Zero to RAPIDS in Minutes with NVIDIA GPUs + Saturn Cloud
With RAPIDS, practitioners can quickly accelerate data science workloads on NVIDIA GPUs, and with Saturn Cloud focus on solving their business challenges.
Search Results for rapids
Limit Order Book Dataset Generation for Accelerated Short-Term Price Prediction with RAPIDS
Hardware acceleration using GPUs reduces the time required for financial ML researchers to obtain prediction results.
Accelerating Vector Search: Using GPU-Powered Indexes with RAPIDS RAFT
In the AI landscape of 2023, vector search is one of the hottest topics due to its applications in large language models (LLM) and generative AI. Semantic vector search enables a broad range of important tasks like detecting fraudulent transactions, recommending products to users, using contextual information to augment full-text searches, and finding actors that … Continued
Achieving 100x Faster Single-Cell Modality Prediction with NVIDIA RAPIDS cuML
Single-cell measurement technologies have advanced rapidly, revolutionizing the life sciences. We have scaled from measuring dozens to millions of cells and from one modality to multiple high dimensional modalities. The vast amounts of information at the level of individual cells present a great opportunity to train machine learning models to help us better understand the … Continued
An Interactive 2010 Census Plotly-dash Visualization Accelerated By RAPIDS
The COVID-19 pandemic brings the efforts of the data science community to the forefront. Real-time, interactive visualizations of the novel coronavirus’ spread across populations help researchers, scientists, health officials and governments understand, validate, and communicate important insights hidden among hundreds of millions of rows of records.
Accelerated Data Analytics: Speed Up Data Exploration with RAPIDS cuDF
This post is part of a series on accelerated data analytics. Digital advancements in climate modeling, healthcare, finance, and retail are generating unprecedented volumes and types of data. IDC says that by 2025, there will be 180 ZB of data compared to 64 ZB in 2020, scaling up the need for data analytics to turn … Continued
Accelerating ETL on KubeFlow with RAPIDS
Using RAPIDS on your KubeFlow cluster empowers you to GPU-accelerate your ETL work in both your interactive sessions and ETL pipelines.
Analyzing the RNA-Sequence of 1.3M Mouse Brain Cells with RAPIDS on NVIDIA GPUs
Learn how the use of RAPIDS to accelerate the analysis of single-cell RNA-sequence on a single NVIDIA V100 GPU shows a massive performance increase.
Model Interpretability using RAPIDS Implementation of SHAP on Microsoft Azure
Model Interpretability aids developers and other stakeholders to understand model characteristics and the underlying reasons for the decisions, thus making the process more transparent.
Streamline Your Model Builds with PyCaret + RAPIDS on NVIDIA GPUs
Running PyCarert on GPU not only streamline model building but offsets the time cost.
Step-by-Step Guide to Building a Machine Learning Application with RAPIDS
Here’s how you can get up and running quickly using the RAPIDS machine learning pipeline with the NVIDIA NGC catalog and Google Vertex AI.
Using the RAPIDS VM Image for Google Cloud Platform
NVIDIA’s Ty McKercher and Google’s Viacheslav Kovalevskyi and Gonzalo Gasca Meza jointly authored a post on using the new the RAPIDS VM Image for Google Cloud Platform. Following is a short summary. For the full post, please see the full Google article. If you’re a data scientist, researcher, engineer, or developer using pandas, Dask, scikit-learn, … Continued
Fast, Flexible Allocation for NVIDIA CUDA with RAPIDS Memory Manager
When I joined the RAPIDS team in 2018, NVIDIA CUDA device memory allocation was a performance problem. RAPIDS cuDF allocates and deallocates memory at high frequency, because its APIs generally create new Series and DataFrames rather than modifying them in place. The overhead of cudaMalloc and synchronization of cudaFree was holding RAPIDS back. My first … Continued
Building an Accelerated Data Science Ecosystem: RAPIDS Hits Two Years
GTC Fall 2020 marked the second anniversary of the initial release of RAPIDS. Created out of the GPU Open Analytics Initiative (GoAi) aimed at making accelerated, end-to-end analytics on GPUs easy, RAPIDS has proven GPUs are performant, easy to use, and transformative to the future of data analytics. By thinking about the relationship between software … Continued
ICYMI: Utilizing GPUs for Machine Learning with RAPIDS
Delve into how TMA Solutions is accelerating original ML and AI workflows with RAPIDS.