Kenichi Maehashi
@kmaehashiEngineering Manager @PreferredNet, @CuPy_Team dev lead, he/him
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Thrilled to unbox some incredible swag box from @GitHubSecurity today! 🎉 Absolutely adore the cute Octocat figurine and the custom hoodie featuring my handle 🥰 Big thanks for hosting the #Hacktocat VIP program!
Optuna 4.1 is out! 🤖 AutoSampler: Automatic Selection of Optimization Algorithm 🚀 More Scalable RDB Storage Backend 🧑💻 Five New Algorithms in OptunaHub (MO-CMA-ES, MOEA/D, etc.) 🐍 Python 3.13 Support 👇See what’s new github.com/optuna/optuna/…
Today, @pydatanyc kicked off with a tutorial on GPU Accelerated Python! @numba_jit, @CuPy_Team, and @RAPIDSai are all great ways to accelerate your code. Check out the full tutorial on the NVIDIA Accelerated Computing Hub to learn more: github.com/NVIDIA/acceler…
📝 Transferring GitHub Projects Between Organizations medium.com/@kmaehashi/tra…
【PFN2024インターンブログ】夏季インターンの細川颯介さんによる寄稿です。CUDAの新機能であるCUDA Graph Conditional NodesのサポートをCuPyに実装しました。 tech.preferred.jp/ja/blog/cupy-c…
📣 Ask CUDA Python questions to experts! Join the LIVE event "CUDA Virtual Connect with Experts" this Friday, September 27th at 10am PT. Discuss CuPy, Numba @numba_jit, RAPIDS @rapidsai, or CUDA Python ecosystem with NVIDIA experts. linkedin.com/posts/katrinar…
We're trending on GitHub for a few days in a row 🚀 github.com/trending/pytho… If you haven't, star us to help spread the word! 🙌🌟 github.com/cupy/cupy
Google Gemma 2 implemented in pure NumPy/CuPy 👀 github.com/githubpradeep/… buttondown.com/ainews/archive…
Optuna 4.0, the new major release, is here! Huge thanks to all contributors and users! We are glad to see Optuna has become a leading hyperparameter optimization OSS! See what's new: medium.com/optuna/announc…
MN-Core challenge に勝手に便乗して、総合得点もしくは FizzBuzz において PFN 社内記録を倒した場合、個人的に50万円ずつ賞金を出します！詳細はこのポエムの後ろの方にあります: shinh.skr.jp/m/?date=202408… 賞金出すことになるのかならないのか、むっちゃ楽しみです #mncore
🎉 CuPy v13.3 is just out! This release includes performance improvements (“one-time only warm-up” eliminated), support for CUDA 12.5 & 12.6, and better interoperability with NumPy 2. Check out the release notes for details! github.com/cupy/cupy/rele…
n月刊ラムダノートに深層学習コンパイラに関する記事を寄稿しました。汎用コンパイラと違って深層学習コンパイラはどういう最適化に焦点を置いて、どのように実装されているかを、PFNで使われている"PFVM"を例に解説してあります。PDF版は本日発売で1000円になります！ lambdanote.com/blogs/news/n-v…
著者です。間違いなく読みごたえがある、すばらしい本である自信があります。どうぞよろしくお願いいたします。 x.com/oreilly_japan/…
8月発行予定の新刊『Binary Hacks Rebooted —低レイヤの世界を探検するテクニック89選』の情報をAmazonおよび楽天ブックスで公開開始しました！ books.rakuten.co.jp/rb/17936277/ amazon.co.jp/dp/4814400853/
📢 Just announced: nvmath-python brings NVIDIA accelerated math to #Python. ✅ Pythonic APIs for using CUDA math operations ✅ Works with your favorite Python packages ✅ #OpenSource Beta version is available now! #HPC Learn more now: nvda.ws/3VV2fGN
Open software tools, policies + communities for biomedicine are essential! This week, our Open Science grantees gathered to share their work, connect with other groups + discuss how they can make important scientific tools & information more widely accessible.
📢 CuPy v13.2 is out! This release added support for NumPy 2.0. You can use CuPy with the coming NP2! This release also has improved NCCL preloading, which brings better operability on mixed-library environments.
【論文】PFNの @asi1024, @xuzijian629 によるメモリアドレス割り当てに関する論文がInternational Symposium on Memory Management 2024に採択されました。セグメント木を用いた焼きなまし法で割り当てを事前に決定することでメモリの断片化をほぼなくすことができます。 conf.researchr.org/details/ismm-2…
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