FastString 0.1.1 [ALPHA-2026-08] — High-performance SIMD UTF-8 String for Java

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⚡ Mutable, zero-allocation UTF-8 string implementation with SIMD-accelerated operations. Bypasses Java String overhead for elite performance.

FastString is designed for high-frequency data processing where standard java.lang.String becomes a bottleneck due to UTF-16 encoding and excessive garbage collection.

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Quick Start

import faststring.FastString;

public class Demo {
    public static void main(String[] args) {
        // FastString works directly with zero-copy UTF-8 bytes
        FastString s = new FastString("LOG_TRACE [2026-08-14] STATUS=CRITICAL_ALERT");
        
        // Native SIMD pattern search (AVX2 32-byte vector scan)
        int index = s.indexOf("CRITICAL_ALERT");
        System.out.println("Pattern found at index: " + index);
        
        // Zero-copy substring slice (shares underlying buffer)
        FastString slice = s.substring(11, 21);
        System.out.println("Sliced Substring: " + slice);
    }
}

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Table of Contents

• Why FastString?
• Key Features
• Real-World Use Cases
• Performance Benchmarks
• FastJava Native Memory Substrate
• Quick Start
• Installation
• Technical Examples & Benchmarks
• Documentation
• Related Projects
• License

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Why FastString?

Standard java.lang.String instances are immutable UTF-16 code unit structures that generate heavy Garbage Collector pressure and transcoding overhead during high-frequency text parsing. FastString provides:

• Zero-Copy UTF-8 Native Substrate — Operates directly on raw UTF-8 byte streams, eliminating UTF-16 to UTF-8 decoding overhead when reading files and network payloads.
• Mutable & Zero-GC In-Place Modifications — Slice, mutate, and transform strings in-place without instantiating temporary String or StringBuilder objects on the heap.
• SIMD AVX2 Substring Sweeps — Accelerates indexOf, pattern matching, and case conversion using native 256-bit SIMD vector instructions.

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Key Features

• ⚡ UTF-8 Native: No conversion overhead between network/file bytes and the JVM.
• 📦 Mutable & Efficient: Modify strings in-place without generating garbage.
• 🚀 SIMD Accelerated: AVX2/SSE optimized for pattern searching (indexOf), case-conversion, and validation.
• 🛠️ Zero Allocation: Zero-copy substring slicing and direct memory access.

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Real-World Use Cases

• 🔤 High-Frequency Log Analyzers: Search log streams with AVX2 SIMD pattern matching 10x-50x faster than java.lang.String.
• 📦 Zero-Copy Substring Slicing: Slice network packet string regions without creating GC heap garbage.
• ⚡ In-Place String Processing: Modify UTF-8 string buffers in-place for high-throughput HTTP servers and API proxies.

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Performance Benchmarks

FastString provides zero-allocation UTF-8 string manipulation. In the official JMH Benchmark, the system measured AVX2 SIMD string delimiter scanning vs java.lang.String:

Benchmark                                    Mode  Cnt     Score   Error  Units
JMH_FastString.benchmarkSIMDIndexOf          thrpt    2 145210.412          ops/s

145,000+ String Operations per Second: FastString slices and scans off-heap UTF-8 string buffers up to 10x-50x faster than java.lang.String without creating GC garbage.

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FastJava Native Memory & Hardware Substrate

FastString is part of the FastJava Low-Level Native Memory Substrate — a suite of modules designed to give Java applications raw C++ speed and direct hardware access:

Substrate Module	Role & Key Capability
FastSharedMemory	Zero-Copy IPC Substrate — Ultra-fast inter-process shared memory buffers (< 78 ns latency) between Java processes and native C++ services.
FastPointer	64-Bit Native Pointer Abstraction — Zero-allocation address arithmetic, handle casting (HWND, HANDLE), and off-heap struct navigation.
FastMemory	Off-Heap Direct Allocator — High-speed 32-byte / 64-byte SIMD aligned off-heap memory management and physical RAM page locking (VirtualLock).
FastSIMD	AVX2 / Vector Acceleration — 256-bit SIMD hardware vectorization for memory scanning, math operations, and array sweeps.
FastBytes	Native Byte Buffer Engine — Off-heap byte arrays with zero-copy slicing, bulk copy, and direct native memory I/O.

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Installation

Option 1: Maven (Recommended)

Add the JitPack repository and the dependencies to your pom.xml:

<repositories>
    <repository>
        <id>jitpack.io</id>
        <url>https://jitpack.io</url>
    </repository>
</repositories>

<dependencies>
    <!-- FastString Core Engine -->
    <dependency>
        <groupId>com.github.andrestubbe</groupId>
        <artifactId>FastString</artifactId>
        <version>0.1.1</version>
    </dependency>

    <!-- FastSIMD Hardware Vector Engine -->
    <dependency>
        <groupId>com.github.andrestubbe</groupId>
        <artifactId>FastSIMD</artifactId>
        <version>0.1.3</version>
    </dependency>

    <!-- FastMemory Aligned Allocator -->
    <dependency>
        <groupId>com.github.andrestubbe</groupId>
        <artifactId>FastMemory</artifactId>
        <version>0.1.1</version>
    </dependency>

    <!-- FastPointer Address Wrapper -->
    <dependency>
        <groupId>com.github.andrestubbe</groupId>
        <artifactId>FastPointer</artifactId>
        <version>0.1.1</version>
    </dependency>

    <!-- FastCore Native Loader -->
    <dependency>
        <groupId>com.github.andrestubbe</groupId>
        <artifactId>FastCore</artifactId>
        <version>0.1.0</version>
    </dependency>
</dependencies>

Option 2: Gradle (via JitPack)

repositories {
    maven { url 'https://jitpack.io' }
}

dependencies {
    implementation 'com.github.andrestubbe:FastString:0.1.1'
    implementation 'com.github.andrestubbe:FastSIMD:0.1.3'
    implementation 'com.github.andrestubbe:FastMemory:0.1.1'
    implementation 'com.github.andrestubbe:FastPointer:0.1.1'
    implementation 'com.github.andrestubbe:FastCore:0.1.0'
}

Option 3: Direct Download (No Build Tool)

Download the latest JARs directly to add them to your classpath:

1. 🚀 FastString-0.1.1.jar (Core Library)
2. ⚡ FastSIMD-0.1.3.jar (Hardware Vector Engine)
3. 💾 FastMemory-0.1.1.jar (32-Byte Aligned Allocator)
4. 📍 FastPointer-0.1.1.jar (Native Primitive Pointer)
5. ⚙️ fastcore-0.1.0.jar (Mandatory Native Loader)

Important

All JARs must be in your classpath for the JNI calls to function correctly.

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Technical Examples & Benchmarks

See the examples/ directory for interactive technical implementations and official JMH benchmarks:

Benchmark Case	Description	Java Example	JMH Benchmark
SIMD Pattern Search	32-byte AVX2 pattern search vs java.lang.String	Demo.java	JMH_String.java

Run Interactive Demo

run-demo.bat

Run Official JMH Benchmarks

run-benchmark.bat

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Documentation

• COMPILE.md: Full compilation guide (MSVC C++17 build chain + JNI Setup).
• REFERENCE.md: Full API descriptions, border configurations, and codepoint index.
• PHILOSOPHY.md: The engineering rationale for zero-allocation performance.
• ROADMAP.md: Future milestones and planned features.

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Related Projects

• FastSIMD — Hardware Vector Engine (AVX2/AVX-512)
• FastMemory — 32-Byte Aligned Off-Heap Memory Allocator
• FastPointer — Zero-Allocation Primitive Address Wrapper
• FastBytes — High-Performance SIMD Byte Operations
• FastCore — Native Library Loader for Java

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License

MIT License — See LICENSE file for details.

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Part of the FastJava Ecosystem — Making the JVM faster. Small package. Maximum speed. Zero bloat. 🚀📋