for EfficientDet-D0, it is necessary to use RTX 2070, at $ 450 (34 FPS), with an accuracy of 33.8% AP / 52.2% AP50; I.e. YOLOv4 requires 5 times less expensive equipment and yet is more accurate than EfficientDet-D2 (Google-TensorFlow). You can use EfficientDet-D0 (Google-TensorFlow) on cheap equipment, but then the accuracy will be 10% AP lower.
Dec 29, 2020 · The recently released Nvidia RTX 2060 SUPER is supposedly positioned in-between the RTX 2060 and RTX 2070. The performance of the 2060 SUPER though tells a different story, as it is much closer, and in many benchmarks on par, with an RTX 2070 at a significantly lower price.
Aug 14, 2019 · The RTX 2070Super has a single sub-link (like the RTX 2080). The RTX 2080Ti and RTX Titan (as well as the RTX Quadro's) have dual sub-links. This means that the 2070-Super has 1/2 the NVLINK bandwidth as the 2080Ti and RTX Titan.
All training and inference by winning and runner-up teams were performed on various NVIDIA GPUs including TITAN Xp GPUs to V100s, to RTX 2070 with frameworks such as the cuDNN-accelerated PyTorch deep learning framework. Dataset curation for the Challenge was done for the four tracks using NVIDIA DGX Systems, and NVIDIA TITAN RTX and 2080 Ti GPUs.
TensorFlow performance with 1-2 RTX Titan GPU's. I am including relevant results for all of my recent testing with the RTX GPU's. The two latest posts being, P2P peer-to-peer on NVIDIA RTX 2080Ti vs GTX 1080Ti GPUs and RTX 2080Ti with NVLINK - TensorFlow Performance (Includes Comparison with GTX 1080Ti, RTX 2070, 2080, 2080Ti and Titan V).Both of these posts may be of interest.
Jun 02, 2020 · The RTX cards were specially designed to support real-time ray tracing which made the video looked more beautiful. They were first announced in 2018 and uses Turing architecture. These RTX cards include RTX 2060, RTX 2070, RTX 2080, RTX 2080Ti, and Super counterparts of 2060 and 2070.
Cette RTX 2070 semble être un monstre en termes de calculs. Je me souviens avoir réussi à lancer un algorithme de reconnaissance d’images (articles de e-commerce) avec mon CPU (AMD 1700X), ça avait pris une plombe (de souvenir plusieurs heures) !!!