The L2 cache has also been cut from 6MB to 4.5MB so it is correct to think of this as a lower memory bandwidth and capacity version of the Tesla V100. 900GB/s on the Tesla V100, but it is relatively close. Memory is down to “only” 12GB per card v. Tensor performance is rated at 110 TFLOPS versus 112 for the Tesla V100. If you wanted to use 1-2 Volta class GPUs in a system, the NVIDIA Titan V is going to be the hot commodity. Why the NVIDIA Titan V is a Watershed Moment This is the technology those involved in deep learning want. Like the NVIDIA Tesla V100, the Titan V has the 640 Tensor Core array along with the 5120 CUDA cores. The real target audience is very easy to see: the deep learning / AI crowd. Instead, the NVIDIA Titan V is intended for workstation development environments that need floating point precision beyond FP32. Although it has four video outputs, it is not intended for gaming. HotHardware.The NVIDIA Titan V is officially out. "NVIDIA 12nm FinFET Volta GPU Architecture Reportedly Replacing Pascal In 2017". "Nvidia Volta, IBM Power9 Land Contracts for New US Government Supercomputers". "IBM, Nvidia rev HPC engines in next-gen supercomputer push". "IBM, Nvidia land $325M supercomputer deal".
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