In this session, we will discuss the Vector API in a preview in Java. We will begin by introducing SIMD (single instruction, multiple data) and explore how it can be used to maximize computation speed. The session will then cover the setup required to use the Vector API, including how to establish a species, define and use components and lanes, and apply masking with different strategies. We will also discuss same-lane and cross-lane computation. Finally, we will conclude by presenting metrics comparing the performance of using the Vector API versus not using it.

This session is primarily aimed at backend developers working on performance-intensive applications, as they can leverage the Vector API to optimize computational tasks. Software architects are the secondary audience, as they need to understand the implications of using the Vector API when designing high-performance systems that require efficient data processing. DeepTech professionals may also find this session valuable on account of its focus on advanced computational techniques and performance optimizations using SIMD and the Vector API.