Nvidia unveiled what it is calling the world’s most powerful AI processing system, the Blackwell GPU, purpose built to power real-time generative AI on trillion-parameter large language models at what the company says will be up to 25x less cost and energy consumption than its predecessors. Blackwell’s capabilities will usher in what the company promises will be a new era in generative AI computing. News from Nvidia’s GTC 2024 developer conference included the NIM software platform, purpose built to streamline the setup of custom and pre-trained AI models in a production environment, and the DGX SuperPOD server, powered by Blackwell. Continue reading GTC: Nvidia Unveils Blackwell GPU for Trillion-Parameter LLMs

Nvidia has issued a software update for its formidable NeMo Megatron giant language training model, increasing efficiency and speed. Barely a year since Nvidia unveiled Megatron, this latest improvement further leverages the transformer engine architecture that has become synonymous with deep learning since Google introduced the concept in 2017. New features result in what Nvidia says is a 5x reduction in memory requirements and up to a 30 percent gain in speed for models as large as 1 trillion parameters, making NeMo Megatron better at handling transformer tasks across the entire stack. Continue reading Nvidia Turbo Charges NeMo Megatron Large Training Model

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

Data center and colocation provider Equinix is inviting companies to test-drive the NVIDIA DGX A100 system at its International Business Exchange (IBX) data center in Los Angeles (the company currently has more than 200 IBX centers in 52 markets). This site is currently the only place in the world where companies can take advantage of the DGX A100 to test drive their AI equipment. According to the Equinix testbed landing page, “The test drive solution brings together industry-leading AI hardware from NVIDIA and NetApp alongside best-in-class software technology from Core Scientific, all directly connected on Platform Equinix.” Continue reading Equinix Invites Companies to Test-Drive AI System at LA IBX

The University of Florida (UF) and Nvidia joined forces to enhance the former’s HiPerGator supercomputer with DGX SuperPOD architecture. Set to go online by early 2021, HiPerGator will deliver 700 petaflops (one quadrillion floating-point operations per second), making it the fastest academic AI supercomputer. UF and Nvidia said the HiPerGator will enable the application of AI to a range of studies, including “rising seas, aging populations, data security, personalized medicine, urban transportation and food insecurity.” Continue reading Nvidia and University of Florida Partner on AI Supercomputer