1294 Open source projects that are alternatives of or similar to Popsift

High-performance Vision library in Python. Scale your research, not boilerplate.

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an implementation of parallel linear BVH (LBVH) on GPU

Examples of C# code compiled to GPU by hybridizer

[内测中]前向式Python环境快捷封装工具，快速将Python打包为EXE并添加CUDA、NoAVX等支持。

A library for high performance deep learning inference on NVIDIA GPUs.

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JCuda - Java bindings for CUDA

No description or website provided.

Simple physically based path tracer based on Nvidia's Optix Ray Tracing Engine

Dockerfiles for OpenCV compiled with CUDA, opencv_contrib modules and Python 3 bindings

PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer

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A structured light scanner

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gmonitor is a GPU monitor (Nvidia only at the moment)

Molecular dynamics and Monte Carlo soft matter simulation on GPUs.

An efficient C++17 GPU numerical computing library with Python-like syntax

Modified nVidia .inf files to run drivers on all video cards, research & telemetry free drivers

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JIT Compilation for Multiple Architectures: C++, OpenMP, CUDA, HIP, OpenCL, Metal

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GPU Fluid Simulation with Volumetric Rendering

Deep.Net machine learning framework for F#

A Python wrapper of NVIDIA Video Loader (NVVL) with CuPy for fast video loading with Python

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oneAPI Math Kernel Library (oneMKL) Interfaces

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Deep Learning library using GPU(CUDA/cuBLAS)

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A real time optical flow algorithm implemented on GPU

An open-source library of algorithms to analyse time series in GPU and CPU.

Single C file, Realtime CPU/GPU Profiler with Remote Web Viewer

Burstcoin C++ CPU and GPU Miner

QUDA is a library for performing calculations in lattice QCD on GPUs.

cuML - RAPIDS Machine Learning Library

ThunderSVM: A Fast SVM Library on GPUs and CPUs

SDK for GPU accelerated genome assembly and analysis

Automatic parallelization of Python/NumPy, C, and C++ codes on Linux and MacOSX

Robotics with GPU computing

A simple GPU hash table implemented in CUDA using lock free techniques

Data visualisation in Python based on OptiX 7.2 ray tracing framework.

Squeeze-and-Excitation Networks

Achieve peak performance on x86 CPUs and NVIDIA GPUs

Set up CUDA for machine learning (and gaming) on macOS using a NVIDIA eGPU

monolish: MONOlithic LInear equation Solvers for Highly-parallel architecture

A stream processing framework for high-throughput applications.

continuous energy monte carlo neutron transport in general geometries on GPUs

BriefMatch real-time GPU optical flow

Implementation of Macklin, Miles, and Matthias Müller. "Position based fluids.". Visual Studio 2015 + CUDA 8.0

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A domain-specific language and compiler for image processing