VRAM of GPUs for training and reasoning about fov-3dgs HOT 2 CLOSED

Thanks for your reply! 5GB is very friendly for most embedded development boards, It's really a commendable job! At 2024-07-11 05:14:04, "linwk20" ***@***.***> wrote: We performed training on an RTX 4090 GPU and used a Jetson for inference rendering. The 4090's 24GB memory is sufficient for all scenes tested during training. For inference on Jetson, we needed to disable data caching on GPU memory to prevent out-of-memory (OOM) errors. We achieved this by using fps_mode as shown in this code snippet. After disabling data caching, we successfully ran all scenes on Jetson. It generally takes less than 5GB memory if i remember correctly. — Reply to this email directly, view it on GitHub, or unsubscribe. You are receiving this because you authored the thread.Message ID: ***@***.***>