Nvidia CEO Jensen Huang took to the stage at GTC Japan to announce the company's latest advancements in AI, which includes the new Tesla T4 GPU. This new GPU, which Nvidia designed for inference workloads in the data center, leverages the same Turing microarchitecture as Nvidia's forthcoming GeForce RTX 20-series gaming graphics cards.
But the Tesla T4 is a unique graphics card designed specifically for AI inference workloads, like powering neural networks that process video, speech, search engines, and images. Nvidia's previous-gen Tesla P4 fulfilled this role in the past.
|Nvidia Tesla T4 (TFLOPS)||65||130||260|
|Nvidia Tesla P4 (TFLOPS)||5.5||22||-|
The Tesla T4 GPU comes bristling with 16GB of GDDR6, which 320 Turning Tensor cores, and 2,560 CUDA cores. The GPU supports mixed-precision, such as FP32, FP16, INT8, and INT4 (performance above). The low-profile 75W card slots into a standard PCIe slot in servers, but it doesn't require an external power source, like a 6-pin connector. Nvidia tells us that the die does feature RT Cores, just like the desktop models, but that they will be useful for raytracing or VDI (Virtual Desktop Infrastructure), which implies they will be unused for most inference workloads.
The Tesla T4 also features an INT4 and (experimental) INT1 precision mode, which is a notable advancement over its predecessor.
As expected, the card supports all the major deep learning frameworks, such as PyTorch, TensorFlow, MXNet, and Caffee2. Nvidia also offers its TensorRT 5, a new version of Nvdia's deep learning inference optimizer and runtime engine that supports Turing Tensor Cores and multi-precision workloads.