Search Results for "linux kernel"
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Showing 293 open source projects for "linux kernel"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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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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LKMPG
The Linux Kernel Module Programming Guide
lkmpg is a modernized, open-source guide that teaches the fundamentals of writing Linux kernel modules through clear explanations and working examples. It covers the full lifecycle: building and loading modules, understanding kernel symbols, handling device files, and interacting with kernel subsystems. Readers learn about concurrency concerns (spinlocks, mutexes), memory allocation in kernel space, and safe patterns for error handling and cleanup. ... -
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The Amazon Linux hibernation agent
The Amazon Linux hibernation agent
The purpose of this agent is to create a setup for an instance to support hibernation feature. The setup is created only on supported instance types. Upon startup, it checks for sufficient swap space to allow hibernate and fails if it's present but there's not enough of it. If there's no swap space, it launches a background thread to create it and touch all of its blocks to make sure that EBS volumes are pre-warmed if configured. This is configurable. It updates the offset of the swap file... -
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HyDE Linux
Aesthetic, dynamic and minimal dots for Arch hyprland
...The install script will auto-detect an NVIDIA card and install nvidia-dkms drivers for your kernel. -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Armbian Linux Build Framework
Armbian Linux Build Framework
Powerful menu-driven configuration tool along with stock Debian utilities. BASH shell and lightweight XFCE-based desktop. Standard boot, config, and update methods with minimal user-space footprint. 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... -
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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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gVisor
Application Kernel for Containers
gVisor is an application kernel developed by Google that provides a strong layer of isolation between applications and the host operating system. Written in Go, it implements a Linux-compatible system call interface that runs entirely in user space, creating a secure sandboxed environment for containers. Unlike traditional virtual machines or lightweight syscall filters, gVisor follows a third approach that offers many of the security benefits of virtualization while maintaining the speed, resource efficiency, and flexibility of containers. ... -
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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. -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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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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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. It is suited for many tasks, including performance analysis and network traffic control. With a... -
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JupyterLab LSP
Coding assistance for JupyterLab (code navigation + hover suggestions
Hover over any piece of code; if an underline appears, you can press Ctrl to get a tooltip with function/class signature, module documentation or any other piece of information that the language server provides. Critical errors have red underline, warnings are orange, etc. Hover over the underlined code to see a more detailed message. 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... -
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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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CuPy
A NumPy-compatible array library accelerated by CUDA
CuPy is an open source implementation of NumPy-compatible multi-dimensional array accelerated with NVIDIA CUDA. It consists of cupy.ndarray, a core multi-dimensional array class and many functions on it. CuPy offers GPU accelerated computing with Python, using CUDA-related libraries to fully utilize the GPU architecture. According to benchmarks, it can even speed up some operations by more than 100X. CuPy is highly compatible with NumPy, serving as a drop-in replacement in most... -
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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... -
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LiteBox
A security-focused library OS supporting kernel execution
LiteBox is a security-focused “library OS” sandboxing project that aims to shrink the interface between an application and its host environment to reduce attack surface. Instead of relying solely on broad OS-level permissions, it focuses on isolating workloads by tightly controlling the boundary where code interacts with host services and system resources. The design emphasizes interoperability across different integration layers, describing a separation between “North” shims (how apps or... -
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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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CUDA Python
Performance meets Productivity
CUDA Python is a unified Python interface for accessing and working with the NVIDIA CUDA platform, enabling developers to build GPU-accelerated applications entirely in Python. It acts as a metapackage composed of multiple submodules that provide both high-level and low-level access to CUDA functionality, including runtime APIs, driver APIs, and JIT compilation tools. The project is designed to simplify GPU programming by offering Pythonic abstractions while still exposing the full power of... -
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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... -
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CubeCL
Multi-platform high-performance compute language extension for Rust
CubeCL is a low-level compute language and compiler framework designed to simplify and optimize GPU programming for high-performance workloads, particularly in machine learning and numerical computing. It provides an abstraction layer that allows developers to write portable, hardware-efficient compute kernels without directly dealing with complex GPU APIs such as CUDA or OpenCL. CubeCL focuses on delivering predictable performance and composability by exposing explicit control over memory... -
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Tun2Socks
tun2socks , powered by gVisor TCP/IP stack
Proxy Everything: Handle all network traffic of any internet programs sent by the device through a proxy. Proxy Protocols: HTTP/Socks4/Socks5/Shadowsocks with authentication support for remote connections. Run Everywhere. Linux/macOS/Windows/FreeBSD/OpenBSD multi-platform support with specific optimization. Gateway Mode: Act as a layer three gateway to handle network traffic from other devices in the same network. Full IPv6 Support: All functions work in IPv6, tunnel IPv4 connections through IPv6 proxy and vice versa. Network Stack: Powered by user-space TCP/IP stack from Google container application kernel gVisor. -
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Perfetto
Production-grade client-side tracing, profiling, and analysis
Perfetto is a production-grade tracing platform for Android, Linux, and Chrome that captures extremely detailed information about what a system is doing over time. 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. ... -
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SocketCAN userspace utilities and tools
Linux-CAN / SocketCAN user space applications
SocketCAN userspace utilities and tools. This repository contains some userspace utilities for the Linux CAN subsystem (aka SocketCAN). -
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ipytest
Pytest in IPython notebooks
ipytest allows you to run Pytest in Jupyter notebooks. ipytest aims to give access to the full pytest experience and to make it easy to transfer tests out of notebooks into separate test files. -
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Inspektor Gadget
The eBPF tool and systems inspection framework for Kubernetes
Inspektor Gadget is a collection of tools (or gadgets) to debug and inspect Kubernetes resources and applications. It manages the packaging, deployment, and execution of eBPF programs in a Kubernetes cluster, including many based on BCC tools, as well as some developed specifically for use in Inspektor Gadget. It automatically maps low-level kernel primitives to high-level Kubernetes resources, making it easier and quicker to find the relevant information.
