Pinned Tweet
Announcing CuPy v14! 🚀
🔹 NumPy v2 semantics
🔹 CUDA Pip Wheels support
🔹 bfloat16 & structured dtype
🔹 Enhanced NumPy/SciPy API coverage
Read more on our blog for the full details! 👇
🔹 NumPy v2 semantics
🔹 CUDA Pip Wheels support
🔹 bfloat16 & structured dtype
🔹 Enhanced NumPy/SciPy API coverage
Read more on our blog for the full details! 👇
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CuPy retweeted
Major ecosystem libraries like PyTorch and CuPy now build on the shared cuda.core foundation, reducing version conflicts and interop bugs for developers.
With CUDA 13.3, @nvidia released CUDA Python 1.0, the libraries and tools that give you the full CUDA platform from Python. text, devices, streams, and memory are shared with the rest of the Python GPU ecosystem, so your own kernels can run against CuPy arrays or PyTorch tensors without copying data.
Read the full blog post: bit.ly/4hcSu2C
With CUDA 13.3, @nvidia released CUDA Python 1.0, the libraries and tools that give you the full CUDA platform from Python. text, devices, streams, and memory are shared with the rest of the Python GPU ecosystem, so your own kernels can run against CuPy arrays or PyTorch tensors without copying data.
Read the full blog post: bit.ly/4hcSu2C
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CuPy v14.2 is out! 🎉
Highlights:
🔹 SciPy-compatible sparse array classes
🔹 Windows on Arm (RTX Spark) support
🔹 Initial integration with nvmath-python
Check the release notes for details 👇
Highlights:
🔹 SciPy-compatible sparse array classes
🔹 Windows on Arm (RTX Spark) support
🔹 Initial integration with nvmath-python
Check the release notes for details 👇
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CuPy v14.1.0 is out! 🚀 Large sparse matrices, Python 3.14t (free-threaded) support, structured dtypes, CUDA 13.2/NCCL 2.29, new APIs, and more. Check out the release notes for details! 🧵
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🚀 CuPy v14.0.0rc1 is here!
Highlights include CUDA PyPI package compatibility (no system-wide CUDA Toolkit installation required) and AMD ROCm 7 support.
Test your workload with our pre-compiled packages and report any feedback! See the release notes for the full details 👇
Highlights include CUDA PyPI package compatibility (no system-wide CUDA Toolkit installation required) and AMD ROCm 7 support.
Test your workload with our pre-compiled packages and report any feedback! See the release notes for the full details 👇
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⚡️A talk on CuPy will be presented at the SciPy 2025 conference! 🎉
Leo Fang, a long-time contributor, will share his personal story on #CuPy's evolution and future.
cfp.scipy.org/scipy2025/talk…
#SciPy2025
Leo Fang, a long-time contributor, will share his personal story on #CuPy's evolution and future.
cfp.scipy.org/scipy2025/talk…
#SciPy2025
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Recording is now available on YouTube! youtube.com/watch?v=Jj4Kdt…
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Also, there are more sessions and tutorials highlighting CuPy at SciPy 2025. Explore the full schedule at scipy2025.scipy.org/schedule!
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📢CuPy v13.5 is out! CuPy now supports CUDA 12.9, ROCm 6.4, and NumPy 2.3. This release also brings Unified Memory Programming support for NVIDIA’s Grace Hopper systems.
Check out the full release notes 🧵
Check out the full release notes 🧵
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One more thing - CuPy has just reached 10,000 GitHub stars! ⭐ A huge thank you to all our users, contributors, and everyone who has supported us on this incredible journey!
If you haven't yet, now's a great time to add your star 😉
github.com/cupy/cupy
If you haven't yet, now's a great time to add your star 😉
github.com/cupy/cupy
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Thanks for featuring, @StarHistoryHQ! x.com/StarHistoryHQ/…
10.1K ⭐️ CuPy is a NumPy/SciPy-compatible array library 📚 that enables GPU-accelerated computing in Python by serving as a drop-in replacement for existing NumPy/SciPy code. @CuPy_Team
star-history.com/#cupy/cupy&Date
#starhistory #GitHub #OpenSource
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🚀 The first alpha release of CuPy v14 is now available! The v14 series provides the behavior aligned with the latest NumPy 2 specification, as well as numerous new NumPy/SciPy-compatible APIs.
Binary packages are ready to try! Explore the release notes for all the details ⬇️
Binary packages are ready to try! Explore the release notes for all the details ⬇️
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