VectorAPIDemo.java

package java24.vector;

/**
 * Java 24 Vector API (Ninth Incubator) Demonstrates SIMD-style vector computations
 * NOTE: This is an incubator feature requiring:
 * - --add-modules jdk.incubator.vector
 * 
 * Compile: javac --add-modules jdk.incubator.vector VectorAPIDemo.java
 * Run: java --add-modules jdk.incubator.vector VectorAPIDemo
 */
public class VectorAPIDemo
{
	public static void main(String[] args)
	{
		System.out.println("=== Java 24 Vector API (Ninth Incubator) ===\n");

		System.out.println("Overview:");
		System.out.println("--------");
		System.out.println("The Vector API provides SIMD (Single Instruction, Multiple Data) operations");
		System.out.println("for parallel processing of arrays with hardware-optimized computations.\n");

		System.out.println("Example 1: Basic Vector Operations");
		System.out.println("----------------------------------");
		System.out.println("""
				import jdk.incubator.vector.*;
				
				// Define vector species (size)
				VectorSpecies<Float> SPECIES = FloatVector.SPECIES_PREFERRED;
				
				// Arrays to process
				float[] a = {1.0f, 2.0f, 3.0f, 4.0f};
				float[] b = {5.0f, 6.0f, 7.0f, 8.0f};
				float[] c = new float[4];
				
				// Load vectors from arrays
				FloatVector va = FloatVector.fromArray(SPECIES, a, 0);
				FloatVector vb = FloatVector.fromArray(SPECIES, b, 0);
				
				// Perform vector operation (add)
				FloatVector vc = va.add(vb);
				
				// Store result back to array
				vc.intoArray(c, 0);
				// Result: c = [6.0f, 8.0f, 10.0f, 12.0f]
				""");

		System.out.println("\nExample 2: Vectorized Loop");
		System.out.println("--------------------------");
		System.out.println("""
				float[] array = new float[1000];
				// Initialize array...
				
				VectorSpecies<Float> SPECIES = FloatVector.SPECIES_PREFERRED;
				
				for (int i = 0; i < array.length; i += SPECIES.length()) {
				    FloatVector vector = FloatVector.fromArray(SPECIES, array, i);
				    FloatVector result = vector.mul(2.0f); // Multiply by 2
				    result.intoArray(array, i);
				}
				""");

		System.out.println("\nKey Features:");
		System.out.println("- Hardware-agnostic: Works on different platforms");
		System.out.println("- Automatic optimization: Compiles to optimal instructions");
		System.out.println("- Type-safe: Supports int, long, float, double");
		System.out.println("- SIMD operations: Parallel processing of multiple elements");
		System.out.println("- Platform-specific optimizations");
		System.out.println("- Ninth incubator iteration (continued refinement)");

		System.out.println("\nSupported Types:");
		System.out.println("- IntVector, LongVector");
		System.out.println("- FloatVector, DoubleVector");
		System.out.println("- ByteVector, ShortVector");

		System.out.println("\nUse Cases:");
		System.out.println("- Scientific computing");
		System.out.println("- Machine learning");
		System.out.println("- Image processing");
		System.out.println("- Signal processing");
		System.out.println("- Numerical simulations");
		System.out.println("- Cryptography");
		System.out.println("- AI inference");

		System.out.println("\nBenefits:");
		System.out.println("- Better performance than scalar operations");
		System.out.println("- Parallel processing of multiple elements");
		System.out.println("- Hardware-optimized instructions");
		System.out.println("- Type-safe and platform-independent");
		System.out.println("- Expressive API");

		System.out.println("\nNote: This is an incubator feature in Java 24 (Ninth Incubator).");
		System.out.println("Requires --add-modules jdk.incubator.vector flag.");
	}
}