John Zedlewski
@zstats.bsky.social
Leading RAPIDS (https://rapids.ai/) and accelerated data science at NVIDIA, but opinions shared here are my own. We want to help everyone get answers faster, build models more efficiently, and leverage modern AI to make the world a bit better!
You can train your scikit-learn #ML models up to 50x faster on GPU now, without changing a single line of code. The cuML accelerator for scikit-learn is now in open (and open source) beta): www.youtube.com/watch?v=cIJs...
cuML Accelerates Machine Learning by 50x with Zero Code Change
YouTube video by NVIDIA Developer
www.youtube.com
March 18, 2025 at 8:44 PM
You can train your scikit-learn #ML models up to 50x faster on GPU now, without changing a single line of code. The cuML accelerator for scikit-learn is now in open (and open source) beta): www.youtube.com/watch?v=cIJs...
Reposted by John Zedlewski
Nvidia boss saves California College of the Arts with mega donation
Nvidia boss saves California College of the Arts with mega donation
The Nvidia boss swoops in as the school faces a budget shortfall, layoffs, and declining enrollment.
sfstandard.com
February 21, 2025 at 12:25 AM
Nvidia boss saves California College of the Arts with mega donation
Data scientists and engineers, did you know that @pola.rs goes even faster if you have a GPU? NVIDIA and the Polars team are doing a webinar with a deep dive into how it all works on Jan 28. Check it out! info.nvidia.com/nvidia-polar...
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info.nvidia.com
January 13, 2025 at 5:23 PM
Data scientists and engineers, did you know that @pola.rs goes even faster if you have a GPU? NVIDIA and the Polars team are doing a webinar with a deep dive into how it all works on Jan 28. Check it out! info.nvidia.com/nvidia-polar...
Sometimes it's great to write a super-deep tech blog, but I also appreciate these shorter ones. Like, here we just want to give a quick rundown of exactly how to configure Dask so you can scale to multiple GPUs with the best possible memory/networking config: developer.nvidia.com/blog/best-pr...
Best Practices for Multi-GPU Data Analysis Using RAPIDS with Dask | NVIDIA Technical Blog
As we move towards a more dense computing infrastructure, with more compute, more GPUs, accelerated networking, and so forth—multi-gpu training and analysis grows in popularity. We need tools and also...
developer.nvidia.com
November 25, 2024 at 8:17 PM
Sometimes it's great to write a super-deep tech blog, but I also appreciate these shorter ones. Like, here we just want to give a quick rundown of exactly how to configure Dask so you can scale to multiple GPUs with the best possible memory/networking config: developer.nvidia.com/blog/best-pr...
Maybe this bsky account needs to broaden to focus on GPUs, data science, and induction stove fandom? Seriously, induction is the best way to cook, and it's cool to see a company rolling it out with 110v power: www.berkeleyside.org/2024/11/21/m...
Made-in-Berkeley induction stove from Copper lets users 'plug and play'
The range operates on 110 volts so that users don't need an electrical upgrade, and a battery stores the power.
www.berkeleyside.org
November 21, 2024 at 10:43 PM
Maybe this bsky account needs to broaden to focus on GPUs, data science, and induction stove fandom? Seriously, induction is the best way to cook, and it's cool to see a company rolling it out with 110v power: www.berkeleyside.org/2024/11/21/m...
cuPyNumeric is a super cool approach - full NumPy compatibility in Python, but automatically scaling up to 1000-node HPC levels and supporting both GPUs and CPUs. You can try it now: blogs.nvidia.com/blog/cupynum...
NVIDIA Releases cuPyNumeric, Enabling Scientists to Harness GPU Acceleration at Cluster Scale
Researchers can use the NVIDIA cuPyNumeric accelerated computing library to effortlessly run their data-crunching Python code.
blogs.nvidia.com
November 21, 2024 at 8:01 PM
cuPyNumeric is a super cool approach - full NumPy compatibility in Python, but automatically scaling up to 1000-node HPC levels and supporting both GPUs and CPUs. You can try it now: blogs.nvidia.com/blog/cupynum...
Anyone working in #graph analytics knows that NetworkX is super popular for prototyping, but it can get quite slow. This blog introduces zero-code-change GPU acceleration for NetworkX code with massive speedups. (Think 100x or more for large graphs.): developer.nvidia.com/blog/network...
NetworkX Introduces Zero Code Change Acceleration Using NVIDIA cuGraph | NVIDIA Technical Blog
NetworkX accelerated by NVIDIA cuGraph is a newly released backend co-developed with the NetworkX team. NVIDIA cuGraph provides GPU acceleration for popular graph algorithms such as PageRank, Louvain…
developer.nvidia.com
November 14, 2024 at 6:59 PM
Anyone working in #graph analytics knows that NetworkX is super popular for prototyping, but it can get quite slow. This blog introduces zero-code-change GPU acceleration for NetworkX code with massive speedups. (Think 100x or more for large graphs.): developer.nvidia.com/blog/network...
I'll be trying out some occasional posts here on BlueSky, mostly talking about #GPUs, #machinelearning, and interesting stuff we're doing at NVIDIA around accelerating data processing and data science.
November 14, 2024 at 6:57 PM
I'll be trying out some occasional posts here on BlueSky, mostly talking about #GPUs, #machinelearning, and interesting stuff we're doing at NVIDIA around accelerating data processing and data science.