Search Results for "kernel-ntfs"
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Showing 214 open source projects for "kernel-ntfs"
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Lunatik
Lunatik is a framework for scripting the Linux kernel with Lua
Lunatik is a framework for scripting the Linux kernel with Lua. It is composed by the Lua interpreter modified to run in the kernel; a device driver (written in Lua =)) and a command line tool to load and run scripts and manage runtime environments from the user space; a C API to load and run scripts and manage runtime environments from the kernel; and Lua APIs for binding kernel facilities to Lua scripts. -
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pwru
eBPF-based Linux kernel networking debugger
pwru is an eBPF-based tool for tracing network packets in the Linux kernel with advanced filtering capabilities. It allows fine-grained introspection of kernel state to facilitate debugging network connectivity issues. -
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eBPF
ebpf-go is a pure-Go library to read, modify and load eBPF programs
Package ebpf is a toolkit for working with eBPF programs. eBPF programs are small snippets of code which are executed directly in a VM in the Linux kernel, which makes them very fast and flexible. Many Linux subsystems now accept eBPF programs. This makes it possible to implement highly application-specific logic inside the kernel, without having to modify the actual kernel itself. This package is designed for long-running processes which want to use eBPF to implement part of their application logic. ... -
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Nitro Enclaves Command Line Interface
Tooling for Nitro Enclave management
This repository contains a collection of tools and commands used for managing the lifecycle of enclaves. The Nitro CLI needs to be installed on the parent instance, and it can be used to start, manage, and terminate enclaves. The Nitro Enclaves kernel driver is available in the upstream Linux kernel starting with the v5.10 kernel for x86_64 and starting with the v5.16 kernel for arm64. The codebase from the 'drivers/virt/nitro_enclaves' directory in this GitHub repository is similar to the one merged into the upstream Linux kernel. The enclaves do not have access to a physical disk, just a RAM filesystem. ... -
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Copy Fail - CVE-2026-31431
epository that demonstrates and analyzes a Linux kernel vulnerability
Copy Fail - CVE-2026-31431 is a proof-of-concept repository that demonstrates and analyzes a specific Linux kernel vulnerability identified as CVE-2026-31431. The project provides experimental scripts and documentation to reproduce and study the exploit in controlled environments. It is designed for security researchers and engineers who want to understand the mechanics of the vulnerability. The repository includes tested configurations across multiple Linux distributions and kernel versions. ... -
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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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linux-wasm
WebAssembly (Wasm) arch support for the Linux kernel
linux-wasm is an experimental project that ports the Linux kernel to run directly as a WebAssembly module, enabling a full Linux environment to boot and operate entirely inside a web browser without virtualization or cloud infrastructure. Instead of emulating Linux through a virtual machine, this project compiles the actual kernel for a WebAssembly target, allowing it to execute natively within a Wasm runtime. -
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JupyterLab LSP
Coding assistance for JupyterLab (code navigation + hover suggestions
...Use the context menu entry, or Alt + 🖱️ to jump to definitions/references (you can change it to Ctrl/⌘ in settings); use Alt + o to jump back. Place your cursor on a variable, function, etc and all the usages will be highlighted. When a kernel is available the suggestions from the kernel (such as keys of a dict and columns of a DataFrame) are merged with the suggestions from the Language Server (in notebook). If the kernel is too slow to respond promptly only the Language Server suggestions will be shown (default threshold: 0.6s). You can configure the completer to not attempt to fetch the kernel completions if the kernel is busy. -
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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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gophernotes
The Go kernel for Jupyter notebooks and nteract
...The gophernotes logo was designed by the brilliant Marcus Olsson and was inspired by Renee French's original Go Gopher design. If you have the JUPYTER_PATH environmental variable set or if you are using an older version of Jupyter, you may need to copy this kernel config to another directory. -
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Perfetto
Production-grade client-side tracing, profiling, and analysis
...It’s designed around a low-overhead producer/consumer model: instrumented components (“producers”) write binary events into shared memory buffers and a collector (“service”) reliably streams them to storage. The data model spans kernel and userspace, so you can stitch together CPU scheduling, app lifecycles, binder/IPC hops, GPU work, power and thermal signals, file I/O, heap samples, and more into a single coherent timeline. Perfetto’s ecosystem includes a web-based UI that can load multi-GB traces directly in the browser and an offline “trace processor” that exposes the trace as a queryable SQL-like table schema for deep analysis and automation. ... -
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Triton
Development repository for the Triton language and compiler
Triton is a programming language and compiler framework specifically designed for writing highly efficient custom deep learning operations, particularly for GPUs. It aims to bridge the gap between low-level GPU programming, such as CUDA, and higher-level abstractions by providing a more productive and flexible environment for developers. Triton enables users to write optimized kernels for machine learning workloads while maintaining readability and control over performance-critical aspects... -
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Spyder notebook plugin
Jupyter notebook integration with Spyder
...Currently, it supports basic functionality such as creating new notebooks, opening any notebook in your filesystem and saving notebooks at any location. You can also use Spyder's file switcher to easily switch between notebooks and open an IPython console connected to the kernel of a notebook to inspect its variables in the Variable Explorer. -
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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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CUDA Python
Performance meets Productivity
...The project is designed to simplify GPU programming by offering Pythonic abstractions while still exposing the full power of CUDA for advanced users. It integrates tightly with the broader Python GPU ecosystem, including Numba for kernel compilation and CCCL for parallel primitives, allowing developers to write performant code without leaving Python. The toolkit also includes utilities for profiling, memory management, distributed computing, and numerical operations, making it suitable for scientific computing, AI, and data processing workloads. -
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ToaruOS
Hobby operating system, bootloader, kernel, drivers, C library
...While many independent, hobby, and research OSes aim to experiment with new designs, ToaruOS is intended as an educational resource, providing a representative microcosm of functionality found in major desktop operating systems. The OS includes a kernel, bootloader, dynamic shared object linker, C standard library, its own composited windowing system, a dynamic bytecode-compiled programming language, advanced code editor, and dozens of other utilities and example applications. There are no external runtime dependencies and all required source code, totaling roughly 100k lines of (primarily) C, is included in this repository, save for Kuroko, which lives separately. ... -
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CuPy
A NumPy-compatible array library accelerated by CUDA
...CuPy is highly compatible with NumPy, serving as a drop-in replacement in most cases. CuPy is very easy to install through pip or through precompiled binary packages called wheels for recommended environments. It also makes writing a custom CUDA kernel very easy, requiring only a small code snippet of C++. -
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Cosmos
Cosmos is an operating system "construction kit"
...Cosmos (C# Open Source Managed Operating System) is an operating system development kit that uses Visual Studio as its development environment. Despite C# in the name any .NET-based language can be used including VB.NET, Fortran, Delphi Prism, IronPython, F# and more. Cosmos itself and the kernel routines are primarily written in C#, and thus the Cosmos name. Cosmos is not an operating system in the traditional sense, but instead, it is an "Operating System Development Kit". Cosmos lets you create operating systems just as Visual Studio and C# normally let you create applications. Most users can write and boot their own operating system in just a few minutes, all using Visual Studio. -
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Multik
Multidimensional array library for Kotlin
Multidimensional array library for Kotlin. -
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Armbian Linux Build Framework
Armbian Linux Build Framework
...Special config utilities are optional. A distributed image is compressed to its real data size which starts below 1G. Login is possible via serial, HDMI/VGA or SSH. Boot loader and kernel optimizations, memory caching, ZRAM swap, and video acceleration where applicable. Images are made fully automatized from sources. Releases are PGP signed and code is regularly inspected by the community. Long-term support, quick security fixes, documentation and community-based end-user support. Make sure you have a good & reliable SD card and a proper power supply. ... -
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fswatch
A cross-platform file change monitor with multiple backends
...A monitor based on kqueue, an event notification interface introduced in FreeBSD 4.1 and supported on most BSD systems (including OS X). A monitor based on inotify, a Linux kernel subsystem that reports file system changes to applications. A monitor based on File Events Notification, a Solaris/Illumos kernel API that reports file events. A monitor based on ReadDirectoryChangesW, a Microsoft Windows API that reports changes to a directory. -
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Git
Fast, scalable, distributed revision control system
Git is a free, distributed version control system created by Linus Torvalds in 2005 to manage the development of the Linux kernel. It emphasizes speed, data integrity, and support for non-linear workflows, and remains the most popular VCS for collaborative software development. Git is an Open Source project covered by the GNU General Public License version 2 (some parts of it are under different licenses, compatible with the GPLv2). It was originally written by Linus Torvalds with help of a group of hackers around the net. ... -
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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. ... -
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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. ...
