue)
+
+      while i < spi.loopBound(vec.length) do
+        acc = acc.min(IntVector.fromArray(spi, vec, i))
+        i += spil
+      end while
+
+      var temp = acc.reduceLanes(VectorOperators.MIN)
+
+      while i < vec.length do
+        temp = Math.min(temp, vec(i))
+        i += 1
+      end while
+      temp
+
+    inline def maxSIMD =
+      var i = 0
+      var acc = IntVector.broadcast(spi, Int.MinValue)
+
+      while i < spi.loopBound(vec.length) do
+        acc = acc.max(IntVector.fromArray(spi, vec, i))
+        i += spil
+      end while
+
+      var temp = acc.reduceLanes(VectorOperators.MAX)
+
+      while i < vec.length do
+        temp = Math.max(temp, vec(i))
+        i += 1
+      end while
+      temp
+
   end extension
 
   extension [@specialized(Double, Int) A](vec: Array[A])(using ClassTag[A])

vecxt/test/src-jvm/IntArrays.test.scala

@@ -0,0 +1,45 @@
+/*
+ * Copyright 2023 quafadas
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package vecxt
+
+import all.*
+import narr.*
+
+class MinMaxSIMDSuite extends munit.FunSuite:
+
+  test("maxSIMD finds maximum in small array"):
+    val arr = NArray[Double](1.0, 5.0, 3.0, 9.0, 2.0)
+    val result = arr.maxSIMD
+    assertEquals(result, 9.0)
+
+  test("maxSIMD finds maximum in large array with SIMD lanes"):
+    // Create array larger than SIMD vector length to test SIMD path
+    val arr = NArray.tabulate[Double](100)(i => (i * 2.5) % 37.0)
+    arr(75) = 1000.0 // Insert known maximum
+    val result = arr.maxSIMD
+    assertEquals(result, 1000.0)
+
+  test("minSIMD finds minimum in array with positive integers"):
+    val arr = Array(5, 3, 9, 1, 7, 2, 8, 4, 6)
+    val result = arr.minSIMD
+    assertEquals(result, 1)
+
+  test("minSIMD finds minimum in large array crossing SIMD boundaries"):
+    // Create array larger than SIMD vector length to test both SIMD and scalar paths
+    val arr = Array.tabulate(100)(i => if i == 73 then -5 else i * 2 + 10)
+    val result = arr.minSIMD
+    assertEquals(result, -5)