Synexs Custom PyTorch Build — RTX 5080
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Synexs Custom PyTorch Model (RTX 5080 CUDA Build)
🧠 Author: Synexs AI Engineering Unit
🔧 Tools Used: Visual Studio 2022, CUDA Toolkit 12.1, CMake 4.0.1, Ninja, Windows 10 x64
📍 Platform: Synexs Custom PC w/ RTX 5080 GPU
🔓 Summary
This build represents a custom-compiled version of PyTorch, tailored for the NVIDIA RTX 5080 (SM_120 architecture).
As of now, no official PyTorch binaries support this architecture — so we compiled it from source using advanced build flags and environment overrides.
This enables:
💡 Why Build from Source?
- 🔧 Precompiled PyTorch fails on RTX 5080 (SM_120)
- ⚠️ CUDA runtime errors:
no kernel image is available - ✅ Manual compilation unlocks the full power of the next-gen GPU
✅ What We Achieved
- ✅ Stable Diffusion WebUI launches
- ✅ CUDA errors bypassed via
--allow-unsupported-compiler - ✅ PyTorch fully GPU-enabled with CUDA 12.1 + SM_120
- ✅ Environment ready for symbolic mutation & agent deployment
📦 Next Steps
This custom PyTorch engine will serve as the base for:
- ➕ Synexs symbolic intelligence simulation
- ➕ Local image/video generation via Stable Diffusion + Deforum
- ➕ Symbolic model fine-tuning (DreamBooth, LoRA, Embeddings)
- ➕ Real-time AI agents running on physical devices
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