Ok I am geeking SUPER HARD about this one!

🔥NVIDIA just made pandas 100x faster through RAPIDS AI

▫️Zero code changes
▫️One code path differing hardware (aka you can run on GPU or CPU, depending on what you have available, with no code change)
▫️One “magic formula”:

>…

The RAPIDS 24.04 release is out now! Check out the new accelerated vector search library, expanded zero-code change experiences for pandas & NetworkX workflows, optional query optimization for Dask workflows, support for Python 3.11 and pandas 2, and more. nvda.ws/4aTabyH

Discover the enhanced capabilities of RAPIDS AI #cuDF which boosts Pandas performance up to 100x without code changes. Watch the on-demand #GTC24 session to learn how. nvda.ws/4cXeNFm

Discover the enhanced capabilities of RAPIDS AI #cuDF which boosts Pandas performance up to 100x without code changes. Watch the on-demand #GTC24 session to learn how. nvda.ws/4cXeNFm

🌊What is RAPIDS AI from NVIDIA?
💻How can we leverage GPU powered workstations within our AI/ Data Science projects?
🏎️Why speed is an important factor within the MLOps pipeline?

🎙️Join us for a one-hour webinar exploring how CUDA can accelerate ML pipelines on Z by HP…

Josh Patterson @MurrayData polars data DuckDB RAPIDS AI FWIW that's what I got on my laptop with 32 GB RAM & 10 cores I9 (I did not use per_thread_output in DuckDB because I wanted a single output file). Input file size : 2.7 GB, row count : 59986052.

First public demo on Thursday: Real-time accelerated #genAI investigation & monitoring of crime, news, & social

Join us in Virginia/DC to see what has been made possible with Groq Inc , louie.ai (@Graphistry ), Nvidia RAPIDS AI , and DOD Chief Digital & AI Office Disaster Tech

I learned so much from Erik Welch (@[email protected])'s keynote at PyCon Hong Kong: How to accelerate NetworkX with GraphBLAS and cuGraph.

Amazing work Erik Welch (@[email protected]) NVIDIA RAPIDS AI NetworkX 🙌🙌🙌

Discover the enhanced capabilities of RAPIDS AI #cuDF which boosts Pandas performance up to 100x without code changes. Watch the on-demand #GTC24 session to learn how. nvda.ws/4cXeNFm

Interested in Big Data Visualization? Check out the RAPIDS AI visualization guide docs.rapids.ai/visualization

Thanks for using Panel and HoloViz to power the interactivity in the page and the positive mention.

#python #bigdata #Datavisualization

10 years of 'it can't be done...' 7 NVIDIA GPU architectures... 5 years of RAPIDS AI... 3 years of Voltron Data... finally a petabyte-scale GPU-native engine that DOESN'T require you to change your data pipelines. Same code, same data formats, just modular, interoperable,…

My colleagues Michael Wang and Thomson Comer will be presenting at #GTC23 about our work on the RAPIDS AI cuSpatial library. Join for a fascinating discussion on GPU geospatial analytics and a killer #Python demo. Don't miss it! Register now: register.nvidia.com/flow/nvidia/gt…

Join us for our webinar on how Dask DataFrame is fast now
- TPC-H benchmarks for Dask, Spark, DuckDB, Polars
- How Dask expressions optimizes your code (like Spark SQL would)
- Use GPUs with RAPIDS AI

🗓 Thursday, Nov. 16th
⏰ 11am ET
Register here: content.coiled.io/dask-expr-webi…

.RAPIDS AI, the open-source software to accelerate data science, has just been recognized as a Top #OpenSource Software by InfoWorld. Read about it here: nvda.ws/479CHK4 #RAPIDSAI

Josh Patterson RAPIDS AI ApacheArrow Oh that’s cool. I didn’t find it in GitHub

How to accelerate your data science in Python with RAPIDS AI?

✅ leverage common APIs to run on the GPU
✅ hands-on, end-to-end introduction to cudf, cuml, and data viz with UMAP and hvplot!

A great talk by John Zedlewski and Ashwin Srinath!

nvidia.com/gtc/session-ca…

Discover the enhanced capabilities of RAPIDS AI #cuDF which boosts Pandas performance up to 100x without code changes. Watch the on-demand #GTC24 session to learn how. nvda.ws/4cXeNFm

Woot! Great to be back in person NVIDIA #GTC24 seeing my teams, new and old… so proud of all the accomplishments of RAPIDS AI and all their spinouts, cuOpt, Morpheus, the graph team, and so much more. The power of RAPIDS is spreading to all corners of the GPU ecosystem.

The HoloViz ecosystem works really as well with the other members of the #Pandata stack like pandas, Xarray RAPIDS AI, Numba, Dask, Matplotlib, Bokeh Visualization Library, conda and Project Jupyter

Check out github.com/panstacks/pand…

#ModernScienceStack