We present fast-vollib, an open-source Python library that provides high-performance European option pricing, implied volatility (IV) computation, and Greeks under the Black-76, Black-Scholes, and Black-Scholes-Merton models. The library is designed as a drop-in alternative to the de-facto-standard py_vollib and py_vollib_vectorized packages, with pluggable PyTorch and JAX execution backends, a CUDA fused-kernel Triton contribution for batched IV workloads, and a compatibility-first public API. In addition to a vectorized Halley-method IV solver, fast-vollib ships an experimental, fully-vectorized implementation of Jäckel's "Let's Be Rational" (LBR) algorithm with NumPy/Numba, torch.compile, JAX, and Triton single-pass GPU kernels for batched option chains. This note announces the library and describes its public API surface, with source, documentation, and packaging artifacts available at: GitHub (https://github.com/raeidsaqur/fast-vollib), Docs (https://raeidsaqur.github.io/fast-vollib/), PyPI (https://pypi.org/project/fast-vollib/).

翻译：摘要：本文介绍fast-vollib——一个开源Python库，用于在Black-76、Black-Scholes和Black-Scholes-Merton模型下实现高性能欧式期权定价、隐含波动率（IV）计算及希腊值求解。该库设计为现行标准库py_vollib与py_vollib_vectorized的直接替代方案，配备了可插拔的PyTorch和JAX执行后端、用于批量IV工作负载的CUDA融合内核Triton贡献模块，以及优先保障兼容性的公共API。除向量化Halley法IV求解器外，fast-vollib还推出了Jäckel的"Let's Be Rational"（LBR）算法的实验性全向量化实现，该实现支持NumPy/Numba、torch.compile、JAX以及面向批量期权链的Triton单次遍历GPU内核。本文正式发布该库并描述其公共API接口，源代码、文档及打包资源可通过以下地址获取：GitHub (https://github.com/raeidsaqur/fast-vollib)、文档 (https://raeidsaqur.github.io/fast-vollib/)、PyPI (https://pypi.org/project/fast-vollib/)。