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Intro

Introducing the SIMD features of your CPU

Scalar parallel computing based on concurrency

Vector parallel computing based on SIMD machine

Shape and species of a Vector

Creating vectors from arrays to sum them

Loading any array in a vector using masks

Avoiding masking when it is not supported

Parallel cross-lanes and lane-wise operations

Computing the norm of a vector in parallel

Computing the average of vector components in parallel

Filtering and compressing a vector in parallel

Reducing a vector in parallel

Wrapping up parallel computations using vectors

Examples, patterns and performances

Outro

Description:

Explore the Vector API in Java to significantly accelerate computations using SIMD capabilities of modern CPUs. Dive into parallel computing on SIMD machines, learn how to leverage the Java Vector API for enhanced performance, and discover techniques to structure code for optimal utilization of these powerful features. Gain insights into vector creation, manipulation, and parallel operations such as summing, computing norms, averaging, filtering, and reducing. Examine practical examples, patterns, and performance metrics to master fast Java code writing using the Vector API.

Writing Fast Java Code with the Vector API - JEP Café 18

Java

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#Programming #Programming Languages #Java #Data Science #Data Processing #Computer Science #High Performance Computing #Parallel Computing #Computer Architecture #CPU Architecture #SIMD #Vector API