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rCUDA, which stands for Remote CUDA, is a type of middleware software framework for remote GPU virtualization. Fully compatible with the CUDA application programming interface , it allows the allocation of one or more CUDA-enabled GPUs to a single application. Each GPU can be part of a cluster or running inside of a virtual machine. The ...
GPU virtualization refers to technologies that allow the use of a GPU to accelerate graphics or GPGPU applications running on a virtual machine.GPU virtualization is used in various applications such as desktop virtualization, [1] cloud gaming [2] and computational science (e.g. hydrodynamics simulations).
CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3]
Quantum chemistry computer programs are used in computational chemistry to implement the methods of quantum chemistry.Most include the Hartree–Fock (HF) and some post-Hartree–Fock methods.
Within the CUDA ecosystem, Nvidia offers a tangential platform known as CUDA-Q that focuses specifically on quantum computing development. CUDA-Q is marketed as a "unified programming model."
List of free analog and digital electronic circuit simulators, available for Windows, macOS, Linux, and comparing against UC Berkeley SPICE.The following table is split into two groups based on whether it has a graphical visual interface or not.
In computing, CUDA (Compute Unified Device Architecture) is a proprietary [2] parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for accelerated general-purpose processing, an approach called general-purpose computing on GPUs.
Parallel Thread Execution (PTX or NVPTX [1]) is a low-level parallel thread execution virtual machine and instruction set architecture used in Nvidia's Compute Unified Device Architecture programming environment.