Search Results for "gpu hardware"
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Showing 8 open source projects for "gpu hardware"
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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. ... -
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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).... -
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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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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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KEMP
A FDTD solver for electromagnetic wave simulations on a GPU cluster
KEMP is a fast FDTD solver on a GPU-based cluster. The FDTD (Finite-Difference Time-Domain) method is a popular numerical method for electromagnetic field simulations. KEMP enables hardware accelerations suitable for multi-GPU, multi-core CPU and GPU cluster. KEMP also provide easy configuration by using Python scripting language. -
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Rozkład temperatury w pomieszczeniach
Symulacja procesów cieplnych zachodzących w pomieszczeniach
Program tworzony w ramach przedmiotu "Projekt Grupowy" na Politechnice Gdańskiej. Skład: inż. Adam Banaś inż. Maciej Gajdzica inż. Adam Lasota inż. Damian Pawlus inż. Włodzimierz Kaoka Opiekun projektu: mgr inż. Piotr Fiertek Celem projektu jest stworzenie środowiska symulacyjnego dla procesów termicznych zachodzących w pomieszczeniach. Integralną jego częścią jest implementacja algorytmów obliczeniowych na procesorach graficznych GPU przy użyciu standardów CUDA... -
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The GWO library is numerical calculation library for the diffraction integrals using a GPU (Graphics Processing Unit). If optics engineers and researchers have no knowledge of GPU, the GWO library provides them with the GPU calculation power easily.
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