Search Results for "kernel-ntfs"
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175 projects for "kernel-ntfs" with 1 filter applied:
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Kernel Memory
Research project. A Memory solution for users, teams, and applications
Kernel Memory is an open-source reference architecture developed by Microsoft to help developers build memory systems for AI applications powered by large language models. The project focuses on enabling applications to store, index, and retrieve information so that AI systems can incorporate external knowledge when generating responses. -
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Moss
Rust Linux-compatible kernel
Moss Kernel is an open-source operating system kernel project designed to explore modern OS design and provide a foundation for experimental system research and development. Rather than replicating traditional monolithic kernels exactly, it emphasizes modularity, safety, and simplicity by incorporating well-structured subsystems for memory management, scheduling, and device abstraction that are easy for contributors to understand and extend. -
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SerenityOS
The Serenity Operating System
SerenityOS is an open source Unix-like operating system project with its own custom kernel, graphical user interface, system libraries, and userland tools. It combines a nostalgic “90s UI aesthetic” with modern system capabilities: a preemptive, multi-threaded kernel, own browsers, network stack, file systems, IPC, security features, and a suite of graphical / developer applications. The project is both a hobbyist OS and a polished engineering sandbox. -
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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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tt-metal
TT-NN operator library, and TT-Metalium low level kernel programming
tt-metal, also referred to in its documentation as TT-Metalium, is Tenstorrent’s low-level software development kit for programming applications on Tenstorrent AI accelerators. The project is designed for developers who need direct access to the company’s Tensix processor architecture, exposing a programming model that is closer to hardware control than high-level inference frameworks. Instead of following a traditional GPU model centered on massive thread parallelism, the platform is built... -
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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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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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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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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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DeepGEMM
Clean and efficient FP8 GEMM kernels with fine-grained scaling
DeepGEMM is a specialized CUDA library for efficient, high-performance general matrix multiplication (GEMM) operations, with particular focus on low-precision formats such as FP8 (and experimental support for BF16). The library is designed to work cleanly and simply, avoiding overly templated or heavily abstracted code, while still delivering performance that rivals expert-tuned libraries. It supports both standard and “grouped” GEMMs, which is useful for architectures like Mixture of... -
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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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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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os-tutorial
How to create an OS from scratch
os-tutorial is an open source educational project by cfenollosa that teaches the basics of building an operating system from scratch. The repository provides step-by-step lessons starting with bootloaders and moving through kernel development, interrupts, memory management, and system calls. Each tutorial is accompanied by clear explanations, code examples, and references to deepen understanding. The project uses x86 assembly and C to illustrate concepts, making it accessible to students and hobbyists interested in low-level programming. By compiling and running the examples with tools like QEMU, learners gain hands-on experience with OS fundamentals. ... -
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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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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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Inspektor Gadget
The eBPF tool and systems inspection framework for Kubernetes
...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. -
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CUDA Agent
Large-Scale Agentic RL for High-Performance CUDA Kernel Generation
CUDA Agent is a research-driven agentic reinforcement learning system designed to automatically generate and optimize high-performance CUDA kernels for GPU workloads. The project addresses the long-standing challenge that efficient CUDA programming typically requires deep hardware expertise by training an autonomous coding agent capable of iterative improvement through execution feedback. Its architecture combines large-scale data synthesis, a skill-augmented CUDA development environment,... -
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Multik
Multidimensional array library for Kotlin
Multidimensional array library for Kotlin. -
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ANE Training
Training neural networks on Apple Neural Engine via APIs
...It explores the internal software stack of the Apple Neural Engine by interfacing with private classes such as _ANEClient and compiling custom compute graphs in the MIL format. The project includes performance benchmarks and kernel breakdowns that show how different components of the training loop are distributed between the ANE and CPU. It is primarily intended as a research and educational proof of concept rather than a production library, highlighting what is technically possible with undocumented hardware access. -
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DeepSeek-V3.2-Exp
An experimental version of DeepSeek model
DeepSeek-V3.2-Exp is an experimental release of the DeepSeek model family, intended as a stepping stone toward the next generation architecture. The key innovation in this version is DeepSeek Sparse Attention (DSA), a sparse attention mechanism that aims to optimize training and inference efficiency in long-context settings without degrading output quality. According to the authors, they aligned the training setup of V3.2-Exp with V3.1-Terminus so that benchmark results remain largely... -
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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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Symfony FrameworkBundle
Provides a tight integration between Symfony components
Symfony Framework Bundle is the core bundle of the Symfony PHP framework, providing the essential components and configuration needed to build robust web applications. It integrates various Symfony components, such as routing, templating, and dependency injection, into a cohesive structure. This bundle serves as the foundation for Symfony applications and enables developers to efficiently manage routes, templates, services, and more. -
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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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polynote
A better notebook for Scala (and more)
...Designed to address shortcomings in classic notebook solutions, it blends features familiar from IDEs — such as smart autocomplete, parameter hints, and better runtime insights — with the flexibility of notebook workflows, enhancing both developer productivity and data exploration. Unlike many notebook environments that are tied to a single language kernel, Polynote tracks and manages state consistently across cells based on execution order and cell dependencies, which reduces hidden state and makes notebooks more reproducible and understandable.
