Search Results for "kernel-athene" - Page 3
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Showing 2692 open source projects for "kernel-athene"
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Santa
A binary authorization system for macOS
Santa is a binary authorization system for macOS, aptly named since its main purpose is to keep track of binaries that are either naughty or nice. Santa is made up of a kernel extension (or a system extension on macOS 10.15+) that monitors and participates in execve() decisions, a userland daemon that makes the execution decisions, a GUI agent that shows notifications when an execve() is blocked, and a command-line utility that oversees system management and the synchronization of database and server. ... -
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Tile Kernels
A kernel library written in tilelang
Tile Kernels is a DeepSeek kernel library written with TileLang for high-performance AI and machine-learning workloads. It contains specialized kernels for areas such as mixture-of-experts routing, quantization, batched transpose operations, Engram gating, and Manifold HyperConnection components. The project includes both optimized kernel implementations and PyTorch reference versions for comparison and validation. -
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BCC (BPF Compiler Collection)
Tools for BPF-based Linux IO analysis, networking, monitoring, etc.
BCC is a toolkit that simplifies creating efficient kernel tracing, monitoring, and manipulation programs by leveraging extended Berkeley Packet Filters (eBPF). It includes a rich set of example tools and scripting interfaces in C, Python, and Lua. BCC makes BPF programs easier to write, with kernel instrumentation in C (and includes a C wrapper around LLVM), and front-ends in Python and lua. -
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almond
A Scala kernel for Jupyter
Almond already supports code navigation in dependencies via meta browse, paving the way for more IDE-like features and closer integration with the Scalameta ecosystem. Ammonite is a modern and user-friendly Scala shell. Almond wraps it in a Jupyter kernel, giving you all its features and niceties, including customizable pretty-printing, magic imports, advanced dependency handling, and its API, right from Jupyter. This also makes it easy to copy some code from notebooks to Ammonite scripts, and vice versa. Almond exposes APIs to interact with Jupyter front-ends. Call them from notebooks… or from your own libraries. ... -
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Fiwix
A UNIX-like kernel for the i386 architecture
Fiwix is a Unix-like operating system kernel designed for educational purposes and hobbyist development, targeting the i386 architecture. It implements many classic UNIX principles and aims to provide a clean, well-documented codebase that is both readable and easy to study. Fiwix offers a functional kernel that supports ELF binaries, a virtual file system, and standard system calls, making it a great platform for learning OS internals or experimenting with system-level programming. ... -
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IJulia.jl
Julia kernel for Jupyter
IJulia is a Julia-language backend (kernel) for Jupyter notebooks, allowing users to write and execute Julia code interactively in browser-based notebooks. It integrates seamlessly with Jupyter’s ecosystem, supporting markdown, plotting, multimedia, and inline output. IJulia is ideal for scientific computing, data analysis, and education, combining the power of Julia with the interactive capabilities of Jupyter. -
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LaTeX3
The expl3 (LaTeX3) Development Repository
...Some older reports from the early days of the project (mainly of historical interest) are available from the Comprehensive TeX Archive Network (CTAN) as ltx3pub. The repository contains development material for expl3. This includes not only code to be developed into the expl3 kernel, but also a variety of test, documentation and more experimental material. All of this code works on top of LaTeX2e. -
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The Astrid Contributor Handbook
The polyrepo, the kernel-is-dumb law, the RFC trigger
...It is not an application, but a documentation project that explains how contributors should understand the Astrid development model. The handbook covers the polyrepo structure, the kernel-is-dumb law, the RFC trigger, contribution tiers, and the release process. It is built with mdBook, which makes it suitable for local reading, web publication, and structured documentation workflows. The project gives contributors a shared reference for process, decision-making, and expectations before they make changes. Overall, it is a governance and onboarding guide for people contributing to the Astrid ecosystem. -
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Jupyter Enterprise Gateway
Enables Jupyter Notebooks to share resources across clusters
...From a technical perspective, Jupyter Enterprise Gateway is a web server that enables the ability to launch kernels on behalf of remote notebooks. This leads to better resource management, as the web server is no longer the single location for kernel activity. It essentially exposes a Kernel as a Service model. By default, the Jupyter framework runs kernels locally - potentially exhausting the server of resources. By leveraging the functionality of the underlying resource management applications like Hadoop YARN, Kubernetes, and others. -
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Pony OS
My Little Unix: Kernels are Magic
ponyos is a lightweight, UNIX-like operating system developed as a personal hobby project by the creator of ToaruOS. It features a monolithic kernel written in C and aims for a POSIX-compliant environment with a built-from-scratch userland. ponyos includes a graphical interface, dynamic linker, shared libraries, and a package manager. It’s designed for fun, experimentation, and as a platform to learn and play with operating system internals, with surprisingly advanced features given its hobbyist origin. -
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OCaml Jupyter
An OCaml kernel for Jupyter (IPython) notebook
An OCaml kernel for Jupyter Notebook. This provides an OCaml REPL with a great user interface such as markdown/HTML documentation, LaTeX formula by MathJax, and image embedding. OCaml Jupyter requires the libraries zlib, libffi, libgmp, libzmq 5+. -
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macFuse
FUSE extends macOS by adding support for user space file systems
...The content of these file systems can come from anywhere: from the local disk, from across the network, from memory, or any other combination of sources. Writing a file system using FUSE is orders of magnitude easier and quicker than the traditional approach of writing in-kernel file systems. Since FUSE file systems are regular applications (as opposed to kernel extensions), you have just as much flexibility and choice in programming tools, debuggers, and libraries as you have if you were developing standard macOS applications. -
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Burn
Burn is a new comprehensive dynamic Deep Learning Framework
Burn is a new comprehensive dynamic Deep Learning Framework from Tracel AI built using Rust with extreme flexibility, compute efficiency and portability as its primary goals. Burn emphasizes performance, flexibility, and portability for both training and inference. Developed in Rust, it is designed to empower machine learning engineers and researchers across industry and academia. -
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syzkaller
syzkaller is an unsupervised coverage-guided kernel fuzzer
syzkaller is Google’s coverage-guided, feedback-driven kernel fuzzer designed to uncover reliability and security bugs in operating system kernels at scale. It automatically generates, mutates, and minimizes system call programs, then drives them through a specialized executor (syz-executor) to exercise deep kernel paths. The system integrates tightly with sanitizers such as KASAN, KMSAN, KCSAN, and UBSAN to surface memory safety, concurrency, and undefined behavior issues with actionable reports. ... -
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hhuOS
hhuOS - A small operating system
hhuOS is an educational operating system project developed by students at Heinrich Heine University (HHU) in Düsseldorf, Germany. It is built from scratch in C and Assembly and intended as a teaching tool to help students grasp the foundations of kernel development, memory management, system calls, and multitasking. The project focuses on clarity, modularity, and hands-on experimentation with real OS components, making it suitable for OS development courses or personal exploration. -
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PicoGK
PicoGK is a compact and robust geometry kernel
PicoGK is a compact, open-source geometry kernel created by LEAP 71 for Computational Engineering. It is designed to let engineers generate complex physical objects through code instead of traditional manual CAD workflows. The library uses a deliberately reduced but powerful instruction set for building computational geometry. It supports geometry generation through voxel fields, lattices, implicit shapes, meshes, and robust Boolean operations. -
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RegionSpoof
Bank of China Mac one-click full Apple Smart
RegionSpoof is a macOS kernel extension project that attempts to enable Apple Intelligence features on region-restricted Apple Silicon Macs. It works by changing the device region information exposed through IORegistry, causing the system to report a U.S.-style region value instead of a China-region value. The repository includes an installer script, source files, a launch daemon configuration, build instructions, verification commands, troubleshooting guidance, and uninstall behavior. ... -
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RWKV Runner
A RWKV management and startup tool, full automation, only 8MB
...So it's combining the best of RNN and transformer - great performance, fast inference, fast training, saves VRAM, "infinite" ctxlen, and free text embedding. Moreover it's 100% attention-free. Default configs has enabled custom CUDA kernel acceleration, which is much faster and consumes much less VRAM. If you encounter possible compatibility issues, go to the Configs page and turn off Use Custom CUDA kernel to Accelerate. -
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NVIDIA Warp
A Python framework for accelerated simulation, data generation
NVIDIA Warp is a high-performance Python framework developed by NVIDIA for building and accelerating simulation, graphics, and physics-based workloads using GPU computing. It enables developers to write kernel-level code in Python that is automatically compiled into efficient CUDA kernels, combining ease of use with near-native performance. The framework is designed for applications such as robotics, reinforcement learning, physical simulation, and differentiable computing, where performance and flexibility are critical. Warp provides a set of primitives for working with arrays, geometry, and physics operations, allowing users to implement complex simulations without writing low-level CUDA code directly. ... -
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Flash Linux 0.11 Talk
Annotated Unix system source code
flash-linux0.11-talk is an annotated walkthrough of the Linux 0.11 kernel that explains how a tiny Unix-like system boots, schedules, handles interrupts, and manages memory. The materials break down historically compact and dense code into digestible segments, with diagrams and call flows that trace execution from bootloader to user space. By focusing on a small, early kernel, the series reveals core OS concepts without the complexity of modern subsystems. -
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LiteBox
A security-focused library OS supporting kernel execution
...The design emphasizes interoperability across different integration layers, describing a separation between “North” shims (how apps or runtimes plug in) and “South” platforms (where the sandbox runs), which helps the system adapt to multiple deployment contexts. A key aspect of the project is that it targets both kernel-mode and user-mode scenarios, enabling experimentation with different trust and performance tradeoffs. The repository positions LiteBox as a foundation for building hardened execution environments where untrusted or semi-trusted components can run with reduced privileges and a minimized host interface. -
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GoNB
GoNB, a Go Notebook Kernel for Jupyter
Go is a compiled language, but with very fast compilation, that allows one to use it in a REPL (Read-Eval-Print-Loop) fashion, by inserting a "Compile" step in the middle of the loop -- so it's a Read-Compile-Run-Print-Loop — while still feeling very interactive. GoNB leverages that compilation speed to implement a full-featured (at least it's getting there) Jupyter notebook kernel. As a side benefit it works with packages that use CGO — although it won't parse C code in the cells, so it can't be used as a C kernel. It already includes many goodies: cache between cell of results, contextual help and auto-complete (with gopls), compilation error context (by mousing over), bash command execution, images, html, etc. ...
