Login

u/Initial-War-6965

▲ 0 r/learnmachinelearning

[Showcase] [Open Source] Episteme: A High-Performance Scientific Framework (15x faster than EJML) built with Java Panama & Antigravity

Hey everyone,

I've spent the last 5 months building something massive, and I'm finally ready to share the first beta and open-source the core foundation.

Meet Episteme—a unified, high-performance scientific computing framework for Java 21/25.

Why another math library?

For decades, HPC was synonymous with C/Fortran. I wanted to bring bare-metal performance to the JVM without losing object-oriented elegance.

* Insane Performance: By leveraging the Java Panama API (FFM) for zero-overhead native C/BLAS access, alongside plug-and-play compute backends for CUDA and OpenCL, we are seeing up to 15x faster results for double-precision linear algebra compared to Apache Commons Math and EJML. We also utilize the Vector API for SIMD.

* The Scale: The framework is 450,000+ lines of code. I was able to build this in just 5 months by heavily utilizing Antigravity AI. It’s a showcase of what agentic AI can do when strictly guided by solid architectural principles.

* The Natural Hierarchy: It’s not just a math wrapper. Modules follow the natural sciences: Mathematics -> Physics -> Biology -> Social Sciences. A model built for fluid dynamics in `episteme-natural` can be seamlessly reused for economic flows in `episteme-social`.

* Distributed Grid: Built-in gRPC worker nodes for out-of-the-box cluster computing.

🤝 Passing the Torch

As my research focus is shifting toward new paradigms (like Open Primer), I am handing the keys over to the community. If you are passionate about Project Panama, HPC, or GPU computing in Java, I am looking for maintainers and contributors to take ownership of these modules.

Check it out, fork it, and drop a star: https://github.com/Episteme-HTC/Episteme

*(Personal note: I am currently looking for my next full-time role as an IT Manager or AI Solutions Architect. If your team is tackling complex systems, let's connect!)*

reddit.com
u/Initial-War-6965 — 3 days ago
▲ 0 r/google_antigravity+1 crossposts

[Showcase] I used Antigravity to build a 450,000-line High-Performance Computing framework in Java in 5 months.

Hey everyone,

I see a lot of discussions here about the limitations of agentic AI, so I wanted to share a successful, massive-scale production use-case.

Over the last 5 months, I partnered with **Antigravity** to build **Episteme**, a unified scientific computing framework for Java. We generated over **450,000 lines of production-ready code**, integrating complex Java Panama (FFM API) bindings to native C/BLAS libraries, as well as CUDA and OpenCL compute backends.

**How I managed the AI:**

The key wasn't letting the AI design the system, but acting as the strict Architect. I defined the "Natural Hierarchy" (Math -> Physics -> Social Sciences) and the exact architectural boundaries. Antigravity handled the boilerplate, the complex mathematical decompositions, and the cross-module synchronization.

The result? A framework that outperforms Apache Commons Math by **15x** in double-precision linear algebra, entirely open-sourced.

If you want to see what heavily guided, AI-augmented engineering looks like at scale, check out the repository: https://github.com/Episteme-HTC/Episteme

I'm moving on to new projects and handing this over to the community, but I'm happy to answer any questions about the workflow and prompt engineering used to achieve this!

u/Initial-War-6965 — 3 days ago