Nvidia, Intel and ARM have published a draft specification for a common AI interchange format aimed at faster and more efficient system development. The proposed “8-bit floating point” standard, known as FP8, will potentially accelerate both training and operating the systems by reducing memory usage and optimizing interconnect bandwidth. The lower precision number format is a key factor in driving efficiency. Transformer networks, in particular, benefit from an 8-bit floating point precision, and having a common interchange format should facilitate interoperability advances for both hardware and software platforms. Continue reading Nvidia, Intel and ARM Publish New FP8 AI Interchange Format

Nvidia has begun previewing its latest H100 Tensor Core GPU, promising “an order-of-magnitude performance leap for large-scale AI and HPC” over previous iterations, according to the company. Nvidia founder and CEO Jensen Huang announced the Hopper earlier this year, and IT professionals’ website ServeTheHome recently had a chance to see a H100 SXM5 module demonstrated. Consuming up to 700W in an effort to deliver 60 FP64 Tensor teraflops, the module — which features 80 billion transistors and has 8448/16896 FP64/FP32 cores in addition to 538 Tensor cores — is described as “monstrous” in the best way. Continue reading Nvidia Touts New H100 GPU and Grace CPU Superchip for AI

Nvidia CEO Jensen Huang announced a host of new AI tech geared toward data centers at the GTC 2022 conference this week. Available in Q3, the H100 Tensor Core GPUs are built on the company’s new Hopper GPU architecture. Huang described the H100 as the next “engine of the world’s AI infrastructures.” Hopper debuts in Nvidia DGX H100 systems designed for enterprise. With data centers, “companies are manufacturing intelligence and operating giant AI factories,” Huang said, speaking from a real-time virtual environment in the firm’s Omniverse 3D simulation platform. Continue reading Nvidia Introduces New Architecture to Power AI Data Centers