Penguin Solutions walks through OriginAI, their “AI factory” concept: pre-validated rack architectures that balance GPU compute, storage, and networking, then arrive as an integrated system so teams spend less time wiring a bespoke stack and more time running training and inference. The conversation also nods to the company’s Linux heritage and why repeatable operations matter once you move beyond a few test nodes. https://www.penguinsolutions.com/
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On the GPU roadmap, OriginAI is being updated to include NVIDIA DGX B300 platforms based on the Blackwell generation, targeting up to 72 petaFLOPs of training throughput and 144 petaFLOPs of inference performance per system, with availability referenced for early 2026. It also highlights NVIDIA RTX PRO 6000 GPUs (dual-slot PCIe Gen5, 96GB GDDR7) for more space- and power-aware builds, plus support for AMD Instinct MI355 where that fits the workload mix.
The hardware is presented as modular: servers can come from partner OEM lines (including Dell) or Penguin-branded designs, storage is selectable via partners such as DDN, VAST Data, Pure Storage, or VDURA, and fabrics can be InfiniBand or Ethernet depending on topology and protocol needs. The point is to ship a known-good configuration, with in-factory integration and burn-in testing, so on-site deployment looks more like commissioning than a science project.
The demo then pivots to ICE ClusterWare, the layer that turns bare metal into an operable cluster: BMC control via IPMI or Redfish, PXE boot, DHCP/IP assignment, and image-based provisioning from Linux distros like Rocky/RHEL-style or Ubuntu. Filmed at Supercomputing SC25 in St. Louis, the console shows hundreds of nodes moving from offline to provisioning, with Grafana-style telemetry and a “chain booting” fan-out method to avoid stampeding-herd overload during mass bring-up.
What stands out is the operations focus: failure is assumed (ECC and memory events, NIC issues, GPU faults), and ClusterWare classifies signals, runs health checks, and applies auto-remediation policies—from automated reboots to ticket creation for a swap—while newer releases add network-isolated multi-tenancy for shared clusters. Zooming out, Penguin cites sovereign AI builds like SK Telecom’s Korea cluster reaching production-readiness in August 2025, and also shows it can integrate emerging HPC silicon—including liquid-cooled Open Compute platforms built around NextSilicon accelerator tech for national-lab style work—under one validated architecture scope.
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