The Serenity Operating System 🐞
- operating-system
- c-plus-plus
- os
- unix
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The Serenity Operating System 🐞
FlashMLA: Efficient Multi-head Latent Attention Kernels
Jupyter kernel for the C++ programming language
Web Serving and Remote Procedure Calls at 50x lower latency and 70x higher bandwidth than FastAPI, implementing JSON-RPC & REST over io_uring ☎️
WinDBG Anti-RootKit Extension
Fuzzer for Linux Kernel Drivers
Bayesian Generalized Kernel Inference for Terrain Traversability Mapping
An In-Kernel Solution Based on eBPF / XDP for 5G UPF
Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.
A modular Linux telemetry engine built with eBPF, libbpf CO-RE, and Modern C++ that captures kernel-level process, file, syscall, and network events through a portable event-processing pipeline for decoding, enrichment, filtering, and structured output—forming the foundation for higher-level runtime intelligence.