{"repo":"CannyLab/tsne-cuda","free":true,"listed":false,"github":"https://github.com/CannyLab/tsne-cuda","clone":"git clone https://github.com/CannyLab/tsne-cuda.git","description":"GPU Accelerated t-SNE for CUDA with Python bindings","language":"Cuda","stars":1953,"topics":["cuda","gpu","mnist","tsne","tsne-algorithm","data-visualization","data-analysis","barnes-hut","barnes-hut-tsne","fit-tsne"],"license":"BSD-3-Clause","category":"analytics","readme_excerpt":"TSNE-CUDA This repo is an optimized CUDA version of FIt-SNE algorithm with associated python modules. We find that our implementation of t-SNE can be up to 1200x faster than Sklearn, or up to 50x faster than Multicore-TSNE when used with the right GPU. The paper describing our approach, as well as the results below, is available at https://arxiv.org/abs/1807.11824. You can install binaries with anaconda for CUDA version 10.1 and 10.2 using conda install tsnecuda -c conda-forge . Tsnecuda supports CUDA versions 9.0 and later through source installation, check out the wiki for up to date installation instructions. https://github.com/CannyLab/tsne-cuda/wiki/ Benchmarks Simulated Data Time taken compared to other state of the art algorithms on synthetic datasets with 50 dimensions and four clusters for varying numbers of points. Note the log scale on both the points and time axis, and that the scale of the x-axis is in thousands of points (thus, the values on the x-axis range from 1K to 10M points. Dashed lines on SkLearn, BH-TSNE, and MULTICORE-4 represent projected times. Projected scaling assumes an O(nlog(n)) implementation. MNIST The performance of t-SNE-CUDA compared to other state-of-the-art implementations on the MNIST dataset. t-SNE-CUDA runs on the raw pixels of the MNIST dataset (60000 images x 768 dimensions) in under 7 seconds. CIFAR The performance of t-SNE-CUDA compared to other state-of-the-art implementations on the CIFAR-10 dataset. t-SNE-CUDA runs on the output","default_branch":null,"files":null,"tree":[],"storefront":"/r/CannyLab","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/CannyLab/tsne-cuda/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}