AI Solutions Group and AMAX's HPC announced its line of advanced server systems powered by NVIDIA A100 that bring AI training, analytics, and inference to a combined yet scalable platform. The resilient system design has accommodated conventional full length and height of 400W SXM A100 or 250W PCIe 4.0 cards for multi-instance burstable workloads, making them the perfect building blocks for up-to-date AI data centers.
AceleMax source design data center servers of AMAX provide both single and double AMD EPYC 7002 CPU choices, 4 or 8 NVIDIA A100 PCIe GPUs to a maximum of five AI performance's 510 PetaOPS through direct-attached PCI-E 4.0 x16 CPU-to-GPU lanes for highest bandwidth and lowest latency. These systems can support up to 2 extra high-performance PCI-E 4.0 extension slots for multiple uses, including NVIDIA Mellanox 200 Gb/s InfiniBand cards, SAS interface cards, or 200 Gigabit Ethernet to fulfill the requirement of high-bandwidth applications.
AMAX’s VP of Technology and Product Development, Dr. Rene Meyer, stated that the value of a company improves when the IT teams and data science teams align to improve the total productivity and results without worrying about the infrastructure. With the power of collaborative partner ecosystems, NVIDIA is taking AI computing to new levels. Dr. Meyer claimed that the company has a great partner history and its rack integration hubs are available in bulk to build and deploy the next generation of A100-based solutions into data centers, irrespective of its size.
NVIDIA’s accelerated computing’s senior director of product management, Paresh Kharya, stated that AceleMax and its upgraded features help to improve and simplify AI computing productivity in the enterprise AI environments. Adding flexibility and power to NVIDIA InfiniBand, Ethernet networking, and NVIDIA A100 PCIe GPU, further allowing AMAX customers to optimize their businesses for lower cost and high utilization.
AMAX, as an NVIDIA Elite Partner, delivers a complete range of GPU-integrated solutions optimized for detailed learning at any scale.
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