Alternatives
Products that do what Axiom – C++ tensor library with NumPy API and Metal GPU support does
I've been building a C++ tensor library that tries to bring the ergonomics of NumPy/PyTorch to native code. The main goals were: - Familiar API (operator overloading, method chaining, same function names) - Actual GPU acceleration via Metal (not just matmul, but all ops) - Cross-platform with SIMD on x86/ARM/RISC-V via xsimd - einops-style rearrange/reduce patterns It started because I wanted NumPy's API but needed to deploy on edge devices without Python. Ended up going deeper than expected (28k LOC+) into BLAS backends, memory views, and GPU kernels. Some things I'm…
- 1
- 2XA
Jul 2026 · github.com
- 3PO
Our company Vertex.AI has been working on this for a while but this is the first public release. We're starting with using PlaidML to bring OpenCL support to Keras and more frameworks, platforms, etc are coming. Yes, this means you can use use your AMD GPU for deep learning dev. Sorry, no Mac or Windows support yet although the brave can try building from source (it should work). http://vertex.ai/blog/announcing-plaidml https://github.com/plaidml/plaidml
2017
- 4TR
2018 · github.com
- 5XC
2017 · github.com
- 6
- 7
- 8LS
Earlier this year, I took a month to reexamine my coding habits and rethink some past design choices. I hope to rewrite and improve my FOSS libraries this year, and I needed answers to a few questions first. Perhaps some of these questions will resonate with others in the community, too. - Are coroutines viable for high-performance work? - Should I use SIMD intrinsics for clarity or drop to assembly for easier library distribution? - Has hardware caught up with vectorized scatter/gather in AVX-512 & SVE? - How do secure enclaves & pointer tagging differ on Intel, Arm, & AMD? - What's…
2025 · github.com
- 9M3
Grant Sanderson (3Blue1Brown) created Manim, the Python library he uses to make the math animations in his videos. We reimplemented Manim with the same Python API, but the implementation underneath is Rust, connected to Python through PyO3. The Rust code uses wgpu, so rendering happens on the GPU. To run it in the browser, we compiled the Rust parts to WebAssembly so the PyO3 extension loads in Pyodide. In the browser, wgpu targets the WebGPU API, so animations render in real time on your GPU through the browser. The editor is Monaco (the editor that powers VS Code) with a live preview:…
Jul 2026 · studio.academa.ai
- 10NT
2017 · xtensor.readthedocs.io
- 11AV
2018 · github.com
- 12AL
2019 · dev.to
- 13AA
Hey HN! We built Achilles, a tool that automatically accelerates your Python code. It identifies performance bottlenecks, rewrites those functions in optimized C++, and seamlessly patches them into your running program—without you changing a single line of code. In CPU-intensive, loop-heavy tasks, we've observed performance improvements of 100-1000x. Achilles can be installed via pip and works with just a single command. We'd appreciate your feedback, and feel free to give us a star if you find it interesting!
2025 · github.com
- 14FG
Open-source tutorial series teaching real-time graphics programming with SDL's GPU API. Covers everything from Hello Window to SSAO, with math lessons, engine lessons, and a UI track building font rendering from scratch. Every lesson is a standalone C program with commented code explaining why, not just what. The whole project was built with Claude Code. Each lesson also distills into a reusable Claude Code skill — copy them into your own project and build games with AI that actually understands the GPU patterns.
Feb 2026 · github.com
- 15LA
tl;dr I'm developing an incredibly fast library for arrays and mathematics, and I've implemented a few new features and made some improvements. I'd love for you to check it out! Links: GitHub: https://github.com/LibRapid/librapid/ Documentation: https://librapid.readthedocs.io/en/latest/ Discord: https://discord.com/invite/cGxTFTgCAC Hey everyone! I am the lead developer of LibRapid (https://github.com/LibRapid/librapid/), a high-performance C++ library for array manipulation and mathematics. I've…
2023
- 16PR
Well, it happened. After endless release candidates, we've finally made it to v0.1.0. What's inside: GPU-accelerated rendering with WebGPU shaders, shadows, and goodies like silhouette edges and a special soft-light mode Core operations run up to 1000x faster than the original PyMOL. Surface generation that used to send you on a coffee run now finishes the moment you hit the button Full PyMOL selection algebra support — 95+ keywords, boolean logic, distance/expansion operators, slash-macros Distance, angle, and dihedral measurements, atom labels — everything you need for structural…
Feb 2026 · github.com
- 17IE
Quick note on how it works and how I've done my batch embedding engine IgniteMS. The whole thing runs as one process using Rust, reading input, tokenizing, packing batches, keeping the queue full. TensorRT handles inference. Python is only as a wrapper. I built it this way because when you use more than couple of GPUs, the GPUs stop being the problem. CPU cannot feed them fast enough. One A100 can go through batches faster than Python can tokenize and feed, so the GPU just sits there idle waiting for work. Most of my time went into optimizing this. At 8 GPUs that was basically the entire…
Jun 2026 · github.com
- 18LL
After the incredible response to our launch of the first online CUDA playground, we have just shipped something we think all you GPU programming and ML enthusiasts will love. Introducing LeetGPU Challenges--the place to compete on writing the fastest CUDA kernels. We have problems like matrix multiplication, agent simulation, multi-head self-attention, with more dropping every couple of days! We have a lot of really cool things coming up, including support for PyTorch, TensorFlow, JAX, TinyGrad; Multi-GPU programs; H100, V100, A100 GPU options Give it a try and let us know what you think!
2025 · leetgpu.com
- 19UI
Hey everyone! I am excited to share updates on four of my & my teams' open-source projects that take large-scale search systems to the next level: USearch, UForm, UCall, and StringZilla. These projects are designed to work seamlessly together, end-to-end—covering everything from indexing and AI to storage and networking. And yeah, they're optimized for x86 AVX2/512 and Arm NEON/SVE hardware. USearch [1]: Think of it as Meta FAISS on steroids. It's now quicker, supports clustering of any granularity, and offers multi-index lookups. Plus, it's got more native bindings than probably…
2023 · usearch-images.com
- 20AP
I've been recently working on porting standard C library functions to work on the GPU https://libc.llvm.org/gpu/. A colleague of mine suggested using it to run DOOM, so that's what I did. It runs on both AMD and NVIDIA GPUs and it is completely playable. This works by targeting C code directly for the GPU via cross-compilation in clang, looks something like this https://godbolt.org/z/hh44a6vKr. The LLVM C library will provide the headers, C library functions, and the kernel that calls the main function, so we only need to compile the DOOM source code…
2024 · github.com
- 21AE
2016 · github.com
- 22
Hi everyone, Please checkout compute.cx which is a simple cli interface for using on demand GPUs from RunPod and HotAisle. I created this because I really like the ease of modal.com for severless gpu access, but don’t always want to pay their markup. Compute.cx gives the same DX but on public on-demand GPUs like runpod and hotaisie. Please try it out, and write to me [email protected] for any questions/suggestions, or file a bug report on https://github.com/theoriclabs/docs.compute.cx Thanks! Harsh Gupta https://x.com/hargup13 P.S. BYOK AWS, GCP and…
17d ago · compute.cx
- 23OS
2013 · yeppp.info
- 24RA
We built RapidFire AI, an open-source Python tool to speed up LLM fine-tuning and post-training with a powerful level of control not found in most tools: Stop, resume, clone-modify and warm-start configs on the fly—so you can branch experiments while they’re running instead of starting from scratch or running one after another. - Works within your OSS stack: PyTorch, HuggingFace TRL/PEFT), MLflow. - Hyperparallel search: launch as many configs as you want together, even on a single GPU - Dynamic real-time control: stop laggards, resume them later to revisit, branch promising configs in…
Sep 2025 · github.com
Ranked by how close each launch is in meaning, then by votes. Refine with a description →