What is the best GPU for Machine Learning 2020?

RTX 2060 (6 GB): if you want to explore deep learning in your spare time. RTX 2070 or 2080 (8 GB): if you are serious about deep learning, but your GPU budget is $600-800. Eight GB of VRAM can fit the majority of models. RTX 2080 Ti (11 GB): if you are serious about deep learning and your GPU budget is ~$1,200.

Is RTX 3090 better than Titan RTX?

Even where things look equal, such as the amount of memory, the RTX 3090 edges it, thanks to the faster GDDR6X memory used. Again, the fact that the RTX 3090 is so much cheaper than the Titan RTX, and yet could offer better performance from a gaming perspective, is great.

Why is RTX Titan so expensive?

TLDR: the Titan V has far more expensive components and is marketed to companies rather than individuals. Professional / datacenter tools are always expensive, probably partly by the cost of production and partly by brand. So, RTX can be 15x slower than GTX Titan V on a datacenter / cloud protein folding.

Why is the Titan RTX so good?

Not only does Titan RTX sport more CUDA cores than GeForce RTX 2080 Ti, it also offers a higher GPU Boost clock rating (1,770 MHz vs. 1,635 MHz). As such, its peak single-precision rate increases to 16.3 TFLOPS. This is one area where Titan RTX loses big to its predecessor.

How does the Titan V compare to the Tesla V100?

The Titan V has the full double precision (fp64) performance of the Tesla V100. Volta has the highest ratio of double (fp64) to single (fp32) performance of any architecture NVIDA has produced. The ratio is 1:2, that means fp64 is half the performance of fp32.

Is the NVIDIA TITAN V good for machine learning?

In this post, Lambda Labs benchmarks the Titan V’s Deep Learning / Machine Learning performance and compares it to other commonly used GPUs. We use the Titan V to train ResNet-50, ResNet-152, Inception v3, Inception v4, VGG-16, AlexNet, and SSD300.

Is the Tesla 2080 faster than the Titan V with FP16?

35\% faster than the 2080 with FP32, 47\% faster with FP16, and 25\% more expensive. 96\% as fast as the Titan V with FP32, 3\% faster with FP16, and ~1/2 of the cost. 80\% as fast as the Tesla V100 with FP32, 82\% as fast with FP16, and ~1/5 of the cost.

What is the best GPU for V100?

GPUs: EVGA XC RTX 2080 Ti GPU TU102, ASUS 1080 Ti Turbo GP102, NVIDIA Titan V, and Gigabyte RTX 2080. The V100 benchmark utilized an AWS P3 instance with an E5-2686 v4 (16 core) and 244 GB DDR4 RAM.