Search Results for "kernel-ntfs"
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21 projects for "kernel-ntfs" with 2 filters applied:
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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
...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. ... -
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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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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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Multik
Multidimensional array library for Kotlin
Multidimensional array library for Kotlin. -
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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 efficiently manage memory during decoding. ... -
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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 the current project, and other projects that wish to use MKL for FFTs should also set that same preference. ... -
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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... -
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Asmosis
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 language header files, - make4fasm - a Makefile generator for fasm, - Linux-2.6 kernel module helpers for fasm and NASM, - macros for Autoconf (https://www.gnu.org/software/autoconf/), - pieces of code that may be useful for starting developing a simple operating system. See the project homepage https://asmosis.sourceforge.io and the project Wiki in the menu above. -
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Neural Tangents
Fast and Easy Infinite Neural Networks in Python
Kernel evaluation is highly optimized for speed and memory, and computations can be automatically distributed across accelerators with near-linear scaling. -
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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. -
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Periph
Peripherals I/O in Go
...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, BeagleBone, and other platforms. A large set of device drivers (sensors, displays, LED controllers, storage, RTCs) give you batteries-included building blocks for prototypes and production systems. Command-line tools like periph-info help verify wiring, enumerate buses, and inspect capabilities before you ship. ... -
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BeaEngine 5
BeaEngine disasm project
...You can use it in C/C++ (usable and compilable with Visual Studio, GCC, MinGW, DigitalMars, BorlandC, WatcomC, SunForte, Pelles C, LCC), in assembler (usable with masm32 and masm64, nasm, fasm, GoAsm) in C#, in Python3, in Delphi, in PureBasic and in WinDev. You can use it in user mode and kernel mode. -
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ViennaCL
Linear algebra and solver library using CUDA, OpenCL, and OpenMP
ViennaCL provides high level C++ interfaces for linear algebra routines on CPUs and GPUs using CUDA, OpenCL, and OpenMP. The focus is on generic implementations of iterative solvers often used for large linear systems and simple integration into existing projects. -
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libVMR
VMR - machine learning library
...The library is intended for users, with machine learning skills. libVMR provides an effective framework for the research and development of data mining and predictive analytics. libVMR is based on the most popular neural network model with a higher generalization ability from kernel tricks - vector machine by Reshetov (VMR). The library has been designed to learn from data sets. Typical applications here are pattern recognition ( binary classification). -
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PhotoJShop
Photo editing JavaScript library
PhotoJShop is a JavaScript library for photo editing using the canvas and kernel convolution matrixes, aiming to reproduce the most usual filters. A demo of its capabilities can be seen in Nuophoto, a project that uses this library for all the editing. The idea is to provide a simple library to developers that will allow quick integration of photo filters to their website. After including jQuery, include photojshop.jquery.js. -
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Universal PHP Framework. toKernel is a fully Object-Oriented extensible framework. By design, the framework's kernel is monolithic which brings a lot of advantages. It is NOT a loader for a mere collection of classes.
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CLara is a framework that enables you to access the computing power of many graphics processors in an IP-based network using a kind of Client/Proxy/Server model. Its programming interface conforms to the OpenCL 1.0 standard.
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