DEEPSEEK
NVIDIA RAPIDS 25.08 Enhances Data Science with New Profiling Tools and Algorithm Support
NVIDIA's RAPIDS 25.08 release introduces new profiling tools for cuML, updates to the Polars GPU engine, and additional algorithm support, enhancing data science accessibility and scalability.
RAPIDS Introduces GPU Polars Streaming and Unified GNN API Enhancements
NVIDIA's RAPIDS suite version 25.06 unveils new features including GPU Polars streaming, a unified GNN API, and zero-code ML speedups, enhancing Python data science capabilities.
NVIDIA's RAPIDS-singlecell Revolutionizes Billion-Cell Data Analysis in Biology
NVIDIA's RAPIDS-singlecell tool addresses data size and analysis speed challenges in single-cell biology, revolutionizing research with GPU acceleration for billion-cell data sets.
NVIDIA RAPIDS Enhances Machine Learning with Zero-Code Acceleration and Performance Gains
NVIDIA's RAPIDS introduces zero-code acceleration for machine learning, boosts IO performance, and supports out-of-core XGBoost training, streamlining data science workflows.
NVIDIA's RAPIDS cuDF Enhances pandas Through Unified Virtual Memory
NVIDIA's RAPIDS cuDF utilizes Unified Virtual Memory to boost pandas' performance by 50x, offering seamless integration with existing workflows and GPU acceleration.
Enhancing Data Deduplication with RAPIDS cuDF: A GPU-Driven Approach
Explore how NVIDIA's RAPIDS cuDF optimizes deduplication in pandas, offering GPU acceleration for enhanced performance and efficiency in data processing.
Optimizing Multi-GPU Data Analysis with RAPIDS and Dask
Explore best practices for leveraging RAPIDS and Dask in multi-GPU data analysis, addressing memory management, computing efficiency, and accelerated networking.
Accelerating Causal Inference with NVIDIA RAPIDS and cuML
Discover how NVIDIA RAPIDS and cuML enhance causal inference by leveraging GPU acceleration for large datasets, offering significant speed improvements over traditional CPU-based methods.
NVIDIA RAPIDS 24.10 Enhances NetworkX and Polars with GPU Acceleration
NVIDIA RAPIDS 24.10 introduces GPU-accelerated NetworkX and Polars with zero code changes, enhancing compatibility with Python 3.12 and NumPy 2.x for improved data processing.
Enhanced UMAP Performance on GPUs with RAPIDS cuML
RAPIDS cuML introduces a faster, scalable UMAP implementation using GPU acceleration, addressing challenges in large dataset processing with new algorithms for improved performance.