RunMat @runmat_com

Try it for yourself at runmat.com/sandbox Paste the code below XRange = -2:0.04:2; YRange = -2:0.04:2; [X, Y] = meshgrid(XRange, YRange); R = sqrt(X.^2 + Y.^2) + 0.01; for t = 0:0.05:10 Z = sin(pi*R*3 - t*2) ./ (1 + R) + cos(pi*R*2 + t*1.5) ./ (1 + R*2); surf(X, Y, Z); shading interp; colormap("jet"); pause(0.03); end

Engineers use wave interference like this to design noise-canceling headphones, radar systems, and 5G antennas. The key ingredient? #Pi. It controls the frequency, the phase, and the cancellation. This video shows two pi-frequency waves colliding in real time. GPU-accelerated, running in a browser, 12 lines of code. Stay tuned for more on Saturday, #PiDay. #RunMat

Every #MATLAB #engineer has done this: write 50 lines, hit run, wait, get "Matrix dimensions must agree" on line 6. Go back. Stare. Fix it. Run again. #RunMat catches it before you run. Hover over any variable and you see its shape. Write a dimension mismatch, and you get the error inline, in real time, with the exact sizes: "left is 1x201, right is 1x201, inner dims 201 and 1." No run. No wait. No guesswork. Software engineers have had this for decades -- TypeScript, Rust, and Go all catch type errors before execution. #Numerical engineers deserve the same. That's what we're building.

eig function doc: runmat.com/docs/reference… eig source code: github.com/runmat-org/run…

MATLAB: eig(A) → eigenvalues. How? Trust us. RunMat: eig(A) → eigenvalues. How? Here's every step. On GitHub. In Rust. Eigenvalues tell you the fundamental modes of a system: vibration frequencies, principal components, and stability characteristics. Simple question. Hard computation. What RunMat does under the hood: 1. Schur decomposition: Reduce to upper-triangular form. 2. Back-substitution: Solve for each eigenvector column by column. 3. Normalization: Handle repeated eigenvalues and near-singular edge cases. 4. GPU awareness: Keep results on-device when a provider is available. That's 900 lines of Rust. Every edge case (repeated eigenvalues, near-singular matrices, complex spectra) handled explicitly in code you can read. Engineers should have full traceability: from the function call, through the algorithm, down to the machine epsilon constant. If you can't trace it, you can't trust it. 300+ functions. Zero black boxes.

Try it for yourself at runmat.com/sandbox % Generate a high-density parametric mesh (250k points) [u,v] = meshgrid(linspace(0,2*pi,500), linspace(0,pi,500)); % Define the 3D heart surface equations x0 = 16*sin(u).^3 .* sin(v).^2; y0 = (13*cos(u)-5*cos(2*u)-2*cos(3*u)-cos(4*u)) .* sin(v).^2; z0 = 6 * cos(v); % Animate the heartbeat for t = 0:0.1:100 % Calculate scale factor for contraction/expansion s = 1 + 0.05*sin(t*3); % Render the scaled point cloud in red scatter3(x0(:)*s, y0(:)*s, z0(:)*s, 2, 'r'); pause(0.01); end

Happy #Valentine's Day from the team that loves math. ❤️ This isn't a pre-rendered animation. It's live numerical computation. We generated a parametric heart with 250,000 points and made it beat. Notice the fluidity? That's what we think modern computation should feel like. Not just solving equations, but exploring them in real-time. You can rotate, zoom, and dive deep into the structure without it ever skipping a beat. We put our heart into this runtime so you can put yours into the #math. (Code in next comment)

Read the full argument: runmat.com/blog/in-defens…

Engineers don't need "better" syntax than MATLAB. `A * B` is already the perfect way to write matrix multiplication. The problem isn't the language. It's the runtime. We built RunMat to fix that: Same whiteboard syntax. Modern, GPU-accelerated engine.

Introducing RunMat Accelerate: The Fastest Runtime for Your Math runmat.org/blog/runmat-ac…

We may have just built the fastest runtime to run math in the world. The initial benchmarks (on my local MacBook pro) are looking stellar 🔥 Here’s how it works, and how we built it 🧵

@kevinweil We built the entire Matlab runtime (it’s over 3M chatarcters of code) in 6 weeks using it. runmat.org It’s open source. Matlab programming is now free — like Python. We’re making it the fastest math runtime in the world — JIT for CPU logic and auto-GPU shaders.

@DaveShapi Think we may already be at senior. Did a side project to test the bounds — been programming for a very long time, and am a founder. There’s little to no room for junior / mid. Even senior I think is hairy. I’d only want architects / great supervisors. x.com/nabeelallana/s…

Nabeel Allana @nabeelallana

11 months ago

MATLAB makes $500M annually selling what I just re-engineered in 3 weeks. Here’s how I demonstrated that enterprise software moats today can evaporate in the same time it typically takes to plan a sprint. 👇🧵

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The rust-ification will continue until memory safety improves

Nabeel Allana @nabeelallana

11 months ago

MATLAB makes $500M annually selling what I just re-engineered in 3 weeks. Here’s how I demonstrated that enterprise software moats today can evaporate in the same time it typically takes to plan a sprint. 👇🧵

4 6 27 3K 5

Cool new open source MATLAB runtime. Some CUDA acceleration too!

Nabeel Allana @nabeelallana

11 months ago

MATLAB makes $500M annually selling what I just re-engineered in 3 weeks. Here’s how I demonstrated that enterprise software moats today can evaporate in the same time it typically takes to plan a sprint. 👇🧵

4 6 27 3K 5

✅ Fully functional MATLAB runtime ✅ All grammar & core semantics implemented ✅ Functional JIT + GPU acceleration framework ✅ Tiny ~5MB binary, runs in 5ms ✅ Container-ready, cross platform (ARM/x86_64/...) ✅ 150-180x faster than Octave ✅ Typed computation graphs (IYKYK)

MATLAB makes $500M annually selling what I just re-engineered in 3 weeks. Here’s how I demonstrated that enterprise software moats today can evaporate in the same time it typically takes to plan a sprint. 👇🧵

@FluentInFinance Would add Dystr to the list! Engineers and scientists love it!

@paulg Classic innovators dilemma!