With Turing fast approaching for consumer cards, Nvidia is bringing new GPUs to market for data center and the HPC universe as well. Last week, the company announced its new T4 GPU family, specifically intended for AI and inference workloads and taking over for the Tesla P4 in this role.
Nvidia claims the new GPU is up to 12x more power-efficient than its Pascal predecessor. The company has released a suite of benchmark tests showing the T4 blasting past its competition, though as always, such vendor results should be treated with a grain of salt. We’ve seen Intel release test results claiming its own Xeon processors are excellent at inference, for example. The degree to which this is or is not true is likely the result of optimization flags and specific test configurations or scenarios.
Specs on the new T4 are impressive. 16GB of GDDR6 feeds a cluster of 2560 CUDA cores and 320 Turing Tensor cores, all within a svelte 75W power profile. THG reports that the Tesla T4 has an INT4 and even an experimental INT1 mode, with up to 65TFLOPS of FP16, 130 TFLOPS of INT8, and 260 TFLOPS of INT4 performance on-tap. The older P4, in contrast, offers 5.5TFLOPS of FP16 and 22 TFLOPS of INT8. Nvidia says there are optimizations for AI video applications as well and a buffed-up decoder that can handle up to 38 HD video streams simultaneously.
Alongside the new T4, Nvidia is also launching new tools for development, including a refresh of its TensorRT software package and a new, Turing-optimized version of CUDA (CUDA 10) that includes libraries and models that have been optimized for Turing. Watch for the battle over inferencing to heat up in 2019. Intel is pushing into that space with Xeon, AMD wants a piece of the pie for its Radeon Instinct line-up of machine accelerators, Nvidia’s Turing is going to play in this space, and then, come 2020, Intel will have GPU architectures of its own to compete with. And that’s before you consider the custom accelerators that everyone from Fujitsu to Google has been building and deploying.
It’s not always clear how these technologies will impact consumers; Nvidia’s push to introduce ray tracing and DLSS are the most prominent example we have so far of a company working to take the designs it’s built for HPC and bringing them over to the consumer space. We don’t yet know if it’ll work. But there’s clearly a multi-way fight brewing between the largest titans of the industry — and Nvidia wants to take an early leadership position with its new line of GPUs.
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