CV-CUDA™ is an open-source, GPU accelerated library for cloud-scale image processing and computer vision.
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検索結果: cuda-kernels
英語版ディレクトリAI 基础知识 - GPU 架构、CUDA 编程、大模型基础及AI Agent 相关知识。
A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends
Self-host the powerful Chatterbox TTS model. This server offers a user-friendly Web UI, flexible API endpoints (incl. OpenAI compatible), predefined voices, voice cloning, and large audiobook-scale text processing. Runs accelerated on NVIDIA (CUDA), AMD (ROCm), and CPU.
A hardware-aware Codex/WorkBuddy skill that automates local MiniMax H3 video generation through ComfyUI, handling model selection, installation, and low-VRAM configuration.
Solve puzzles. Learn CUDA.
Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
Jupyter magics and kernels for working with remote Spark clusters
PopSift is an implementation of the SIFT algorithm in CUDA.
GPU Accelerated t-SNE for CUDA with Python bindings
cuFOLIO is a GPU-accelerated portfolio optimization toolkit for building, backtesting, and scaling modern investment workflows with NVIDIA cuOpt and CUDA-X Data Science.