Super Micro Computer has announced two new systems designed for artificial intelligence (AI) deep learning applications.

These applications look to leverage the third-generation NVIDIA HGX technology with the NVIDIA A100 Tensor Core GPUs as well as full support for the NVIDIA A100 GPUs across the company’s portfolio of 1U, 2U, 4U and 10U GPU servers. NVIDIA A100 is the first elastic, multi-instance GPU that unifies training, inference, HPC, and analytics.

“Expanding upon our portfolio of GPU systems and NVIDIA HGX-2 system technology, Supermicro is introducing a new 2U system implementing the NVIDIA HGX A100 4 GPU board (formerly codenamed Redstone) and a 4U system based on the NVIDIA HGX A100 8 GPU board (formerly codenamed Delta) delivering 5 PetaFLOPS of AI performance,” said Charles Liang, CEO and president of Supermicro.

“These new systems will significantly boost performance on all accelerated workloads for HPC, data analytics, deep learning training and deep learning inference.”

Supermicro’s 2U system leverages the HGX A100 4 GPU board with four direct-attached A100 Tensor Core GPUs using PCI-E 4.0 for maximum performance and NVIDIA NVLink for high-speed GPU-to-GPU interconnects. This GPU system looks to accelerate compute, networking and storage performance with support for one PCI-E 4.0 x8 and up to four PCI-E 4.0 x16 expansion slots for GPUDirect RDMA high-speed network cards and storage such as InfiniBand HDR, which supports up to 200Gb per second bandwidth.

“AI models are exploding in complexity as they take on next-level challenges such as accurate conversational AI, deep recommender systems and personalised medicine,” said Ian Buck, general manager and VP of accelerated computing at NVIDIA. “By implementing the HGX A100 platform into their new servers, Supermicro provides customers the powerful performance and massive scalability that enable researchers to train the most complex AI networks at unprecedented speed.”

Optimised for AI and machine learning, Supermicro’s 4U system supports eight A100 Tensor Core GPUs. The 4U form factor with eight GPUs is intended for customers that want to scale their deployment as their processing requirements expand. The new 4U system will have one NVIDIA HGX A100 8 GPU board with eight A100 GPUs all-to-all connected with NVIDIA NVSwitch for up to 600GB per second GPU-to-GPU bandwidth and eight expansion slots for GPUDirect RDMA high-speed network cards. Ideal for deep learning training, data centres can use this scale-up platform to create next-gen AI and maximize data scientists’ productivity with support for ten x16 expansion slots.

Customers can expect a significant performance boost across Supermicro’s extensive portfolio of multi-GPU servers when they are equipped with the new A100 GPUs. For maximum acceleration, Supermicro’s new A+ GPU system supports up to eight full-height double-wide (or single-wide) GPUs via direct-attach PCI-E 4.0 x16 CPU-to-GPU lanes without any PCI-E switch for the lowest latency and highest bandwidth. The system also supports up to three additional high-performance PCI-E 4.0 expansion slots for a variety of uses, including high-performance networking connectivity up to 100G. An additional AIOM slot supports a Supermicro AIOM card or an OCP 3.0 mezzanine card.

To deliver enhanced security and performance at the edge, Supermicro is planning to add the new NVIDIA EGXB A100 configuration to its edge server portfolio. The EGX A100 converged accelerator combines a Mellanox SmartNIC with GPUs powered by the new NVIDIA Ampere architecture, so enterprises can run AI at the edge more securely.