Cpp-Libraries on Pi Stack

Open-Source Fixed-Point Arithmetic Libraries: libfixmath vs fpm vs CNL vs shopspring/decimal

Fri, 19 Jun 2026 00:00:00 +0000

Introduction

Floating-point arithmetic is not always the right tool. In embedded systems without hardware FPUs, financial applications that demand exact decimal precision, and deterministic simulations that must produce identical results across platforms, fixed-point arithmetic provides a compelling alternative. Fixed-point numbers represent fractional values using integer types with an implicit scale factor — trading dynamic range for exact, deterministic computation.

Open-Source PRNG Algorithm Libraries: Xoshiro vs PCG vs SplitMix vs Mersenne Twister

Fri, 19 Jun 2026 00:00:00 +0000

Introduction

Random number generation is foundational to scientific computing, game development, cryptography, and statistical simulation. While your operating system provides /dev/urandom and language runtimes ship with default generators, the quality, speed, and statistical properties of those defaults vary dramatically. For Monte Carlo simulations, procedural content generation, randomized algorithms, and reproducible research, choosing the right pseudo-random number generator (PRNG) algorithm is critical.

Self-Hosted Concurrent Hash Map Libraries: Dashmap vs Flurry vs Evmap vs Folly AtomicHashMap

Fri, 19 Jun 2026 00:00:00 +0000

Modern multi-threaded applications demand data structures that scale across CPU cores without bottlenecks. A standard HashMap wrapped in a mutex becomes a serialization point — only one thread can access the map at a time, killing performance under contention. Concurrent hash map libraries solve this by allowing multiple threads to read and write simultaneously using lock-free algorithms, fine-grained locking, or sharding.

Self-Hosted Procedural Generation Noise Libraries: FastNoise2 vs OpenSimplex2 vs libnoise vs noise-rs

Fri, 19 Jun 2026 00:00:00 +0000

Introduction

Procedural generation is the backbone of modern game development, terrain simulation, and generative art. Rather than hand-crafting every mountain, forest density map, or cloud pattern, developers use noise functions — mathematical functions that produce coherent pseudo-random values across 2D, 3D, or 4D coordinate spaces. The right noise library dramatically impacts generation quality, performance, and artistic control.