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Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learn...
The fastest and most memory efficient lattice Boltzmann CFD software, running on all GPUs and CPUs via OpenCL. Free for non-commercial use.
Python framework for creating, editing, and running Noisy Intermediate-Scale Quantum (NISQ) circuits.
Code for running RFdiffusion
For running psychology and neuroscience experiments
GPGPU-Sim provides a detailed simulation model of contemporary NVIDIA GPUs running CUDA and/or OpenCL workloads. It includes support for features such as TensorCores and CUDA Dynamic Parallelism as well as a performance visualization tool, AerialVisoin, and an integrated energy model, GPUWattch.
Shadow is a discrete-event network simulator that directly executes real application code, enabling you to simulate distributed systems with thousands of network-connected processes in realistic and scalable private network experiments using your laptop, desktop, or server running Linux.
A GPU-accelerated computing library for running physics simulations and other GPGPU computations in a web browser.