Specialized BufferNDField

benchmarks/src/main/kotlin/scientifik/kmath/structures/StructureReadBenchmark.kt

@@ -0,0 +1,36 @@
+package scientifik.kmath.structures
+
+import kotlin.system.measureTimeMillis
+
+fun main(args: Array<String>) {
+    val n = 6000
+
+    val array = DoubleArray(n * n) { 1.0 }
+    val buffer = DoubleBuffer(array)
+    val strides = DefaultStrides(intArrayOf(n, n))
+
+    val structure = BufferNDStructure(strides, buffer)
+
+    measureTimeMillis {
+        var res: Double = 0.0
+        strides.indices().forEach { res = structure[it] }
+    } // warmup
+
+    val time1 = measureTimeMillis {
+        var res: Double = 0.0
+        strides.indices().forEach { res = structure[it] }
+    }
+    println("Structure reading finished in $time1 millis")
+
+    val time2 = measureTimeMillis {
+        var res: Double = 0.0
+        strides.indices().forEach { res = buffer[strides.offset(it)] }
+    }
+    println("Buffer reading finished in $time2 millis")
+
+    val time3 = measureTimeMillis {
+        var res: Double = 0.0
+        strides.indices().forEach { res = array[strides.offset(it)] }
+    }
+    println("Array reading finished in $time3 millis")
+}

benchmarks/src/main/kotlin/scientifik/kmath/structures/StructureWriteBenchmark.kt

@@ -0,0 +1,39 @@
+package scientifik.kmath.structures
+
+import kotlin.system.measureTimeMillis
+
+
+
+fun main(args: Array<String>) {
+
+    val n = 6000
+
+    val structure = NdStructure(intArrayOf(n, n), DoubleBufferFactory) { 1.0 }
+
+    structure.map { it + 1 } // warm-up
+
+    val time1 = measureTimeMillis {
+        val res = structure.map { it + 1 }
+    }
+    println("Structure mapping finished in $time1 millis")
+
+    val array = DoubleArray(n*n){1.0}
+
+    val time2 = measureTimeMillis {
+        val target = DoubleArray(n*n)
+        val res = array.forEachIndexed{index, value ->
+            target[index] = value + 1
+        }
+    }
+    println("Array mapping finished in $time2 millis")
+
+    val buffer = DoubleBuffer(DoubleArray(n*n){1.0})
+
+    val time3 = measureTimeMillis {
+        val target = DoubleBuffer(DoubleArray(n*n))
+        val res = array.forEachIndexed{index, value ->
+            target[index] = value + 1
+        }
+    }
+    println("Buffer mapping finished in $time3 millis")
+}

kmath-core/src/commonMain/kotlin/scientifik/kmath/misc/Grids.kt

@@ -32,6 +32,6 @@ fun ClosedFloatingPointRange<Double>.toSequence(step: Double): Sequence<Double>
  * Convert double range to array of evenly spaced doubles, where the size of array equals [numPoints]
  */
 fun ClosedFloatingPointRange<Double>.toGrid(numPoints: Int): DoubleArray {
-    if (numPoints < 2) error("Can't create grid with less than two points")
+    if (numPoints < 2) error("Can't generic grid with less than two points")
     return DoubleArray(numPoints) { i -> start + (endInclusive - start) / (numPoints - 1) * i }
 }

kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/BufferNDField.kt

@@ -0,0 +1,22 @@
+package scientifik.kmath.structures
+
+import scientifik.kmath.operations.Field
+
+class BufferNDField<T : Any, F : Field<T>>(override val shape: IntArray, override val field: F, val bufferFactory: BufferFactory<T>) : NDField<T, F> {
+    val strides = DefaultStrides(shape)
+
+    override inline fun produce(crossinline initializer: F.(IntArray) -> T): NDElement<T, F> {
+        return BufferNDElement(this, bufferFactory(strides.linearSize) { offset -> field.initializer(strides.index(offset)) })
+    }
+}
+
+class BufferNDElement<T : Any, F : Field<T>>(override val context: BufferNDField<T, F>, private val buffer: Buffer<T>) : NDElement<T, F> {
+
+    override val self: NDStructure<T> get() = this
+    override val shape: IntArray get() = context.shape
+
+    override fun get(index: IntArray): T = buffer[context.strides.offset(index)]
+
+    override fun elements(): Sequence<Pair<IntArray, T>> = context.strides.indices().map { it to get(it) }
+
+}

kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/ExtendedNDField.kt

@@ -9,14 +9,15 @@ import scientifik.kmath.operations.TrigonometricOperations
 /**
  * NDField that supports [ExtendedField] operations on its elements
  */
-class ExtendedNDField<T : Any, F : ExtendedField<T>>(shape: IntArray, field: F) : NDField<T, F>(shape, field),
+inline class ExtendedNDField<T : Any, F : ExtendedField<T>>(private val ndField: NDField<T, F>) : NDField<T, F>,
         TrigonometricOperations<NDStructure<T>>,
         PowerOperations<NDStructure<T>>,
         ExponentialOperations<NDStructure<T>> {
 
-    override fun produceStructure(initializer: F.(IntArray) -> T): NDStructure<T> {
+    override val shape: IntArray get() = ndField.shape
-        return NdStructure(shape, ::boxingBuffer) { field.initializer(it) }
+    override val field: F get() = ndField.field
-    }
+
+    override fun produce(initializer: F.(IntArray) -> T): NDElement<T, F> = ndField.produce(initializer)
 
     override fun power(arg: NDStructure<T>, pow: Double): NDElement<T, F> {
         return produce { with(field) { power(arg[it], pow) } }

kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/NDField.kt

@@ -15,28 +15,25 @@ class ShapeMismatchException(val expected: IntArray, val actual: IntArray) : Run
  * @param field - operations field defined on individual array element
  * @param T the type of the element contained in NDArray
  */
-abstract class NDField<T, F : Field<T>>(val shape: IntArray, val field: F) : Field<NDStructure<T>> {
+interface NDField<T, F : Field<T>> : Field<NDStructure<T>> {
 
-    abstract fun produceStructure(initializer: F.(IntArray) -> T): NDStructure<T>
+    val shape: IntArray
+    val field: F
 
     /**
      * Create new instance of NDArray using field shape and given initializer
      * The producer takes list of indices as argument and returns contained value
      */
-    fun produce(initializer: F.(IntArray) -> T): NDElement<T, F> = NDStructureElement(this, produceStructure(initializer))
+    fun produce(initializer: F.(IntArray) -> T): NDElement<T, F>
 
-    override val zero: NDElement<T, F> by lazy {
+    override val zero: NDElement<T, F> get() = produce { zero }
-        produce { zero }
-    }
 
-    override val one: NDElement<T, F> by lazy {
+    override val one: NDElement<T, F> get() = produce { one }
-        produce { one }
-    }
 
     /**
      * Check the shape of given NDArray and throw exception if it does not coincide with shape of the field
      */
-    private fun checkShape(vararg elements: NDStructure<T>) {
+    fun checkShape(vararg elements: NDStructure<T>) {
         elements.forEach {
             if (!shape.contentEquals(it.shape)) {
                 throw ShapeMismatchException(shape, it.shape)
@@ -49,7 +46,7 @@ abstract class NDField<T, F : Field<T>>(val shape: IntArray, val field: F) : Fie
      */
     override fun add(a: NDStructure<T>, b: NDStructure<T>): NDElement<T, F> {
         checkShape(a, b)
-        return produce { with(field) { a[it] + b[it] } }
+        return produce { field.run { a[it] + b[it] } }
     }
 
     /**
@@ -57,7 +54,7 @@ abstract class NDField<T, F : Field<T>>(val shape: IntArray, val field: F) : Fie
      */
     override fun multiply(a: NDStructure<T>, k: Double): NDElement<T, F> {
         checkShape(a)
-        return produce { with(field) { a[it] * k } }
+        return produce { field.run { a[it] * k } }
     }
 
     /**
@@ -65,7 +62,7 @@ abstract class NDField<T, F : Field<T>>(val shape: IntArray, val field: F) : Fie
      */
     override fun multiply(a: NDStructure<T>, b: NDStructure<T>): NDElement<T, F> {
         checkShape(a)
-        return produce { with(field) { a[it] * b[it] } }
+        return produce { field.run { a[it] * b[it] } }
     }
 
     /**
@@ -73,55 +70,72 @@ abstract class NDField<T, F : Field<T>>(val shape: IntArray, val field: F) : Fie
      */
     override fun divide(a: NDStructure<T>, b: NDStructure<T>): NDElement<T, F> {
         checkShape(a)
-        return produce { with(field) { a[it] / b[it] } }
+        return produce { field.run { a[it] / b[it] } }
     }
 
-//    /**
+
-//     * Reverse sum operation
+    companion object {
-//     */
+        /**
-//    operator fun T.plus(arg: NDElement<T, F>): NDElement<T, F> = arg + this
+         * Create a nd-field for [Double] values
-//
+         */
-//    /**
+        fun real(shape: IntArray) = ExtendedNDField(BufferNDField(shape, DoubleField, DoubleBufferFactory))
-//     * Reverse minus operation
+
-//     */
+        /**
-//    operator fun T.minus(arg: NDElement<T, F>): NDElement<T, F> = arg.transformIndexed { _, value ->
+         * Create a nd-field with boxing generic buffer
-//        with(arg.context.field) {
+         */
-//            this@minus - value
+        fun <T : Any, F : Field<T>> generic(shape: IntArray, field: F) = BufferNDField(shape, field, ::boxingBuffer)
-//        }
+
-//    }
+        /**
-//
+         * Create a most suitable implementation for nd-field using reified class
-//    /**
+         */
-//     * Reverse product operation
+        inline fun <reified T : Any, F : Field<T>> inline(shape: IntArray, field: F) = BufferNDField(shape, field, ::inlineBuffer)
-//     */
+    }
-//    operator fun T.times(arg: NDElement<T, F>): NDElement<T, F> = arg * this
-//
-//    /**
-//     * Reverse division operation
-//     */
-//    operator fun T.div(arg: NDElement<T, F>): NDElement<T, F> = arg.transformIndexed { _, value ->
-//        with(arg.context.field) {
-//            this@div / value
-//        }
-//    }
 }
 
 
-interface NDElement<T, F : Field<T>> : FieldElement<NDStructure<T>, NDField<T, F>>, NDStructure<T>
+interface NDElement<T, F : Field<T>> : FieldElement<NDStructure<T>, NDField<T, F>>, NDStructure<T> {
+    companion object {
+        /**
+         * Create a platform-optimized NDArray of doubles
+         */
+        fun real(shape: IntArray, initializer: DoubleField.(IntArray) -> Double = { 0.0 }): NDElement<Double, DoubleField> {
+            return NDField.real(shape).produce(initializer)
+        }
+
+        fun real1D(dim: Int, initializer: (Int) -> Double = { _ -> 0.0 }): NDElement<Double, DoubleField> {
+            return real(intArrayOf(dim)) { initializer(it[0]) }
+        }
+
+        fun real2D(dim1: Int, dim2: Int, initializer: (Int, Int) -> Double = { _, _ -> 0.0 }): NDElement<Double, DoubleField> {
+            return real(intArrayOf(dim1, dim2)) { initializer(it[0], it[1]) }
+        }
+
+        fun real3D(dim1: Int, dim2: Int, dim3: Int, initializer: (Int, Int, Int) -> Double = { _, _, _ -> 0.0 }): NDElement<Double, DoubleField> {
+            return real(intArrayOf(dim1, dim2, dim3)) { initializer(it[0], it[1], it[2]) }
+        }
+
+//        inline fun real(shape: IntArray, block: ExtendedNDField<Double, DoubleField>.() -> NDStructure<Double>): NDElement<Double, DoubleField> {
+//            val field = NDField.real(shape)
+//            return GenericNDElement(field, field.run(block))
+//        }
+
+        /**
+         * Simple boxing NDArray
+         */
+        fun <T : Any, F : Field<T>> generic(shape: IntArray, field: F, initializer: F.(IntArray) -> T): NDElement<T, F> {
+            return NDField.generic(shape,field).produce(initializer)
+        }
+
+        inline fun <reified T : Any, F : Field<T>> inline(shape: IntArray, field: F, crossinline initializer: F.(IntArray) -> T): NDElement<T, F> {
+            return NDField.inline(shape,field).produce(initializer)
+        }
+    }
+}
 
 inline fun <T, F : Field<T>> NDElement<T, F>.transformIndexed(crossinline action: F.(IntArray, T) -> T): NDElement<T, F> = context.produce { action(it, get(*it)) }
 inline fun <T, F : Field<T>> NDElement<T, F>.transform(crossinline action: F.(T) -> T): NDElement<T, F> = context.produce { action(get(*it)) }
 
 
-/**
- *  Read-only [NDStructure] coupled to the context.
- */
-class NDStructureElement<T, F : Field<T>>(override val context: NDField<T, F>, private val structure: NDStructure<T>) : NDElement<T, F>, NDStructure<T> by structure {
-
-    //TODO ensure structure is immutable
-
-    override val self: NDElement<T, F> get() = this
-}
-
 /**
  * Element by element application of any operation on elements to the whole array. Just like in numpy
  */
@@ -133,18 +147,14 @@ operator fun <T, F : Field<T>> Function1<T, T>.invoke(ndElement: NDElement<T, F>
  * Summation operation for [NDElement] and single element
  */
 operator fun <T, F : Field<T>> NDElement<T, F>.plus(arg: T): NDElement<T, F> = transform { value ->
-    with(context.field) {
+    context.field.run { arg + value }
-        arg + value
-    }
 }
 
 /**
  * Subtraction operation between [NDElement] and single element
  */
 operator fun <T, F : Field<T>> NDElement<T, F>.minus(arg: T): NDElement<T, F> = transform { value ->
-    with(context.field) {
+    context.field.run { arg - value }
-        arg - value
-    }
 }
 
 /* prod and div */
@@ -153,55 +163,53 @@ operator fun <T, F : Field<T>> NDElement<T, F>.minus(arg: T): NDElement<T, F> =
  * Product operation for [NDElement] and single element
  */
 operator fun <T, F : Field<T>> NDElement<T, F>.times(arg: T): NDElement<T, F> = transform { value ->
-    with(context.field) {
+    context.field.run { arg * value }
-        arg * value
-    }
 }
 
 /**
  * Division operation between [NDElement] and single element
  */
 operator fun <T, F : Field<T>> NDElement<T, F>.div(arg: T): NDElement<T, F> = transform { value ->
-    with(context.field) {
+    context.field.run { arg / value }
-        arg / value
-    }
 }
 
-class GenericNDField<T : Any, F : Field<T>>(shape: IntArray, field: F) : NDField<T, F>(shape, field) {
+
-    override fun produceStructure(initializer: F.(IntArray) -> T): NDStructure<T> = NdStructure(shape, ::boxingBuffer) { field.initializer(it) }
+//    /**
+//     * Reverse sum operation
+//     */
+//    operator fun T.plus(arg: NDStructure<T>): NDElement<T, F> = produce { index ->
+//        field.run { this@plus + arg[index] }
+//    }
+//
+//    /**
+//     * Reverse minus operation
+//     */
+//    operator fun T.minus(arg: NDStructure<T>): NDElement<T, F> = produce { index ->
+//        field.run { this@minus - arg[index] }
+//    }
+//
+//    /**
+//     * Reverse product operation
+//     */
+//    operator fun T.times(arg: NDStructure<T>): NDElement<T, F> = produce { index ->
+//        field.run { this@times * arg[index] }
+//    }
+//
+//    /**
+//     * Reverse division operation
+//     */
+//    operator fun T.div(arg: NDStructure<T>): NDElement<T, F> = produce { index ->
+//        field.run { this@div / arg[index] }
+//    }
+
+class GenericNDField<T : Any, F : Field<T>>(override val shape: IntArray, override val field: F) : NDField<T, F> {
+    override fun produce(initializer: F.(IntArray) -> T): NDElement<T, F> = GenericNDElement(this, produceStructure(initializer))
+    private inline fun produceStructure(crossinline initializer: F.(IntArray) -> T): NDStructure<T> = NdStructure(shape, ::boxingBuffer) { field.initializer(it) }
 }
 
-//typealias NDFieldFactory<T> = (IntArray)->NDField<T>
+/**
-
+ *  Read-only [NDStructure] coupled to the context.
-object NDElements {
+ */
-    /**
+class GenericNDElement<T, F : Field<T>>(override val context: NDField<T, F>, private val structure: NDStructure<T>) : NDElement<T, F>, NDStructure<T> by structure {
-     * Create a platform-optimized NDArray of doubles
+    override val self: NDElement<T, F> get() = this
-     */
-    fun realNDElement(shape: IntArray, initializer: DoubleField.(IntArray) -> Double = { 0.0 }): NDElement<Double, DoubleField> {
-        return ExtendedNDField(shape, DoubleField).produce(initializer)
-    }
-
-    fun real1DElement(dim: Int, initializer: (Int) -> Double = { _ -> 0.0 }): NDElement<Double, DoubleField> {
-        return realNDElement(intArrayOf(dim)) { initializer(it[0]) }
-    }
-
-    fun real2DElement(dim1: Int, dim2: Int, initializer: (Int, Int) -> Double = { _, _ -> 0.0 }): NDElement<Double, DoubleField> {
-        return realNDElement(intArrayOf(dim1, dim2)) { initializer(it[0], it[1]) }
-    }
-
-    fun real3DElement(dim1: Int, dim2: Int, dim3: Int, initializer: (Int, Int, Int) -> Double = { _, _, _ -> 0.0 }): NDElement<Double, DoubleField> {
-        return realNDElement(intArrayOf(dim1, dim2, dim3)) { initializer(it[0], it[1], it[2]) }
-    }
-
-    inline fun real(shape: IntArray, block: ExtendedNDField<Double, DoubleField>.() -> NDStructure<Double>): NDElement<Double, DoubleField> {
-        val field = ExtendedNDField(shape, DoubleField)
-        return NDStructureElement(field, field.run(block))
-    }
-
-    /**
-     * Simple boxing NDArray
-     */
-    fun <T : Any, F : Field<T>> create(field: F, shape: IntArray, initializer: (IntArray) -> T): NDElement<T, F> {
-        return GenericNDField(shape, field).produce { initializer(it) }
-    }
 }

kmath-core/src/commonMain/kotlin/scientifik/kmath/structures/NDStructure.kt

@@ -19,7 +19,7 @@ interface MutableNDStructure<T> : NDStructure<T> {
     operator fun set(index: IntArray, value: T)
 }
 
-fun <T> MutableNDStructure<T>.transformInPlace(action: (IntArray, T) -> T) {
+fun <T> MutableNDStructure<T>.mapInPlace(action: (IntArray, T) -> T) {
     elements().forEach { (index, oldValue) ->
         this[index] = action(index, oldValue)
     }
@@ -113,8 +113,8 @@ class DefaultStrides private constructor(override val shape: IntArray) : Strides
 }
 
 abstract class GenericNDStructure<T, B : Buffer<T>> : NDStructure<T> {
-    protected abstract val buffer: B
+    abstract val buffer: B
-    protected abstract val strides: Strides
+    abstract val strides: Strides
 
     override fun get(index: IntArray): T = buffer[strides.offset(index)]
 
@@ -153,7 +153,18 @@ class BufferNDStructure<T>(
         result = 31 * result + buffer.hashCode()
         return result
     }
+}
 
+/**
+ * Transform structure to a new structure using provided [BufferFactory] and optimizing if argument is [BufferNDStructure]
+ */
+inline fun <T, reified R : Any> NDStructure<T>.map(factory: BufferFactory<R> = ::inlineBuffer, crossinline transform: (T) -> R): BufferNDStructure<R> {
+    return if (this is BufferNDStructure<T>) {
+        BufferNDStructure(this.strides, factory.invoke(strides.linearSize) { transform(buffer[it]) })
+    } else {
+        val strides = DefaultStrides(shape)
+        BufferNDStructure(strides, factory.invoke(strides.linearSize) { transform(get(strides.index(it))) })
+    }
 }
 
 /**

kmath-core/src/commonTest/kotlin/scientifik/kmath/structures/GenericNDFieldTest.kt

@@ -1,16 +0,0 @@
-package scientifik.kmath.structures
-
-import scientifik.kmath.operations.DoubleField
-import scientifik.kmath.structures.NDElements.create
-import kotlin.test.Test
-import kotlin.test.assertEquals
-
-
-class GenericNDFieldTest{
-    @Test
-    fun testStrides(){
-        val ndArray = create(DoubleField, intArrayOf(10,10)){(it[0]+it[1]).toDouble()}
-        assertEquals(ndArray[5,5], 10.0)
-    }
-
-}

kmath-core/src/commonTest/kotlin/scientifik/kmath/structures/NDFieldTest.kt

@@ -0,0 +1,13 @@
+package scientifik.kmath.structures
+
+import kotlin.test.Test
+import kotlin.test.assertEquals
+
+
+class NDFieldTest {
+    @Test
+    fun testStrides() {
+        val ndArray = NDElement.real(intArrayOf(10, 10)) { (it[0] + it[1]).toDouble() }
+        assertEquals(ndArray[5, 5], 10.0)
+    }
+}

kmath-core/src/commonTest/kotlin/scientifik/kmath/structures/NumberNDFieldTest.kt

@@ -1,16 +1,15 @@
 package scientifik.kmath.structures
 
 import scientifik.kmath.operations.Norm
-import scientifik.kmath.structures.NDElements.real
+import scientifik.kmath.structures.NDElement.Companion.real2D
-import scientifik.kmath.structures.NDElements.real2DElement
 import kotlin.math.abs
 import kotlin.math.pow
 import kotlin.test.Test
 import kotlin.test.assertEquals
 
 class NumberNDFieldTest {
-    val array1 = real2DElement(3, 3) { i, j -> (i + j).toDouble() }
+    val array1 = real2D(3, 3) { i, j -> (i + j).toDouble() }
-    val array2 = real2DElement(3, 3) { i, j -> (i - j).toDouble() }
+    val array2 = real2D(3, 3) { i, j -> (i - j).toDouble() }
 
     @Test
     fun testSum() {
@@ -27,7 +26,7 @@ class NumberNDFieldTest {
     @Test
     fun testGeneration() {
 
-        val array = real2DElement(3, 3) { i, j -> (i * 10 + j).toDouble() }
+        val array = real2D(3, 3) { i, j -> (i * 10 + j).toDouble() }
 
         for (i in 0..2) {
             for (j in 0..2) {
@@ -52,7 +51,7 @@ class NumberNDFieldTest {
     }
 
     @Test
-    fun combineTest(){
+    fun combineTest() {
         val division = array1.combine(array2, Double::div)
     }
 
@@ -64,7 +63,7 @@ class NumberNDFieldTest {
 
     @Test
     fun testInternalContext() {
-        real(array1.shape) {
+        NDField.real(array1.shape).run {
             with(L2Norm) {
                 1 + norm(array1) + exp(array2)
             }

kmath-coroutines/src/commonMain/kotlin/scientifik/kmath/structures/LazyField.kt

@@ -0,0 +1,7 @@
+package scientifik.kmath.structures
+
+//
+//class LazyField<T>: Field<T> {
+//}
+//
+//class LazyValue<T: Any>():

kmath-coroutines/src/commonMain/kotlin/scientifik/kmath/structures/LazyNDField.kt

@@ -8,7 +8,7 @@ class LazyNDField<T, F : Field<T>>(shape: IntArray, field: F, val scope: Corouti
     override fun produceStructure(initializer: F.(IntArray) -> T): NDStructure<T> = LazyNDStructure(this) { initializer(field, it) }
 
 
-    override fun add(a: NDElement<T, F>, b: NDElement<T, F>): NDElement<T, F> {
+    override fun add(a: NDStructure<T>, b: NDStructure<T>): NDElement<T, F> {
         return LazyNDStructure(this) { index ->
             val aDeferred = a.deferred(index)
             val bDeferred = b.deferred(index)
@@ -16,11 +16,11 @@ class LazyNDField<T, F : Field<T>>(shape: IntArray, field: F, val scope: Corouti
         }
     }
 
-    override fun multiply(a: NDElement<T, F>, k: Double): NDElement<T, F> {
+    override fun multiply(a: NDStructure<T>, k: Double): NDElement<T, F> {
         return LazyNDStructure(this) { index -> a.await(index) * k }
     }
 
-    override fun multiply(a: NDElement<T, F>, b: NDElement<T, F>): NDElement<T, F> {
+    override fun multiply(a: NDStructure<T>, b: NDStructure<T>): NDElement<T, F> {
         return LazyNDStructure(this) { index ->
             val aDeferred = a.deferred(index)
             val bDeferred = b.deferred(index)
@@ -28,7 +28,7 @@ class LazyNDField<T, F : Field<T>>(shape: IntArray, field: F, val scope: Corouti
         }
     }
 
-    override fun divide(a: NDElement<T, F>, b: NDElement<T, F>): NDElement<T, F> {
+    override fun divide(a: NDStructure<T>, b: NDStructure<T>): NDElement<T, F> {
         return LazyNDStructure(this) { index ->
             val aDeferred = a.deferred(index)
             val bDeferred = b.deferred(index)
@@ -57,15 +57,15 @@ class LazyNDStructure<T, F : Field<T>>(override val context: LazyNDField<T, F>,
     }
 }
 
-fun <T> NDElement<T, *>.deferred(index: IntArray) = if (this is LazyNDStructure<T, *>) this.deferred(index) else CompletableDeferred(get(index))
+fun <T> NDStructure<T>.deferred(index: IntArray) = if (this is LazyNDStructure<T, *>) this.deferred(index) else CompletableDeferred(get(index))
 
-suspend fun <T> NDElement<T, *>.await(index: IntArray) = if (this is LazyNDStructure<T, *>) this.await(index) else get(index)
+suspend fun <T> NDStructure<T>.await(index: IntArray) = if (this is LazyNDStructure<T, *>) this.await(index) else get(index)
 
 fun <T, F : Field<T>> NDElement<T, F>.lazy(scope: CoroutineScope = GlobalScope): LazyNDStructure<T, F> {
     return if (this is LazyNDStructure<T, F>) {
         this
     } else {
-        val context = LazyNDField(context.shape, context.field)
+        val context = LazyNDField(context.shape, context.field, scope)
         LazyNDStructure(context) { get(it) }
     }
 }

kmath-coroutines/src/commonTest/kotlin/scientifik/kmath/structures/LazyNDFieldTest.kt

@@ -9,7 +9,7 @@ class LazyNDFieldTest {
     @Test
     fun testLazyStructure() {
         var counter = 0
-        val regularStructure = NDElements.create(IntField, intArrayOf(2, 2, 2)) { it[0] + it[1] - it[2] }
+        val regularStructure = NDElements.generic(intArrayOf(2, 2, 2), IntField) { it[0] + it[1] - it[2] }
         val result = (regularStructure.lazy() + 2).transform {
             counter++
             it * it

settings.gradle.kts

@@ -12,5 +12,5 @@ include(
         ":kmath-core",
         ":kmath-io",
         ":kmath-coroutines",
-        ":kmath-jmh"
+        ":benchmarks"
 )