Alternatives
Products that do what RunClass: Solver para Matéria Escura S8 does
Solving the Universe's Dark Sector.
- 1AP
We ported pbrt-v4 to Julia and built it into a Makie backend. Any Makie plot can now be rendered with physically-based path tracing. Julia compiles user-defined physics directly into GPU kernels, so anyone can extend the ray tracer with new materials and media - a black hole with gravitational lensing is ~200 lines of Julia. Runs on AMD, NVIDIA, and CPU via KernelAbstractions.jl, with Metal coming soon. Demo scenes: github.com/SimonDanisch/RayDemo
Feb 2026 · makie.org
- 2PI
Hi HN! I’m Alex from Parabola (https://parabola.io). Parabola is a visual programming tool for creating functional data flows that everyone can use. It’s entirely drag-and-drop, handles data sizes much larger than a traditional spreadsheet, calculates everything live, and can run your flows on a schedule of your choosing. I used to work in strategy consulting, doing data analytics for SMBs and Fortune 500 companies. The amount of time wasted on menial tasks was astounding. Things like cleaning data, generating custom reports, creating human workflows to solve shortcomings in third…
2018 · parabola.io
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- 4SB
2020 · landgreen.github.io
- 5BB
Features include: - Several preset periodic orbits: the classic Figure-8, plus newly discovered 3D solutions from Li and Liao's recent database of 10,000+ orbits (https://arxiv.org/html/2508.08568v1) - Full 3D camera controls (rotate/pan/zoom) with body-following mode - Force and velocity vector visualization - Timeline scrubbing to explore the full orbital period The 3D presets are particularly interesting. Try "O₂(1.2)" or "Piano O₆(0.6)" from the Load Presets menu to see configurations where bodies weave in and out of the orbital plane. Most browser…
Nov 2025 · trisolarchaos.com
- 6RT
I ported Microsoft's TRELLIS.2 (4B parameter image-to-3D model) to run on Apple Silicon via PyTorch MPS. The original requires CUDA with flash_attn, nvdiffrast, and custom sparse convolution kernels: none of which work on Mac. I replaced the CUDA-specific ops with pure-PyTorch alternatives: a gather-scatter sparse 3D convolution, SDPA attention for sparse transformers, and a Python-based mesh extraction replacing CUDA hashmap operations. Total changes are a few hundred lines across 9 files. Generates ~400K vertex meshes from single photos in about 3.5 minutes on M4 Pro (24GB). Not as fast as…
Apr 2026 · github.com
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- 8WT
I figured I needed to work on my coding skills before building the next groundbreaking AI app, so I started working on this free tool site. Its basically just an aggregation of various commonly used calculators and unit convertors. Link: https://www.calcverse.live Tech Stack: Next, React, Typescript, shadcn UI, Tailwind CSS Would greatly appreciate your feedback on the UI/UX and accessibilty. I struggled the most with navigation. I've added a search box, a sidebar, breadcrumbs and pages with grids of cards leading to the respective calculator or unit convertor, but not sure if…
2025 · calcverse.live
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Powers faster, efficient reasoning for long-running agents
Jun 2026 · developer.nvidia.com
- 11IB
Hi HN, Over the past few months, I've been building `dsc`, a tensor library from scratch in C++/CUDA. My main focus has been on getting the basics right, prioritizing a clean API, simplicity, and clear observability for running small LLMs locally. The key features are: - C++ core with CUDA support written from scratch. - A familiar, PyTorch-like Python API. - Runs real models: it's complete enough to load a model like Qwen from HuggingFace and run inference on both CUDA and CPU with a single line change[1]. - Simple, built-in observability for both Python and C++. Next on the roadmap is…
2025 · github.com
- 12GV
100k real ( +100k random ) galaxies from a sector. Visualized with Raylib.
2024 · github.com
- 13AN
- 14LO
Hi HN, I’m Joe. My friends Matthew, Jake and I are building Luminal (https://luminalai.com/), a GPU compiler for automatically generating fast GPU kernels for AI models. It uses search-based compilation to achieve high performance. We take high level model code, like you'd have in PyTorch, and generate very fast GPU code. We do that without using LLMs or AI - rather, we pose it as a search problem. Our compiler builds a search space, generates millions of possible kernels, and then searches through it to minimize runtime. You can try out a demo in `demos/matmul` on mac to…
2025 · github.com
- 15IT
Hi HN - My name is Andrew, and I'm a high school student. This is a write-up on StratoSpore, a payload I designed and launched to the stratosphere. The goal was to test if we could estimate physical altitude based on algae fluorescence (using a lightweight ML model trained on the sensor data). The blog post covers the full engineering mess/process, including: - The Hardware: Designing PCBs for the AS7263 spectral sensor and Pi Zero 2 W. -The biological altimeter: How I tried to correlate biological stress (fluorescence) with altitude. - The Communications: A custom lossy compression…
Nov 2025 · radi8.dev
- 16RR
Hi, I’m Nabeel. In August I released RunMat as an open-source runtime for MATLAB code that was already much faster than GNU Octave on the workloads I tried. https://news.ycombinator.com/item?id=44972919 Since then, I’ve taken it further with RunMat Accelerate: the runtime now automatically fuses operations and routes work between CPU and GPU. You write MATLAB-style code, and RunMat runs your computation across CPUs and GPUs for speed. No CUDA, no kernel code. Under the hood, it builds a graph of your array math, fuses long chains into a few kernels, keeps data on the GPU when…
Dec 2025 · github.com
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- 18TA
We’re building TheorIA— an open, high quality dataset of theoretical physics results: equations, derivations, definitions, and explanations — all in structured, machine- and human-readable JSON. Why? Physics is rich with beautiful, formal results — but most of them are trapped in PDFs, LaTeX, or lecture notes. That makes it hard to: - train symbolic/physics-aware ML models, - build derivation-checking tools, - or even just teach physics interactively. THEORIA fills that gap. Each entry includes: A result name (e.g., Lorentz transformations) Clean equations (AsciiMath) Straightforward…
2025 · theoria-dataset.github.io
- 19HS
I saw a tweet that tinygrad is so good that you could make a graphics library that wraps tg. So I’ve been hacking on a gtinygrad, and honestly it convinced me it could be used for legit research. The JIT + tensor model ends up being a really nice way to express light transport all in simple python, so I reimplemented some new research papers from SIGGRAPH like REstir PG and SZ and it just works. instead of complicated cpp its just a 200 LOC of python.
Jan 2026 · github.com
- 20
- 21RB
2016 · flannelhead.github.io
- 22IB
Mar 2026 · structuredlabs.github.io
- 23RA
Why build this? MATLAB wasn’t chosen by engineers; it was inherited from classrooms. That unfair advantage let MathWorks sell a decades-old runtime with heavy startup, sluggish hot loops, and paywalled toolboxes. It milks about $500M a year out of the engineering ecosystem for what amounts to an outdated compiler and runtime stack. GNU Octave has been the main open-source way to run MATLAB code but it only supports a subset of the grammar and semantics, and its performance is far behind modern expectations. It’s more of a compatibility bridge than a true runtime alternative. I decided to…
2025 · runmat.org
- 24TA
Hi HN! I’ve spent the summer of the past 2 years building The Atlas, a procedural universe simulator that generates 1 sextillion galaxies (10²¹) from a single mathematical seed. Think No Man’s Sky meets theoretical physics, but running entirely in your browser. Everything is purely deterministic, the universe is calculated from SHA-256 hashed seeds using the golden ratio as primordial constant. There’s no database, no pre-saved data, just pure math. Time itself is treated as a coordinate, so the universe exists as a 4D structure where any moment can be computed on demand. Shut it down for…
Sep 2025 · github.com
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