| 06/01 | 7 |
Tooling for optimized, validated, reproducible GPU-accelerated Kubernetes clusters via version-locked recipes and deployment-ready bundles.
|
| 06/01 | 7 |
Pure Go GPU computing ecosystem offering WebGPU-compatible APIs with selectable Rust or native backends and zero CGO.
|
| 05/30 | 7 |
Hyperparallelized, shard-based experiment framework for rapid LLM customization, RAG, context engineering, and fine-tuning with real-time control.
|
| 05/27 | 7 |
Pure Go GPU computing ecosystem offering WebGPU-compatible APIs with selectable Rust or native backends and zero CGO.
|
| 05/27 | 7 |
Pure Go WebGPU implementation providing W3C-compliant API and multiple hardware backends without Rust or CGO.
|
| 05/31 | 6 |
Pure Go GPU computing ecosystem offering WebGPU-compatible APIs with selectable Rust or native backends and zero CGO.
|
| 05/31 | 6 |
Pure Go GPU computing ecosystem offering WebGPU-compatible APIs with selectable Rust or native backends and zero CGO.
|
| 05/29 | 6 |
TypeScript library enhancing the WebGPU API for type-safe resource management.
|
| 05/28 | 6 |
Kubernetes operator managing self-hosted LLM inference on NVIDIA GPUs and Apple Silicon, with autoscaling, model routing, and OpenAI-compatible API.
|
| 05/28 | 6 |
TypeScript library enhancing the WebGPU API for type-safe resource management.
|
| 05/27 | 5 |
Pure Go WebGPU implementation providing W3C-compliant API and multiple hardware backends without Rust or CGO.
|
| 05/26 | 5 |
Pure Go WebGPU implementation providing W3C-compliant API and multiple hardware backends without Rust or CGO.
|
| 05/26 | 5 |
Pure Go WebGPU implementation providing W3C-compliant API and multiple hardware backends without Rust or CGO.
|