Browsing: GPU acceleration

GPU-accelerated Polars DataFrames improve the efficiency of XGBoost model training by introducing features such as category re-coding to optimize machine learning workflows. Polars DataFrames provide a powerful framework for handling large datasets, enabling faster data…

NVIDIA’s integration of cuVS with Faiss significantly boosts the efficiency of GPU-accelerated vector searches, providing faster index builds and reduced search latency. This development is particularly important for handling large datasets. The combination of cuVS…

NVIDIA’s GeForce RTX GPUs significantly improve creative workflows through the use of AI, GPU acceleration, and real-time rendering technology, as demonstrated at Adobe MAX. These advancements are designed to transform the content creation process, making…