STAC recently performed a STAC-AI™ LANG6 (Inference-Only) audit of the STAC-AI Pack for TensorRT-LLM (Rev D), running on a Supermicro SYS-222C-TN server hosting NVIDIA RTX PRO 6000 GPUs managed by Red Hat OpenShift 4.20. (ID: SMCI260303)
Enterprises face significant hurdles in the quest for new AI functionality in their business processes and products. According to IDC research, 50% of respondents worldwide say that less than half of their AI-related projects have delivered measurable business outcomes, and only 11.4% report that they are obtaining measurable business results from more than 75% of their AI projects.
Introducing 4 storage essentials for enterprise AI success; explore how to right-size data lakes (for aggregating enterprise data) and lakehouses (for running analytics) to power success in the AI era.
STAC recently performed a STAC-AI™ LANG6 (Inference-Only) audit of the STAC-AI Pack for TensorRT-LLM (Rev D), running on a Supermicro SYS-222C-TN server hosting NVIDIA RTX PRO 6000 GPUs managed by Red Hat OpenShift 4.20. (ID: SMCI260303)
Enterprises face significant hurdles in the quest for new AI functionality in their business processes and products. According to IDC research, 50% of respondents worldwide say that less than half of their AI-related projects have delivered measurable business outcomes, and only 11.4% report that they are obtaining measurable business results from more than 75% of their AI projects.
Introducing 4 storage essentials for enterprise AI success; explore how to right-size data lakes (for aggregating enterprise data) and lakehouses (for running analytics) to power success in the AI era.
Adopting Direct-to-Chip Liquid Cooling to Help Address Exponentially Increasing Power Consumption
Neoclouds Move AI Builders Faster – From Inspiration to Empire
STAC recently performed a STAC-M3™ benchmark audit on a solution featuring the KDB+ database system sharded across six Supermicro Storage SuperServer SSG-222B-NE3X24R servers. (ID: KDB250929)
STAC recently performed a STAC-ML™ Markets (Inference) benchmark audit on a stack including an NVIDIA GH200 Grace Hopper Superchip in a Supermicro ARS-111GL-NHR server. (ID: SMC250910)
Traditional retail is more competitive than ever. As AI advances, retailers have the opportunity to unlock new efficiencies and incredible shopper experiences. But success isn’t guaranteed. It requires enterprise-grade edge systems with rack-simplicity. That’s where Supermicro and AMD come in.
Supermicro and AMD offer solutions to address the numerous challenges involved with successfully transitioning enterprise generative AI initiatives from Proof of concept to production, providing high-performance servers optimized for AI training and inferencing.
Supercharged AI & HPC workloads drive critical business momentum
Supermicro servers with AMD ROCm vLLM—Let’s Get Moving!
Modernize your data center with AMD, Red Hat, and Supermicro
How to accelerate AI and omnichannel analytics for sustainable growth.
Data lakehouses combine the best of both worlds—the massive scalability of a data lake, with the structured, transactional power of a data warehouse. This means all your data can coexist, be properly governed, and easily accessed for smarter insights. Here’s how a data lakehouse gives you the upper hand in the AI era.
The traditional method of cooling data centers – air conditioning – is no longer sufficient or efficient for the intense heat generated by the significant number of HPE and AI servers, making liquid cooling not only a better option but a requirement. Here are 6 of the most important advantages liquid cooling has over traditional air cooling.
