IBM and Nvidia partner again to produce a tower-sized DGX server that combines high-end IBM hardware with Nvidia GPUs and is specific for AI. Credit: IBM IBM and Nvidia further enhanced their hardware relationship with the announcement of a new turnkey AI solution that combines IBM Spectrum Scale scale-out file storage with Nvidia’s GPU-based AI server. The name is a mouthful: IBM SpectrumAI with Nvidia DGX. It combines Spectrum Scale, a high performance Flash-based storage system, with Nvidia’s DGX-1 server, which is designed specifically for AI. In addition to the regular GPU cores, the V100 processor comes with special AI chips called Tensor Cores optimized to run machine learning workloads. The box comes with a rack of nine Nvidia DGX-1 servers, with a total of with 72 Nvidia V100 Tensor Core GPUs. Storage key to AI success The box addresses an overlooked element to successful AI, and that’s storage. It’s recognized that for AI to work, vast amounts of data is required, and GPUs have taken the lead in AI processing because of their massive parallelism. The trick is getting those terabytes of data off the disk. It’s pretty much impossible with hard disks, but even flash isn’t normally fast enough to feed the GPUs. IBM claimed the storage scales “practically linearly” and offers 120GB/s of data throughput in a rack. That’s due to Spectrum Scale’s cluster file management, which accelerates random read data requirements to feed multiple GPUs, since GPUs are usually much faster than even flash disks and storage is usually the bottleneck. The two companies boast that the server offers “the highest performance in any tested converged system” while supporting data science practices and AI data pipelines, including data prep, data training, inference, and archival. Spectrum Discover, a part of SpectrumAI, makes data accessible via data cataloging and indexing. And thanks to an API in SpectrumAI, it re-uses the workflows created by Spectrum Discover, reducing time spent on data prep. The Nvidia DGX software stack is designed for maximized GPU-accelerated training performance, using Nvidia’s new RAPIDS framework to accelerate data science workflow. The whole thing can be deployed and used immediately with no complex installation required. This is the latest in the IBM/Nvidia partnership, which has seen IBM adopt Nvidia’s high-speed interconnect called NVLink in its Power servers and the creation of Summit, the world’s fastest supercomputer, which uses IBM Power9 processors and Nvidia Tesla processors. The two companies also helped build the two fastest supercomputers on the biannual Top 500 supercomputer list: Summit and Sierra, both used by the Department of Energy. Related content news analysis AMD launches Instinct AI accelerator to compete with Nvidia AMD enters the AI acceleration game with broad industry support. First shipping product is the Dell PowerEdge XE9680 with AMD Instinct MI300X. By Andy Patrizio Dec 07, 2023 6 mins CPUs and Processors Generative AI Data Center news analysis Western Digital keeps HDDs relevant with major capacity boost Western Digital and rival Seagate are finding new ways to pack data onto disk platters, keeping them relevant in the age of solid-state drives (SSD). By Andy Patrizio Dec 06, 2023 4 mins Enterprise Storage Data Center news Omdia: AI boosts server spending but unit sales still plunge A rush to build AI capacity using expensive coprocessors is jacking up the prices of servers, says research firm Omdia. By Andy Patrizio Dec 04, 2023 4 mins CPUs and Processors Generative AI Data Center news AWS and Nvidia partner on Project Ceiba, a GPU-powered AI supercomputer The companies are extending their AI partnership, and one key initiative is a supercomputer that will be integrated with AWS services and used by Nvidia’s own R&D teams. By Andy Patrizio Nov 30, 2023 3 mins CPUs and Processors Generative AI Supercomputers Podcasts Videos Resources Events NEWSLETTERS Newsletter Promo Module Test Description for newsletter promo module. Please enter a valid email address Subscribe