| 10/05 | 8 |
Tooling for optimized, validated, reproducible GPU-accelerated Kubernetes clusters via version-locked recipes and deployment-ready bundles.
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| 09/25 | 8 |
Python-first machine learning compilation framework that generates minimum deployable modules and supports universal deployment across targets.
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| 10/05 | 7 |
Cross-platform remediation service detecting, classifying, and automatically resolving runtime GPU node faults in Kubernetes clusters.
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| 10/02 | 7 |
AI agent builder that creates sandboxed agents using microVMs to install software, run code, and access GPU from your app.
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| 09/24 | 7 |
GPU-focused monitoring and diagnostics tool that detects GPU and fabric errors and reports critical system metrics.
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| 09/24 | 7 |
GPU.js is a JavaScript GPGPU library that transpiles simple functions into GPU shader code and runs them with CPU fallback when needed.
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| 09/20 | 7 |
Fast language focused on enforcing application laws through formal proofs and compiling to high-performance executables.
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| 09/19 | 7 |
Go library for embedded vector search and GGUF BERT-based semantic embeddings with optional GPU acceleration.
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| 10/06 | 6 |
TypeScript library enhancing the WebGPU API for type-safe resource management.
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| 09/14 | 6 |
Platform for deploying, managing, and running GPU-accelerated inference, streaming, and batch workloads across worker clusters.
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| 09/30 | 5 |
Kubernetes operator managing self-hosted LLM inference on NVIDIA GPUs and Apple Silicon, with autoscaling, model routing, and OpenAI-compatible API.
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| 10/10 | 4 |
Self-hosted retrieval-augmented generation engine that keeps all document processing and answering offline on a single binary, with cited sources.
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| 10/05 | 3 |
Kubernetes API providing a single declarative interface to orchestrate multi-node AI inference with topology-aware placement, hierarchical gang scheduling, and autoscaling.
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