Search Results for "windows kernel"
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Showing 39 open source projects for "windows kernel"
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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... -
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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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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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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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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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ToaruOS
Hobby operating system, bootloader, kernel, drivers, C library
ToaruOS is a "complete" operating system for x86-64 PCs and experimental support for ARMv8. 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,... -
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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... -
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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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Multik
Multidimensional array library for Kotlin
Multidimensional array library for Kotlin. -
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Spyder notebook plugin
Jupyter notebook integration with Spyder
Spyder plugin to use Jupyter notebooks inside 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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eCapture
Capturing SSL/TLS plaintext without a CA certificate using eBPF
Capture SSL/TLS text content without a CA certificate using eBPF. Supports Linux/Android kernel versions x86_64 4.18 and above, aarch64 5.5 and above. Does not support Windows and macOS systems. -
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FlashMLA
FlashMLA: Efficient Multi-head Latent Attention Kernels
FlashMLA is a high-performance decoding kernel library designed especially for Multi-Head Latent Attention (MLA) workloads, targeting NVIDIA Hopper GPU architectures. It provides optimized kernels for MLA decoding, including support for variable-length sequences, helping reduce latency and increase throughput in model inference systems using that attention style. The library supports both BF16 and FP16 data types, and includes a paged KV cache implementation with a block size of 64 to... -
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TensorRT
C++ library for high performance inference on NVIDIA GPUs
NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference. It includes a deep learning inference optimizer and runtime that delivers low latency and high throughput for deep learning inference applications. TensorRT-based applications perform up to 40X faster than CPU-only platforms during inference. With TensorRT, you can optimize neural network models trained in all major frameworks, calibrate for lower precision with high accuracy, and deploy to hyperscale data centers,... -
14
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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FFTW.jl
Julia bindings to the FFTW library for fast Fourier transforms
This package provides Julia bindings to the FFTW library for fast Fourier transforms (FFTs), as well as functionality useful for signal processing. These functions were formerly a part of Base Julia. Users with a build of Julia based on Intel's Math Kernel Library (MKL) can use MKL for FFTs by setting a preference in their top-level project by either using the FFTW.set_provider!() method, or by directly setting the preference using Preferences.jl. Note that this choice will be recorded for... -
16
PyTorch Geometric
Geometric deep learning extension library for PyTorch
It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of an easy-to-use mini-batch loader for many small and single giant graphs, a large number of common benchmark datasets (based on simple interfaces to create your own), and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. We have outsourced a lot of... -
17
oneDNN
oneAPI Deep Neural Network Library (oneDNN)
This software was previously known as Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN) and Deep Neural Network Library (DNNL). oneAPI Deep Neural Network Library (oneDNN) is an open-source cross-platform performance library of basic building blocks for deep learning applications. oneDNN is part of oneAPI. The library is optimized for Intel(R) Architecture Processors, Intel Processor Graphics and Xe Architecture graphics. oneDNN has experimental support for the... -
18
Unikraft
A next-generation cloud native kernel designed to unlock performance
Unikraft powers the next generation of cloud-native, containerless applications by enabling you to radically customize and build custom OS/kernels; unlocking best-in-class performance, security primitives, and efficiency savings. Unikraft optimizes resource utilization, leading to smaller footprints (meaning higher server saturation) and improved efficiency in resource-constrained environments. Unikraft is an open-source project driven by a vibrant community of over 100 developers, fostering... -
19
Asmosis
A set of tools related to assembly language programming.
Project Asmosis provides a set of tools related to assembly language programming. The tools include: - the Asm::X86 Perl module, - AsmDoc - an HTML documentation generator for assembly language, - Asm4Doxy - Assembly converter for Doxygen (http://www.doxygen.org/), - converters between various assembly language dialects: NASM (The Netwide Assembler, https://www.nasm.us), fasm (flat assembler, https://flatassembler.net) and GNU as, - converters from C/C++ header files to assembly... -
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Neural Tangents
Fast and Easy Infinite Neural Networks in Python
Neural Tangents is a high-level neural network API for specifying complex, hierarchical models at both finite and infinite width, built in Python on top of JAX and XLA. It lets researchers define architectures from familiar building blocks—convolutions, pooling, residual connections, and nonlinearities—and obtain not only the finite network but also the corresponding Gaussian Process (GP) kernel of its infinite-width limit. With a single specification, you can compute NNGP and NTK kernels,... -
21
LMAX Disruptor
High performance inter-thread messaging library
LMAX aims to be the fastest trading platform in the world. Clearly, in order to achieve this we needed to do something special to achieve very low-latency and high-throughput with our Java platform. Performance testing showed that using queues to pass data between stages of the system was introducing latency, so we focused on optimising this area. The Disruptor is the result of our research and testing. We found that cache misses at the CPU-level, and locks requiring kernel arbitration are... -
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Plymouth Themes
A huge collection (80+) of Plymouth themes ported from Android
A big collection of Plymouth themes, ported from Android bootanimation. Plymouth is a project from Fedora and now listed among the freedesktop.org's official resources providing a flicker-free graphical boot process. It relies on kernel mode setting (KMS) to set the native resolution of the display as early as possible, then provides an eye-candy splash screen leading all the way up to the login manager. -
23
Periph
Peripherals I/O in Go
periph is a Go library that unifies hardware I/O on single-board computers and embedded Linux devices, exposing clean interfaces for GPIO, I²C, SPI, UART, PWM, and more. Its philosophy is “no daemon, no codegen”—you link a Go package and speak directly to the hardware via stable abstractions, keeping deployments simple and auditable. The project auto-detects host capabilities at runtime and selects the best driver backend, smoothing over kernel and board differences across Raspberry Pi,... -
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PowerShell Suite
My musings with PowerShell
PowerShell-Suite is a curated collection of PowerShell utility scripts and modules created to provide low-level Windows API access, process manipulation, debugging detection, security operations, and post-exploitation techniques directly from PowerShell. The project is licensed under BSD-3-Clause. Among its components, there are scripts like Invoke-Runas (to launch processes under alternate credentials via CreateProcessWithLogonW), Invoke-CreateProcess (to spawn processes with fine control over flags, window state, etc.), Detect-Debug (to detect kernel or user mode debugging environments), Get-Handles (to enumerate handles in a process via NtQuerySystemInformation), Get-TokenPrivs (to inspect privileges on process tokens), Get-Exports (to parse DLL exports without loading DLLs), Masquerade-PEB (to alter the PEB of a process to appear as a different process), and UAC-TokenMagic (a method to bypass UAC via token manipulation). -
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Minkowski Engine
Auto-diff neural network library for high-dimensional sparse tensors
The Minkowski Engine is an auto-differentiation library for sparse tensors. It supports all standard neural network layers such as convolution, pooling, unspooling, and broadcasting operations for sparse tensors. The Minkowski Engine supports various functions that can be built on a sparse tensor. We list a few popular network architectures and applications here. To run the examples, please install the package and run the command in the package root directory. Compressing a neural network to...
