====== Java Vector API ======
Java Vector  API provides the ability to explicitly write vector ([[https://en.wikipedia.org/wiki/Single_instruction,_multiple_data|SIMD]]) computations that compiles to vector instructions on supported CPUs. Although one of the JVM JIT compiler optimizations (called auto-vectorization) uses the vector instructions too, it cannot always benefit from them because it cannot know as much about the algorithm as the programmer.

The feature is still under development; however, it is mature enough to be a part of the JDK library as an incubator module from Java 16. You need to explicitly include the module by the following JVM argument: 
<code>--add-modules jdk.incubator.vector</code>

===== Exercises =====

==== Sum of an Array ====
Try to implement the following code using vector API (solution will be presented during the seminar and later provided in slides):

<code>
public static int sum(int[] array) {
	int sum = 0;
	for (int i : array) {
		sum += i;
	}
	return sum;
}
</code>

==== Dot Product ====
Implement dot product using vector API. Scalar implementation can be seen here:
<code>
public static int dot(int[] v1, int[] v2) {
	if (v1.length != v2.length) throw new IllegalArgumentException();
	int sum = 0;
	for (int i = 0; i < v1.length; i++) {
		sum += v1[i] * v2[i];
	}
	return sum;
}

</code>

==== Matrix Multiplication ====
You can also try to improve the multiplication with the second matrix transposed. 
===== Materials =====
The documentation can be seen in the appropriate JEPs:  [[https://openjdk.java.net/jeps/338|338]], [[https://openjdk.java.net/jeps/414|414]], [[https://openjdk.java.net/jeps/417|417]]

Or you can look at this [[https://www.youtube.com/watch?v=VYo3p4R66N8&ab_channel=Java|video]]

Slides from the seminar (will be provided later)