Keith Kraus

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Keith Kraus

Keith Kraus

@keithjkraus

Director of Engineering for CUDA Python and CUDA C++ @NVIDIA, @condaforge core. Previously Co-Founded @VoltronData, @RAPIDSAI. My thoughts are my own.

Greater NYC Area Katılım Mayıs 2015
1.3K Takip Edilen1.2K Takipçiler
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NVIDIA HPC Developer
NVIDIA HPC Developer@NVIDIAHPCDev·
🎉CUDA meet-up in NYC on November 13 with @floxdevelopment. 🙌 Be sure to reserve your spot, and we will see you there!
Flox@floxdevelopment

Join us for the CUDA Meet-Up by @nvidia + Flox, hosted at the @tryramp HQ in NYC! Calling all engineers, platform teams, and DevOps pros, come hang out, learn, and connect 🙂 Learn how Flox makes it super simple to create and run reproducible CUDA-accelerated stacks. When: November 13th, 2025 Where: Ramp HQ, New York Agenda 5:00 PM — Doors Open 6:00 PM — Talks 7:00 PM — Networking 8:00 PM — Wrap-up Save your seat! Link to sign up in the comments!

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Bryce, the CUDA Colonel
Bryce, the CUDA Colonel@blelbach·
Calling all CUDA developers! The CUDA team will be in London on June 5 to host a free meetup for all skill levels. Chat with the people behind CUDA - we'll answer your questions! @aterrel & I will present on CUDA Python. Register now - space is limited! nvda.ws/45tlrBV
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Bryce, the CUDA Colonel
Bryce, the CUDA Colonel@blelbach·
We've announced cuTile, a tile programming model for CUDA! It's an array-based paradigm where the compiler automates mem movement, pipelining & tensor core utilization, making GPU programming easier & more portable. I'm proud of my stellar team for all their hard work on this!
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NVIDIA AI Developer
NVIDIA AI Developer@NVIDIAAIDev·
Curious about the latest in high-performance #Python? Introducing Numbast, a new tool that automates Numba bindings, bridging the gap between CUDA C++ and Python for seamless performance. ➡️ nvda.ws/4f30fVt Dive into our technical blog to see it in action.
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Phil Eaton
Phil Eaton@eatonphil·
Voltron layoffs, super unfortunate. You should hire Felipe.
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Felipe O. Carvalho
Felipe O. Carvalho@_Felipe·
During my 2y at @VoltronData, I worked on @ApacheArrow C++ (and PyArrow) spec’ing and implementing new types (list-view and run-end encoded arrays), expanding the fs abstraction, improving compute kernels, unblocking contributors by mentoring them on many areas of the project.
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Felipe O. Carvalho
Felipe O. Carvalho@_Felipe·
As you may have heard, there has been a big layoff at @VoltronData. I was one of the affected people together with 50+ others. It’s an exciting time for Data Engineering and Compilers targeting AI accelerators, so I’m curious to see what opportunities are available.
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Naty Clementi
Naty Clementi@ncclementi·
After 1 year at Voltron Data, I found myself along with my teammates and 50+ people in need of a job I have plenty experience building OSS Python data tools, presenting at conferences and OS community management. If you think I'd be a good fit for a job please let me know
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Voltron Data
Voltron Data@VoltronData·
This Thursday, @wesmckinn will discuss what he thinks dataframes and data systems will look like in the future. Wes is the creator of some of the most popular data engineering tools, including pandas, Apache Arrow, and Ibis. He’s also a core contributor to Apache Parquet. Wes will start with a short presentation about his work, followed by a Q&A session. The talk will be hosted by @chipro. Let us know what questions/topics you would like Wes to discuss. Time: 12pm PT, Thursday, June 20 RSVP: lu.ma/vkd8h5nu
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Mim
Mim@mim_djo·
@RitchieVink @mrocklin damn it, create view is not supported in polars ibis backend 529 def create_view(self, *_, **__) -> ir.Table: --> 530 raise NotImplementedError(self.name) 531 532 def drop_table(self, *_, **__) -> ir.Table: NotImplementedError: polars
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Matthew Rocklin
Matthew Rocklin@mrocklin·
TPC-H Cloud Benchmarks: Spark, Dask, DuckDB, Polars Across scales: 10 GiB, 100 GiB, 1 TiB, 10 TiB Hardware: MBP and AWS It was a fun experiment. No project wins uniformly. DuckDB and Dask do pretty well. docs.coiled.io/blog/tpch.html
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Mim
Mim@mim_djo·
holly Cow, I just witness a miracle, @IbisData is the most underrated data engineering package WTF is this sorcery !!!
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Ibis
Ibis@IbisData·
Ibis in the browser? Try it out! (Warning: very experimental, doesn't work on iOS, and we'll be working on UX improvements going forward!): ibis-project.org/tutorials/brow…
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Keith Kraus
Keith Kraus@keithjkraus·
@rf @hpcprogrammer Yes, many of the queries here are running large hash joins that run larger than both GPU memory and host memory where we gracefully spill to run out of core. Large sorting would work similarly, just with a different work partitioning strategy.
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rf
rf@rf·
@hpcprogrammer Does Theseus do external-memory joins with hashing/sorting on the GPU? I remember seeing some benchmarks on the Theseus site mentioning good join perf. (Which is good, large joins seem to be a place a lot of otherwise good analytics tools get weird.)
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