427 Open source projects that are alternatives of or similar to PyTorchTOP

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monolish: MONOlithic LInear equation Solvers for Highly-parallel architecture

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An ultra-fast, GPU-based large graph embedding algorithm utilizing a novel coarsening algorithm requiring not more than a single GPU.

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TouchDesigner components

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geometry processing and shape analysis framework

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Collective Knowledge extension with unified and customizable benchmarks (with extensible JSON meta information) to be easily integrated with customizable and portable Collective Knowledge workflows. You can easily compile and run these benchmarks using different compilers, environments, hardware and OS (Linux, MacOS, Windows, Android). More info:

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Raymarching shader toolkit for TouchDesigner

Project files associated with http://github.com/dbraun/PhaserCHOP and David Braun's "Quantitative Easing" talk at the 2019 TouchDesigner Summit https://www.youtube.com/watch?v=S4PQW4f34c8

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JetScan : GPU accelerated portable RGB-D reconstruction system

Implementation of A Random Finite Set Approach for Dynamic Occupancy Grid Maps with Real-Time Application

Just messing around with PyTorch 1.0's JIT compiler and their new C++ API Libtorch.

Simple tool to calculate sha256 on GPU using Cuda

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PostEffect Shaders(GLSL) for TouchDesigner

GPU-accelerated N-Body particle simulator with visualizer.

Implementation of Cuda to OpenGL rendering

Code accompanying my blog post on k-means in Python, C++ and CUDA

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Support Yolov5(4.0)/Yolov5(5.0)/YoloR/YoloX/Yolov4/Yolov3/CenterNet/CenterFace/RetinaFace/Classify/Unet. use darknet/libtorch/pytorch/mxnet to onnx to tensorrt

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No description or website provided.

An open-source solver tool for the Maxwell-Bloch equations.

Target-dependent sentiment classification in news articles reporting on political events. Includes a high-quality data set of over 11k sentences and a state-of-the-art classification model.

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Crowdsourcing video experiments (such as collaborative benchmarking and optimization of DNN algorithms) using Collective Knowledge Framework across diverse Android devices provided by volunteers. Results are continuously aggregated in the open repository:

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