Könyv Mastering SIMD with Java Vector API Roman Snytsar

Mastering SIMD with Java Vector API

Szerző: Roman Snytsar
Nyelv: Angol
Kötés: Puha kötésű
Kiadó: APRESS L.P.
Elérhetőség: Könyvújdonság
Megjelenés ismeretlen
15 696 Ft
Learn how to write Java code faster by using the Vector API for SIMD operations. This book shows you...

Információk a könyvről

Szerző
Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2026
oldal
158
EAN
9798868826757
Enbook ID
51307831
Kiadó

Teljes leírás

Learn how to write Java code faster by using the Vector API for SIMD operations. This book shows you how to apply data-level parallelism to common algorithms without leaving the Java ecosystem, making modern CPU capabilities accessible to everyday developers.

The book uses a problem-first approach. Each chapter starts with a familiar coding task such as array summation or prefix sums and then reworks the solution using vectorization. You ll move from simple element-wise operations to advanced techniques like parallel scans, bitonic sorting, and sliding window optimizations. Extensive code examples, performance benchmarks, diagrams, and assembly analysis ensure you understand both the how and the why behind every optimization.

Today, the rise of computer-heavy applications in finance, scientific computing, machine learning and real-time analytics makes understanding vectorization an essential skill for developers. Modern processors dedicate significant silicon to vector units, yet most Java code never uses them. By mastering the Vector API, you ll learn to recognize patterns that benefit from SIMD, write production-ready vector algorithms, and make informed architectural decisions. This is your guide to writing faster, smarter Java code that fully leverages today s hardware.

What You Will Learn:

  • Master Java Vector API and SIMD across x86 and ARM architectures.
  • Build vector-length-agnostic algorithms for any hardware platform.
  • Spot patterns for vectorization and use masked ops for conditional logic.
  • Optimize vertical vs. horizontal ops and avoid instruction-level hazards.
  • Ensure numerical stability and verify vectorization via assembly analysis

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