UAE’s Mohamed bin Zayed University of AI to Acquire NVIDIA-AMD-driven HPC System from HPE

October 11, 2022 — DUBAI, United Arab Emirates — Hewlett Packard Enterprise (NYSE: HPE) today announced it is building a supercomputer for Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), which is dedicated to AI, designed to accelerate scientific discovery. The goal is to enable the university to run complex AI models with large data […]

HPC-AI Chips in the News: NVIDIA, AMD Ensnared in US-China Trade War; Arm Sues Qualcomm

NVIDIA and AMD, makers of advanced GPUs used in HPC-AI workloads, became embroiled this week in the deteriorating relations and ongoing trade war between the US and the People’s Republic of China. Yesterday, Nvidia said it has been prohibited by the US government from selling to the PRC its A100 Tensor Core GPU, on the […]

PCIe 4.0 Rugged Short-Depth Server Appliance for Edge AI HPC

AI Transportable™ applications such as autonomous vehicles, situational command and control, aerospace, and high-complexity video-based inference and security often require real-time decision-making with limited 5G or no network connectivity to a centralized datacenter. Commercial-grade servers and expansion products are not suitable for these applications due to harsh physical environments and the transportable nature of the deployments. To address these use-cases, One Stop Systems has developed the industry leading PCIe Gen4 HPC server appliance designed for performance without compromise in a compact, rugged, and transportable form-factor.

Lenovo Claims an HPC First for Liquid-Cooled Nvidia A100 GPU Servers

Today, Lenovo introduced the ThinkSystem SD650-N V2 server, which the company said is the first direct-to-node (DTN) liquid-cooled server for Nvidia A100 Tensor Core GPUs. It includes four board-mounted A100 GPUs in a 1U system delivering up to 3PFLOPS of compute performance in a single rack. The server uses Lenovo Neptune liquid cooling, which the […]

AI Workflow Scalability through Expansion

In this special guest feature, Tim Miller, Braden Cooper, Product Marketing Manager at One Stop Systems (OSS), suggests that for AI inferencing platforms, the data must be processed in real time to make the split-second decisions that are required to maximize effectiveness.  Without compromising the size of the data set, the best way to scale the model training speed is to add modular data processing nodes.

AWS Launches Nvidia GPU-Driven EC2 P4d Instances for AI, HPC

Amazon Web Services today announced the general availability of Amazon EC2 P4d Instances powered by Nvidia GPUs with EC2 UltraClusters capability delivering 3x faster performance, up to 60 percent lower cost, and 2.5x more GPU memory for machine learning training and HPC workloads compared to previous-generation P3 instances, according to AWS. The company said P4d […]

Lenovo Standing Up Liquid-cooled Neptune System at Max Planck Society

Lenovo is installing a Neptune liquid cooled supercomputer at the Max Planck Society, a delivery that began two months ago and is scheduled to be completed early next year. The €20 million project includes a 100,000-core Neptune comprised of Lenovo ThinkSystem servers with  Intel CPUs (unspecified) and Nvidia Tesla A100 GPUs, software and operational support, […]

Lenovo to deploy 17 Petaflop supercomputer at KIT in Germany

Today Lenovo announced a contract for a 17 petaflop supercomputer at Karlsruhe Institute of Technology (KIT) in Germany. Called HoreKa, the system will come online this Fall and will be handed over to the scientific communities by summer 2021. The procurement contract is reportedly on the order of EUR 15 million. “The result is an innovative hybrid system with almost 60.000 next-generation Intel Xeon Scalable Processor cores and 220 terabytes of main memory as well as 740 NVIDIA A100 Tensor Core GPUs. A non-blocking NVIDIA Mellanox InfiniBand HDR network with 200 GBit/s per port is used for communication between the nodes. Two Spectrum Scale parallel file systems offer a total storage capacity of more than 15 petabytes.”