Changes

: With Nvidia [https://en.wikipedia.org/wiki/Volta_(microarchitecture) Volta] series TensorCores were introduced. They offer fp16*fp16FP16xFP16+fp32FP32, matrix-multiplication-accumulate-units, used to accelerate neural networks.<ref>[https://on-demand.gputechconf.com/gtc/2017/presentation/s7798-luke-durant-inside-volta.pdf INSIDE VOLTA]</ref> Turing's 2nd gen TensorCores add FP16, INT8, INT4 optimized computation.<ref>[https://www.anandtech.com/show/13282/nvidia-turing-architecture-deep-dive/6 AnandTech - Nvidia Turing Deep Dive page 6]</ref> Amperes's 3rd gen adds support for bfloat16BF16, TensorFloat-32 (TF32), FP64 and sparsity acceleration.<ref>[https://en.wikipedia.org/wiki/Ampere_(microarchitecture)#Details Wikipedia - Ampere microarchitecture]</ref>