ASUS Servers Announce AI Developments at NVIDIA GTC
Offering NVIDIA-Certified Servers with H100 Tensor Core GPU and AI Enterprise software suite
• ASUS AI demonstrations at NVIDIA GTC: MLPerf Training v2.0 results and methodology, plus success story in academic AI advancement
• NVIDIA H100 Tensor Core GPU: Both NVIDIA AI Enterprise Software and enterprise supported by latest ASUS NVIDIA-Certified servers
• Next-gen NVIDIA Grace server development: ASUS speeds up development using NVIDIA CPUs to empower the future of data centers
Taipei, Taiwan, September 21, 2022 — ASUS, the leading IT company in server systems, server motherboards and workstations, today announced its presence at NVIDIA® GTC – a developer conference for the era of AI and the metaverse. ASUS will focus on three demonstrations outlining its strategic developments in AI, including: the methodology behind ASUS MLPerf Training v2.0 results that achieved multiple breakthrough records; a success story exploring the building of an academic AI data center at King Abdullah University of Science and Technology (KAUST) in Saudi Arabia; and a research AI data center created in conjunction with the National Health Research Institute in Taiwan.
GTC session topic – ASUS GPU server solutions in MLPerf Training v2.0
MLPerf benchmark results help advance machine-learning performance and efficiency, allowing researchers to evaluate the efficacy of AI training and inference based on specific server configurations. Since joining MLCommons in 2021, ASUS has gained multiple breakthrough records in the data center closed division across six AI-benchmark tasks in AI training and inferencing MLPerf Training v2.0. At the ASUS GTC session, senior ASUS software engineers will share the methodology for achieving these world-class results — as well as the company’s efforts to deliver more efficient AI workflows through machine learning.
Academic and research AI case sharing with ASUS AI solutions
A key academic AI breakthrough from ASUS this year has been the collaboration with KAUST – an institution that is the ranked 8th-fastest-rising young universities for its research output in 2019 — that has adopted the ASUS ESC N4A-E11 HGX A100 server platform for contributing to its AI research portfolio. This server has secured seven top performance results in MLPerf Training 2.0 with the configuration of an AMD EPYC™ 7773X GPU and four NVIDIA® HGX A100 GPUs. This server is in particular suitable for academic research due to its single-CPU with four SXM architecture. In MLPerf Training 2.0, this single-CPU ESC N4A-E11 outperformed dual-CPU servers by a speed of up to 3.14 minutes.
ASUS has also been collaborating with one of the top data centers in Taiwan — the National Health Research Institutes (NHRI). This is dedicated to medical research, biotech innovations from drug discovery, genomics analysis and assisted AI. ASUS has provided a comprehensive AI solution in the form of RS720-E10 server and NVIDIA DGX, along with private-cloud software to envision academic AI in the future. As a Cloud Native Computing Foundation (CNCF) Certified Kubernetes Software Conformance provider, ASUS is empowered to ignite more innovations and business opportunities in AI fields.
ASUS GPU servers support NVIDIA H100 Tensor Core GPU and NVIDIA AI Enterprise
ASUS will offer NVIDIA-Certified servers with the latest NVIDIA H100 GPU and the NVIDIA AI Enterprise software suite — with availability expected by the end of the year. The NVIDIA H100 GPU delivers unprecedented performance, scalability and security to every data center, and includes the NVIDIA AI Enterprise software suite for streamlined AI development and deployment. ASUS NVIDIA-Certified servers featuring 350W TDP H100 GPUs are optimized for the best performance on GPU-accelerated workloads, as well as validated for key capabilities in manageability, scalability and security.
Since the release of the NVIDIA Grace CPU superchip in April, ASUS has continued working with NVIDIA to speed the development of next-generation servers. This Arm-based CPU server will revamp current hardware architecture and deliver better performance, improved power consumption and a highly flexible hardware design — and ASUS expects to release more detail in 2023.