Search Results for "onnxruntime-gpu"
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Showing 84 open source projects for "onnxruntime-gpu"
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Newton
An open-source, GPU-accelerated physics simulation engine
Newton is a high-performance, GPU-accelerated physics simulation engine designed primarily for robotics research, machine learning, and advanced simulation workflows. Built on top of NVIDIA Warp, it leverages GPU parallelism to deliver scalable and efficient simulation environments that support rapid iteration and experimentation. The engine extends previous simulation frameworks by introducing differentiable physics capabilities, allowing it to integrate seamlessly with machine learning models and optimization pipelines. ... -
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NumPy
The fundamental package for scientific computing with Python
...NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries. The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code. NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level. Distributed under a liberal BSD license, NumPy is developed and maintained publicly on GitHub by a vibrant, responsive, and diverse community. ... -
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NVIDIA Isaac Sim
NVIDIA Isaac Sim is an open-source application on NVIDIA Omniverse
NVIDIA Isaac Sim is a high-fidelity robotics simulation platform built on NVIDIA Omniverse to develop, test, and validate AI-driven robots in physically accurate virtual environments. It supports a wide array of robotics formats (URDF, MJCF, CAD), includes GPU-accelerated physics, and features immersive RTX rendering and multisensory simulation. Realistic physics via GPU-accelerated engines and RTX ray tracing. Multi-sensor simulation (RGB-D cameras, Lidar, Radar, IMU, contact sensors). Extensible via platform APIs and can integrate into custom USD-based simulators. -
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CUDA-Q
C++ and Python support for the CUDA Quantum programming model
...It provides a full toolchain that includes compilers, runtimes, and libraries for writing quantum programs in both C++ and Python. The platform is designed to be hardware-agnostic, allowing developers to run applications on different quantum backends or simulate them efficiently using GPU acceleration when physical quantum hardware is unavailable. It enables complex workflows where classical and quantum computations are tightly integrated, supporting advanced research and real-world applications in quantum computing. The repository includes components such as the nvq++ compiler and runtime systems that manage execution across heterogeneous environments. -
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NVIDIA Isaac Lab
Unified framework for robot learning built on NVIDIA Isaac Sim
Isaac Lab is an open-source modular robotics learning framework built atop Isaac Sim. It simplifies research workflows across reinforcement learning, imitation learning, and motion planning by offering robust, GPU-accelerated simulation with realistic sensor and physics fidelity—ideal for sim-to-real robot training. Compatible and optimized for use with Isaac Sim versions (e.g., Sim 5.0 and 4.5). GPU-accelerated, high-fidelity physics and sensor simulation suitable for complex learning tasks. Offers a variety of robotic environment simulations on both Linux and Windows. -
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COLMAP
Structure-from-Motion and Multi-View Stereo
COLMAP is a general-purpose Structure-from-Motion (SfM) and Multi-View Stereo (MVS) pipeline with a graphical and command-line interface. It offers a wide range of features for the reconstruction of ordered and unordered image collections. The software is licensed under the new BSD license. -
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FairChem
FAIR Chemistry's library of machine learning methods for chemistry
...Tasks span heterogeneous domains—catalysis (OC20-style), inorganic materials (OMat), molecules (OMol), MOFs (ODAC), and molecular crystals (OMC)—allowing one model family to serve many simulations. The README provides quick paths for pulling models (e.g., via Hugging Face access), then running energy/force predictions on GPU or CPU. -
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Qulacs
Variational Quantum Circuit Simulator for Quantum Computation Research
Variational Quantum Circuit Simulator for Quantum Computation Research. Qulacs is a Python/C++ library for fast simulation of large, noisy, or parametric quantum circuits. Qulacs is developed at QunaSys, Osaka University, NTT, and Fujitsu. -
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Brax
Massively parallel rigidbody physics simulation
Brax is a fast and fully differentiable physics engine for large-scale rigid body simulations, built on JAX. It is designed for research in reinforcement learning and robotics, enabling efficient simulations and gradient-based optimization. -
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CUDA-QX
Accelerated libraries for quantum-classical computing built on CUDA-Q
CUDA-QX is a collection of accelerated libraries built on top of the CUDA-Q platform, designed to enable rapid development of hybrid quantum-classical applications. It extends the CUDA-Q programming model by providing optimized implementations of domain-specific quantum computing primitives and workflows. The libraries are intended to help researchers and developers leverage GPUs, CPUs, and quantum processing units together in a unified computational model. CUDA-QX focuses on key areas such... -
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PyTorch Geometric
Geometric deep learning extension library for PyTorch
...We have outsourced a lot of functionality of PyTorch Geometric to other packages, which needs to be additionally installed. These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. We do not recommend installation as root user on your system python. Please setup an Anaconda/Miniconda environment or create a Docker image. We provide pip wheels for all major OS/PyTorch/CUDA combinations. -
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PyTorch Geometric Temporal
Spatiotemporal Signal Processing with Neural Machine Learning Models
...Moreover, it comes with an easy-to-use dataset loader, train-test splitter and temporal snaphot iterator for dynamic and temporal graphs. The framework naturally provides GPU support. It also comes with a number of benchmark datasets from the epidemiological forecasting, sharing economy, energy production and web traffic management domains. Finally, you can also create your own datasets. The package interfaces well with Pytorch Lightning which allows training on CPUs, single and multiple GPUs out-of-the-box. ... -
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JAX
Composable transformations of Python+NumPy programs
With its updated version of Autograd, JAX can automatically differentiate native Python and NumPy functions. It can differentiate through loops, branches, recursion, and closures, and it can take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation) via grad as well as forward-mode differentiation, and the two can be composed arbitrarily to any order. What’s new is that JAX uses XLA to compile and run your NumPy programs on GPUs and... -
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TorchQuantum
A PyTorch-based framework for Quantum Classical Simulation
...Researchers on quantum algorithm design, parameterized quantum circuit training, quantum optimal control, quantum machine learning, and quantum neural networks. Dynamic computation graph, automatic gradient computation, fast GPU support, batch model terrorized processing. -
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Monte Carlo eXtreme (MCX)
Physically accurate and validated GPU ray-tracer
MCX is a GPU-accelerated, general-purpose, physically-accurate and feature-rich 3-D light transport simulator. It is one of the fastest simulators because it can use tens of thousands of GPU threads to simulate photons in parallel. -
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gVirtualXRay
Virtual X-Ray Imaging Library on GPU
...It is based on the Beer-Lambert law to compute the absorption of light (i.e. photons) by 3D objects (here polygon meshes). It is implemented on the graphics processing unit (GPU) using the OpenGL Shading Language (GLSL). SimpleGVXR is a smaller library build on the top of gVirtualXRay. It provides wrappers to Python, R, Ruby, Tcl, C#, Java, and GNU Octave. -
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Bandicoot
fast C++ library for GPU linear algebra & scientific computing
* Fast GPU linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use * Provides high-level syntax and functionality deliberately similar to Matlab * Provides an API that is aiming to be compatible with Armadillo for easy transition between CPU and GPU linear algebra code * Useful for algorithm development directly in C++, or quick conversion of research code into production environments * Distributed under the permissive Apache 2.0 license, useful for both open-source and proprietary (closed-source) software * Can be used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc * Downloads: http://coot.sourceforge.io/download.html * Documentation: http://coot.sourceforge.io/docs.html * Bug reports: http://coot.sourceforge.io/faq.html * Git repo: https://gitlab.com/conradsnicta/bandicoot-code -
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TomoJ
ImageJ plugin to perform Electron Tomography
...TomoJ proposes the preprocessing and the registration of tilt-series prior to 3D reconstructions (WBP, ART, SIRT, OS-SART, compressed sensing). TomoJ is written in Java, the computations are multithreaded and reconstruction can be performed on CPU or GPU (OpenCL). registration is described in: Journal of Structural Biology: X. 2020, Volume 4. "Improvements on marker-free images alignment for electron tomography" C.O.S. Sorzano et al. https://doi.org/10.1016/j.yjsbx.2020.100037. BMC Bioinformatics. 2009 Apr 27;10:124."Marker-free image registration of electron tomography tilt-series." ... -
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FractalRenderingApp
Lightweight app for visualization of Mandelbrot and Julia set
Source code is available on https://github.com/MarkoLeskovar/FractalRenderingApp -
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DxTonia
A tool for detecting the presence of leg dystonia from videos.
...The software has been verified on two datasets and achieved higher accuracy than routine clinical care. Stay tuned for the improved version. Note: Currently only works on Windows PC with Nvidia GPU. Soon, mac and Linux CPU only version will be released. The requirment files are in old-version_scripts folder. Instructions to use DxTonia https://www.rishabh-bajpai.com/dxtoniainstallation https://www.medrxiv.org/content/10.1101/2024.10.15.24315574 -
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CIRT
CIRT - CUDA Interactive Ray Tracer
CIRT is an implementation of PRTP (Programmable Ray Tracing Pipeline). Mainly it is to be used as a ray-tracing equivalent of OpenGL. It allows the user to implement various ray-tracing related algorithms. -
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...Change-log for MathMod-11.1 (16/06/2021) 1) Support of graphing functions with complex numbers Z=u+iv in 3D and 4D spaces (demo scripts: "Complex3D_xx" and "Complex4D_Saddle") 2) Added support for HSV (hue, saturation, brightness) coloring model (script: "Complex_Domain_Coloring") 3) Texture definitions (RGB and HSV) for parametric surfaces can now be expressed as functions of complex numbers 4) Added a software implementation for the OpenGL variable gl_FrontFacing (fixed an issue with GPU drivers on MacOSX Catalina). The activation of this patch is available from mathmodconfig.js ("OpenGlConfig"-->"GL_FrontFacingSupport"=false) or the GUI("Appearance"-->"OpenGL Front Surface Support") 5) Bug-fixes, code optimization and documentation update.
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octave-ocl
OpenCL support for GNU Octave
The Package is installable in GNU Octave and offers OpenCL support for parallelization of numerical computations. It is most effective for computations which are based on large vectors or n-dimensional arrays of numbers, and mostly (but not limited to) identical element-wise operations. The user can select which available OpenCL hardware and drivers are to be used. The Package offers new numeric data types with many built-in operations (e.g., overloaded operators). It is flexibly... -
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NeedLR
Welcome to NeedLR, a scientific tool for pointcloud annotation.
Welcome to NeedLR, a specialized tool for Needle-like precision in Labeling and Rendering point cloud data. NeedLR offers an intuitive interface for detailed annotation and visualization of pointcloud data, perfect for academic research, ecological studies, and forestry management. The application leverages advanced algorithms to efficiently process and annotate large-scale point cloud data, ensuring high accuracy and ease of use. To use NeedLR: Download and unzip the file and run the... -
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Parallel and Distributed Process System
OmniSim simulates parallel and distributed processing systems
Parallel and Distributed Process OmniSim Computational Neuroscience: Large-scale neural population dynamics, brain-inspired computing architectures, and neuro-symbolic AI systems 🧬 Scientific Overview PDP-OmniSim is an advanced computational framework for simulating parallel and distributed processing systems, with cutting-edge applications in computational neuroscience, distributed computing, and complex systems modeling. The framework provides researchers with robust tools for...
