Real-Time Neural Graphics: 3D Gaussian Splatting, NeRF Reconstruction, and Unreal Pixel Streaming

Accelerating spatial computing and immersive visualization with cloud-based hardware ray tracing, fast photogrammetry training, and low-latency NVENC video streaming.

The rapid rise of 3D Gaussian Splatting (3DGS) has revolutionized computer graphics, replacing slow volumetric neural radiance fields with millions of real-time rasterizable 3D gaussians.

However, training dense spatial scenes from drone photogrammetry or high-resolution camera rigs requires immense memory bandwidth and sustained GPU boost clocks that quickly throttle laptops and thermal-limited local workstations.

NovaPod's high-density RTX 4090 and RTX 5090 instances provide 24 GB to 32 GB of dedicated high-speed GDDR6X/GDDR7 VRAM, allowing artists and spatial engineers to reconstruct complex city-scale scenes in under six minutes.

With pre-configured Unreal Engine Pixel Streaming templates and hardware NVENC encoding, interactive 4K 60fps viewports can be streamed directly to web browsers worldwide with under 16ms of glass-to-glass latency.

NovaPod CLI Quick Launch

np launch \
  --gpu RTX_5090 \
  --template novapod/unreal-pixel-streaming:UE5.5 \
  --disk 120GB \
  --name spatial-gaussian-renderer

Key Architecture TakeawayNeural radiance fields and 3D Gaussian Splatting have merged computer graphics with machine learning. NovaPod provides high-clock workstation GPUs with hardware NVENC encoders for interactive real-time cloud rendering and WebRTC streaming.

Experience High-Density AI Compute

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