Search Results for "kernel virtual machine"
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Showing 33 open source projects for "kernel virtual machine"
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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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Cosmopolitan
Build-once run-anywhere c library
Cosmopolitan Libc makes C a build-once run-anywhere language, like Java, except it doesn't need an interpreter or virtual machine. Instead, it reconfigures stock GCC and Clang to output a POSIX-approved polyglot format that runs natively on Linux + Mac + Windows + FreeBSD + OpenBSD + NetBSD + BIOS with the best possible performance and the tiniest footprint imaginable. Cosmopolitan can be compiled from source on any Linux distro. GNU make needs to be installed beforehand. ... -
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Rasa
Open source machine learning framework to automate text conversations
...If you want to build it from the source, you have to install Poetry first. By default, Poetry will try to use the currently activated Python version to create the virtual environment for the current project automatically. -
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GoNB
GoNB, a Go Notebook Kernel for Jupyter
...See the tutorial. It's been heavily used by the author (in developing GoMLX, a machine learning framework for Go), but should still be seen as experimental — if we hear success stories from others, we can change this. -
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Otter-Grader
A Python and R autograding solution
...Otter supports local grading through parallel Docker containers, grading using the autograder platforms of 3rd party learning management systems (LMSs), the deployment of an Otter-managed grading virtual machine, and a client package that allows students to run public checks on their own machines. Otter is designed to grade Python scripts and Jupyter Notebooks, and is compatible with a few different LMSs, including Canvas and Gradescope. -
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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... -
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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,... -
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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... -
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CasADi
CasADi is a symbolic framework for numeric optimization
...CasADi's backbone is a symbolic framework implementing forward and reverse modes of AD on expression graphs to construct gradients, large-and-sparse Jacobians, and Hessians. These expression graphs, encapsulated in Function objects, can be evaluated in a virtual machine or exported to stand-alone C code. Initial value problems in ordinary or differential-algebraic equations (ODE/DAE) can be calculated using explicit or implicit Runge-Kutta methods or interfaces to IDAS/CVODES from the SUNDIALS suite. Derivatives are calculated using sensitivity equations, up to arbitrary order. -
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DeepPavlov
A library for deep learning end-to-end dialog systems and chatbots
DeepPavlov makes it easy for beginners and experts to create dialogue systems. The best place to start is with user-friendly tutorials. They provide quick and convenient introduction on how to use DeepPavlov with complete, end-to-end examples. No installation needed. Guides explain the concepts and components of DeepPavlov. Follow step-by-step instructions to install, configure and extend DeepPavlov framework for your use case. DeepPavlov is an open-source framework for chatbots and virtual... -
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Amazon Chime SDK for iOS
An iOS client library for integrating multi-party communications
The Amazon Chime SDK for iOS makes it easy to add collaborative audio calling, video calling, and screen share viewing features to iOS applications by using the same infrastructure services that power meetings on the Amazon Chime service. This Amazon Chime SDK for iOS works by connecting to meeting session resources that you have created in your AWS account. The SDK has everything you need to build custom calling and collaboration experiences in your iOS application, including methods to:... -
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PyQuil
A Python library for quantum programming using Quil
PyQuil is a Python library for quantum programming using Quil, the quantum instruction language developed at Rigetti Computing. PyQuil serves three main functions. PyQuil has a ton of other features, which you can learn more about in the docs. However, you can also keep reading below to get started with running your first quantum program. Without installing anything, you can quickly get started with quantum programming by exploring our interactive Jupyter Notebook tutorials and examples. To... -
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4tH compiler
A friendly Forth compiler with a little difference
...It supports about 95% of the ANS Forth CORE wordset and features conditional compilation, pipes, files, assertions, forward declarations, enumerations, structures, suspended execution, recursion, include files, etc. It comes with an RPN calculator, BASIC interpreter, line editor, preprocessor, compiler, decompiler, C-source generator, a virtual machine, and a multitasking environment. -
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BAScript
Scripting engine for Pascal compilers.
BAScript is a simple scripting engine written in Object Pascal you can use to add scripting to your Delphi, Lazarus or Free Pascal applications ("host program") to extend their functionality without the need of recompiling them. The virtual machine defines its own language, called the BAScript language. It is a low-level language, somewhat similar to the Assembler language, which is not intended to be easy to program but easy to execute. So it is recommendable to use other higher level languages and translate them into BAScript language. Package includes two compilers that translates from a higher-level language to the BAScript language. ... -
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Wheefun Graphics Library
Portable Graphics Primitives
...WFGFX at its core provides interfaces for manipulating both raster and vector images through an abstract graphics context; in many cases, several low-level primitives exist for more direct manipulation. It is designed to be easily ported to other programming environments like .NET and the Java Virtual Machine, making the codebase reusable as a result. -
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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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WFEF .NET Bindings
.NET bindings for the WFEF project.
Home Browse Open Source WFIO .NET Bindings WFIO .NET Bindings .NET bindings for WFIO Status: Pre-Alpha Brought to you by: thylordroot Add a Review Downloads: 0 This Week Last Update: 2023-01-25 Browse Code Get Updates Share This Windows Mac Linux BSD ChromeOS Summary Reviews Support Code This subproject contains a parallel implementation effort for the .NET Virtual Machine. It allows for you to use the WFEF interface in your .NET applications and will include a translation layer so that you can talk to the native WFEF libraries. This subproject exists partially to overcome the 8.3 file naming convention that WFEF itself is limited to. -
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Flashlight library
A C++ standalone library for machine learning
Flashlight is a fast, flexible machine learning library written entirely in C++ by Facebook AI Research and the creators of Torch, TensorFlow, Eigen, and Deep Speech. Native support in C++ and simple extensibility make Flashlight a powerful research framework that's hackable to its core and enables fast iteration on new experimental setups and algorithms with little unopinionated and without sacrificing performance. In a single repository, Flashlight provides apps for research across... -
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WFIO Java Bindings
Java bindings for WFIO
This subproject contains a parallel implementation effort for the Java Virtual Machine. It allows for you to use the WFIO interface in your Java applications and will include a translation layer so that you can talk to the native WFIO libraries. This subproject exists partially to overcome the 8.3 file naming convention that WFIO itself is limited to. -
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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... -
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SageMaker MXNet Training Toolkit
Toolkit for running MXNet training scripts on SageMaker
SageMaker MXNet Training Toolkit is an open-source library for using MXNet to train models on Amazon SageMaker. For inference, see SageMaker MXNet Inference Toolkit. For the Dockerfiles used for building SageMaker MXNet Containers, see AWS Deep Learning Containers. For information on running MXNet jobs on Amazon SageMaker, please refer to the SageMaker Python SDK documentation. With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow.... -
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ocapi
C-level driver collection for MSP430 and derivatives
...So it should work, no matter if you live in the Windows, Linux or Mac world. ocapi is used as the hardware abstraction layer for the MSP430 port of the Takatuka Java virtual machine (JVM). Before it can be used, the library must be built from the sources provided here. The build environment allows for fine grained configuration of the library's functionality and target system. -
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ZM
A library to handle coroutine and green thread in C
ZM is a C library to handle continuations (coroutine, exception, green thread) with finite state machines. The library is written in C99 without external dependecy or machine-specific code and can be compiled in ansi-c or ansi-c++ with the minal effort to define two unsigned int type (uint8_t and uint32_t). -
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This project consists of a linux kernel driver and some user-mode libraries. They allow a process to create a virtual usb host controller. Real or virtual usb devices can be "plugged" into this controller.
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Functional, Data Science Intro To Python
[tutorial]A functional, Data Science focused introduction to Python
The first section is an intentionally brief, functional, data science-centric introduction to Python. The assumption is a someone with zero experience in programming can follow this tutorial and learn Python with the smallest amount of information possible. The sections after that, involve varying levels of difficulty and cover topics as diverse as Machine Learning, Linear Optimization, build systems, command line tools, recommendation engines, Sentiment Analysis and Cloud Computing.
