Installation and configuration of high-performance computing (HPC) systems can be a considerable challenge that requires skilled IT pros to\u00a0set up the software stack, for example, and optimize it for maximum performance \u2013 it isn't like building a PC with parts bought off NewEgg.\nGigaIO, which specializes in infrastructure for AI and technical computing, is looking to simplify the task. The vendor recently announced a self-contained, single-node system with 32 configured GPUs in the box to offer simplified deployment of AI and supercomputing resources.\nUp to now, the only way to harness 32 GPUs would require four servers with eight GPUs apiece. There would be latency to contend with, as the servers communicate over networking protocols, and all that hardware would consume floor space.\nWhat makes GigaIO's device\u00a0\u2013 called SuperNODE \u2013 notable is that it offers a choice of GPUs: up to 32 AMD Instinct MI210 GPUs or 24 NVIDIA A100s, plus up to 1PB storage to a single off-the-shelf server. The MI210 is a step down in performance from the top-of-the-line MI250\u00a0card (at least for now) that's used in the Frontier exaFLOP supercomputer. It has a few less cores and less memory but is still based on AMD\u2019s Radeon GPU technology.\n\u201cAMD collaborates with startup innovators like GigaIO in order to bring unique solutions to the evolving workload demands of AI and HPC,\u201d said Andrew Dieckmann, corporate vice president and general manager of the data center and accelerated processing group at AMD, in a statement. \u201cThe SuperNODE system created by GigaIO and powered by AMD Instinct accelerators offers compelling TCO for both traditional HPC and generative AI workloads.\u201d\nSuperNODE is built on GigaIO\u2019s FabreX custom fabric technology, a memory-centric fabric that reduces latency from system memory of one server communicating with other servers in the system to just 200ns. This enables the FabreX Gen4 implementation to scale up to 512Gbits\/sec bandwidth.\nFabreX can connect a variety of resources, including accelerators such as GPUs, DPUs, TPUs, FPGAs and SoCs; storage devices, such as NVMe, PCIe native storage; and other I\/O resources connected to compute nodes. Basically, anything that uses a PCI Express bus can be connected to FabreX for direct device-to-device communication across the same fabric.\nSuperNODE has three modes of operation: beast mode, for applications that make the most of many or all GPUs; freestyle mode, where every user gets their own GPU to use for processing purposes; and swarm mode, where applications run on multiple servers.\nSuperNODE can run existing applications written on popular AI frameworks such as PyTorch and TensorFlow without requiring modification. It uses Nvidia\u2019s Bright Cluster Manager Data Science software to manage and configure the environment and handle scheduling as well as container management.\nSuperNODE is available now from GigaIO.