Iterate at the speed of thought. Keras is the most used deep learning framework among top-5 winning teams on Kaggle.Because Keras makes it easier to run new experiments, it empowers you to try more ideas than your competition, faster.
TensorRT 6.0 DALI 0.15 NCCL 2.5 IndeX 2.1 OptiX 7.0 RAPIDS 0.10 Spark XGBoost 3x in 2 Years 2017 2019 2018 Time to Solution 27 Hours 20 Hours 10 Hours Amber Chroma GROMACS GTC LAMMPS MILC NAMD QE SPECFEM3D TensorFlow VASP Benchmark Application: Amber [PME-Cellulose_NVE], Chroma [szscl21_24_128], GROMACS [ADH Dodec: Dev Prototype], GTC
CPU 2 x Intel Xeon Gold 6148 2.4GHz CPU: RAM: 192GB DDR4-2666: SSD: 500 GB SSD: GPU: 1, 2, 4x NVIDIA GeForce RTX 2080 Ti (blower model) OS: Ubuntu Server 16.04
Fine Tune BERT for Text Classification with TensorFlow. Join for Free. Duration (mins) ... Optimize TensorFlow Models For Deployment with TensorRT. 1 hour and 55 minutes.
DAWNBench is a benchmark suite for end-to-end deep learning training and inference. Computation time and cost are critical resources in building deep models, yet many existing benchmarks focus solely on model accuracy.
Nov 02, 2020 · For the BERT language processing model, two NVIDIA A100 GPUs outperform eight NVIDIA T4 GPUs and three NVIDIA RTX8000 GPUs. However, the performance of three NVIDIA RTX8000 GPUs is a little better than that of eight NVIDIA T4 GPUs.
TensorRT optimized BERT Sample on GitHub Faster Transformer : C++ API, TensorRT plugin, and TensorFlow OP MXNet Gluon-NLP with AMP support for BERT (training and inference)