ptrblck

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ptrblck

ptrblck

@ptrblck_de

Deep learning and drums, @PyTorch engineer at @NVIDIA

California, USA Katılım Nisan 2014
423 Takip Edilen18.2K Takipçiler
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ptrblck
ptrblck@ptrblck_de·
I just posted my 10,000th reply in the @PyTorch discuss forum! Thanks everyone for creating such a great community, for the guidance and mentorship I received, and @soumithchintala for starting this journey.
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PyTorch
PyTorch@PyTorch·
Heading to #NVIDIAGTC next week? Let’s talk @PyTorch. 🚀 We’re bringing the community to San Jose. Drop by Booth #338 to meet expert developers and core maintainers in person. Scaling, inference, foundation models, and OSS contributions. Full schedule below 👇 #PyTorch
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Soumith Chintala
Soumith Chintala@soumithchintala·
@giffmana @msharmavikram @ptrblck_de torch.autograd.profiler.emit_nvtx. It emits nvtx markers for every torch op. #torch.autograd.profiler.emit_nvtx" target="_blank" rel="nofollow noopener">docs.pytorch.org/docs/stable/au…
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Lucas Beyer (bl16)
Lucas Beyer (bl16)@giffmana·
nsys looks pretty cool actually, but information overload for a first-time user. Took me a bit to get good at Google's XProf too, so let's get started! QQ to my nsys expert followers: any specific pro-tips? Biggest bang-for-buck things/views to look at? Any good pytorch training-specific profiling walk-through video or slides or blog you'd recommend? 25% on a thing called "fused zeros" sounds like I may be doing something very wrong still, will have to find out😅 Also, hate the scrolling zoom, no WASD navigation?
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PyTorch
PyTorch@PyTorch·
Update from the PyTorch maintainers: 2.7 is out now. 🔹 Support for NVIDIA Blackwell (CUDA 12.8) 🔹 Mega Cache 🔹 torch.compile for Function Modes 🔹 FlexAttention updates 🔹 Intel GPU perf boost 🔗 Blog: hubs.la/Q03jBPSL0 📄 Release notes: hubs.la/Q03jBPlW0 #PyTorch #OpenSourceAI
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ptrblck
ptrblck@ptrblck_de·
@TheGoonsta08 @PyTorch @nvidia @Meta Blackwell support is already supported in our nightly binaries if you select CUDA 12.8 for some time. PyTorch 2.7.0 will support it as well.
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James
James@TheGoonsta08·
@PyTorch @ptrblck_de @nvidia @Meta all i want to know is if blackwell support is in the pipeline...im just now getting into AI and I bought a 50 series gpu for my first build. stable diffusion is basically impossible for a layman like myself currently
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Dylan Patel
Dylan Patel@dylan522p·
Our banger hackathon this Sunday Over 100 B200 / GB200 to hack on Participants from every lab Prizes of Blackwell GPUs + more Speakers - Phil Tillet OpenAI, Horace He Thinking Machines, Tri Dao Together, Vijay Nvidia, and Mark GPUMode/PT 30 spots left Apply NOW Link in next tweet
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Horace He@cHHillee

I'll be here and talking about ML systems! There'll be some of the best GPU folk I know here, so come and learn more together about Blackwell GPUs!

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SkalskiP
SkalskiP@skalskip92·
popular computer vision package ultralytics (home of yolov8 and yolo11) was compromised. a crypto miner was injected into versions 8.3.41 and 8.3.42. link: github.com/ultralytics/ul…
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Rohan Paul
Rohan Paul@rohanpaul_ai·
NetworkX from NVIDIA is one THE most popular Python graph analytics library with ~15K Github starts and 80M downloads monthly. This library is for working with networks and graphs. It helps analyze connections between things - like social networks, computer networks, or any system where objects are connected to each other. And now NetworkX just got massively accelerated after its backend integration with NVIDIA's cuGraph. ✨ Up to 500x speedups on large graph workloads in NetworkX with zero code changes. And it is Zero Code Change Acceleration. 📌 cuGraph is NVIDIA's GPU-accelerated graph analytics library within the RAPIDS ecosystem. The library provides fast graph algorithms on GPUs, supporting property graphs, remote operations, and graph neural networks (GNNs). Works with GPU DataFrames (cuDF) and integrates smoothly with NetworkX-like API. -------- 📌 The traditional bottleneck of NetworkX's pure Python implementation becomes apparent when processing graphs larger than 100K nodes and 1M edges. 📌 And so now cuGraph solves this by offloading supported algorithms to the GPU. PageRank, Louvain community detection, betweenness centrality, and about 60 other algorithms get instant acceleration. 📌 This acceleration enables previously impractical use cases. Fraud detection systems can now process massive transaction networks in real-time. Recommendation engines handle millions of user-item interactions efficiently. Social network analysis scales to entire platforms worth of data on a single machine. @NVIDIAAIDev
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ptrblck
ptrblck@ptrblck_de·
@rasbt @lantiga @PyTorch It was great meeting you finally! Your books and lectures were my reference while digging into ML and now I even got a signed copy of your new book! Time to build an LLM from scratch!
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Sebastian Raschka
Sebastian Raschka@rasbt·
Such a great conference, had an awesome time! @ptrblck_de was how I learned PyTorch and it was great to finally meet! Ha, and honestly, every time someone asks an LLM a question about PyTorch today and gets a coherent answer, it’s probably thanks to his contributions to the PyTorch community. I wouldn’t be surprised if >90% of the LLM training data on PyTorch comes from his work!
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NVIDIA AI Developer
NVIDIA AI Developer@NVIDIAAIDev·
For those at #PyTorchConf - if you missed our meetup earlier this week, stop by our lounge on the 2nd floor. We have 40+ technical experts that can answer any questions. nvda.ws/3Xz2CHQ We hope to see you there. 🙌
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NVIDIA Data Center
NVIDIA Data Center@NVIDIADC·
📣 CUDA MODE goes live IRL! Join us in San Francisco on Sept. 21 for the #Hackathon event. 🎉 Make friends, enjoy keynotes from #CUDA experts, then hack all day and night! ➡️ Apply for a spot now: nvda.ws/3AcLAHB
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Khushi Agrawal
Khushi Agrawal@khushi__411·
Excited to share a blog series I've been working on, diving deep into CUDA programming! Inspired by the #PMPP book & #CUDA_MODE!! Check out the links below...
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NVIDIA AI Developer
NVIDIA AI Developer@NVIDIAAIDev·
🌟We are honored that our own Piotr Bialecki (@ptrblck_de) has been designated a #PyTorch Superhero Contributor, and now a Core Maintainer, where he will continue to help build the long-term vision for PyTorch, champion #OSS, and be a key member of the governing body and community. ➡️ nvda.ws/4d9eAhG 🎉Congrats Piotr!
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