examples/build.gradle.kts

@@ -20,6 +20,20 @@ dependencies {
     implementation(project(":kmath-viktor"))
     implementation(project(":kmath-dimensions"))
     implementation(project(":kmath-ejml"))
+    implementation(project(":kmath-nd4j"))
+    implementation("org.deeplearning4j:deeplearning4j-core:1.0.0-beta7")
+    implementation("org.nd4j:nd4j-native:1.0.0-beta7")
+
+//    uncomment if your system supports AVX2
+//    val os = System.getProperty("os.name")
+//
+//    if (System.getProperty("os.arch") in arrayOf("x86_64", "amd64")) when {
+//        os.startsWith("Windows") -> implementation("org.nd4j:nd4j-native:1.0.0-beta7:windows-x86_64-avx2")
+//        os == "Linux" -> implementation("org.nd4j:nd4j-native:1.0.0-beta7:linux-x86_64-avx2")
+//        os == "Mac OS X" -> implementation("org.nd4j:nd4j-native:1.0.0-beta7:macosx-x86_64-avx2")
+//    } else
+    implementation("org.nd4j:nd4j-native-platform:1.0.0-beta7")
+
     implementation("org.jetbrains.kotlinx:kotlinx-io:0.2.0-npm-dev-11")
     implementation("org.jetbrains.kotlinx:kotlinx.benchmark.runtime:0.2.0-dev-20")
     implementation("org.slf4j:slf4j-simple:1.7.30")
@@ -48,4 +62,6 @@ kotlin.sourceSets.all {
     }
 }
 
-tasks.withType<KotlinCompile> { kotlinOptions.jvmTarget = "11" }
+tasks.withType<KotlinCompile> {
+    kotlinOptions.jvmTarget = "11"
+}

examples/src/main/kotlin/kscience/kmath/structures/NDField.kt

@@ -1,8 +1,10 @@
 package kscience.kmath.structures
 
 import kotlinx.coroutines.GlobalScope
+import kscience.kmath.nd4j.Nd4jArrayField
 import kscience.kmath.operations.RealField
 import kscience.kmath.operations.invoke
+import org.nd4j.linalg.factory.Nd4j
 import kotlin.contracts.InvocationKind
 import kotlin.contracts.contract
 import kotlin.system.measureTimeMillis
@@ -14,6 +16,8 @@ internal inline fun measureAndPrint(title: String, block: () -> Unit) {
 }
 
 fun main() {
+    // initializing Nd4j
+    Nd4j.zeros(0)
     val dim = 1000
     val n = 1000
 
@@ -23,6 +27,8 @@ fun main() {
     val specializedField = NDField.real(dim, dim)
     //A generic boxing field. It should be used for objects, not primitives.
     val genericField = NDField.boxing(RealField, dim, dim)
+    // Nd4j specialized field.
+    val nd4jField = Nd4jArrayField.real(dim, dim)
 
     measureAndPrint("Automatic field addition") {
         autoField {
@@ -43,6 +49,13 @@ fun main() {
         }
     }
 
+    measureAndPrint("Nd4j specialized addition") {
+        nd4jField {
+            var res = one
+            repeat(n) { res += 1.0 as Number }
+        }
+    }
+
     measureAndPrint("Lazy addition") {
         val res = specializedField.one.mapAsync(GlobalScope) {
             var c = 0.0

kmath-nd4j/src/main/kotlin/kscience.kmath.nd4j/Nd4jArrayAlgebra.kt

@@ -126,6 +126,36 @@ public interface Nd4jArrayRing<T, R> : NDRing<T, R, Nd4jArrayStructure<T>>, Nd4j
         check(b)
         return b.ndArray.rsub(this).wrap()
     }
+
+    public companion object {
+        private val intNd4jArrayRingCache: ThreadLocal<MutableMap<IntArray, IntNd4jArrayRing>> =
+            ThreadLocal.withInitial { hashMapOf() }
+
+        private val longNd4jArrayRingCache: ThreadLocal<MutableMap<IntArray, LongNd4jArrayRing>> =
+            ThreadLocal.withInitial { hashMapOf() }
+
+        /**
+         * Creates an [NDRing] for [Int] values or pull it from cache if it was created previously.
+         */
+        public fun int(vararg shape: Int): Nd4jArrayRing<Int, IntRing> =
+            intNd4jArrayRingCache.get().getOrPut(shape) { IntNd4jArrayRing(shape) }
+
+        /**
+         * Creates an [NDRing] for [Long] values or pull it from cache if it was created previously.
+         */
+        public fun long(vararg shape: Int): Nd4jArrayRing<Long, LongRing> =
+            longNd4jArrayRingCache.get().getOrPut(shape) { LongNd4jArrayRing(shape) }
+
+        /**
+         * Creates a most suitable implementation of [NDRing] using reified class.
+         */
+        @Suppress("UNCHECKED_CAST")
+        public inline fun <reified T : Any> auto(vararg shape: Int): Nd4jArrayRing<T, out Ring<T>> = when {
+            T::class == Int::class -> int(*shape) as Nd4jArrayRing<T, out Ring<T>>
+            T::class == Long::class -> long(*shape) as Nd4jArrayRing<T, out Ring<T>>
+            else -> throw UnsupportedOperationException("This factory method only supports Int and Long types.")
+        }
+    }
 }
 
 /**
@@ -145,6 +175,37 @@ public interface Nd4jArrayField<T, F> : NDField<T, F, Nd4jArrayStructure<T>>, Nd
         check(b)
         return b.ndArray.rdiv(this).wrap()
     }
+
+
+    public companion object {
+        private val floatNd4jArrayFieldCache: ThreadLocal<MutableMap<IntArray, FloatNd4jArrayField>> =
+            ThreadLocal.withInitial { hashMapOf() }
+
+        private val realNd4jArrayFieldCache: ThreadLocal<MutableMap<IntArray, RealNd4jArrayField>> =
+            ThreadLocal.withInitial { hashMapOf() }
+
+        /**
+         * Creates an [NDField] for [Float] values or pull it from cache if it was created previously.
+         */
+        public fun float(vararg shape: Int): Nd4jArrayRing<Float, FloatField> =
+            floatNd4jArrayFieldCache.get().getOrPut(shape) { FloatNd4jArrayField(shape) }
+
+        /**
+         * Creates an [NDField] for [Double] values or pull it from cache if it was created previously.
+         */
+        public fun real(vararg shape: Int): Nd4jArrayRing<Double, RealField> =
+            realNd4jArrayFieldCache.get().getOrPut(shape) { RealNd4jArrayField(shape) }
+
+        /**
+         * Creates a most suitable implementation of [NDRing] using reified class.
+         */
+        @Suppress("UNCHECKED_CAST")
+        public inline fun <reified T : Any> auto(vararg shape: Int): Nd4jArrayField<T, out Field<T>> = when {
+            T::class == Float::class -> float(*shape) as Nd4jArrayField<T, out Field<T>>
+            T::class == Double::class -> real(*shape) as Nd4jArrayField<T, out Field<T>>
+            else -> throw UnsupportedOperationException("This factory method only supports Float and Double types.")
+        }
+    }
 }
 
 /**