Datanami
EnterpriseAI
HPCwire Japan
QCwire
HPC & AI Wall Street
Nvidia Announces Four Supercomputers, with Two in Taiwan
May 29, 2023
At the Computex event in Taipei this week, Nvidia announced four new systems equipped with its Grace- and Hopper-generation hardware, including two in Taiwan. T Read more…
Nvidia, HPE Announce Superchip-Powered ‘Isambard 3’ Supercomputer
May 21, 2023
Nvidia is ramping up deployment of its Superchips – amalgamated chips that include either two CPUs (the Grace CPU Superchip) or a CPU and a GPU (the Grace Hop Read more…
Into the Alps: What Exactly Is the New Swiss Supercomputer Infrastructure?
April 5, 2023
About two years ago, the Swiss National Supercomputing Centre (CSCS), HPE and Nvidia announced plans to launch a powerful new supercomputer in 2023 to replace P Read more…
Nvidia’s Hopper GPUs Enter ‘Full Production,’ DGXs Delayed Until Q1
September 20, 2022
Just about six months ago, Nvidia’s spring GTC event saw the announcement of its hotly anticipated Hopper GPU architecture. Now, the GPU giant is announcing t Read more…
Nvidia, Intel to Power Atos-Built MareNostrum 5 Supercomputer
June 16, 2022
The long-troubled, hotly anticipated MareNostrum 5 supercomputer finally has a vendor: Atos, which will be supplying a system that includes both Nvidia and Inte Read more…
Nvidia’s Grace Superchips to Debut on Venado Supercomputer
May 30, 2022
In March, Nvidia unveiled its two new Grace Superchips: the Grace CPU Superchip, aimed at datacenters, comprises dual Arm-based Grace CPU chips; the Grace Hopper Superchip, meanwhile, combines a Grace CPU with a Hopper GPU in a single SoC. Now, at ISC 2022... Read more…
Nvidia Launches Four Arm-based Grace Server Designs
May 25, 2022
Nvidia is lining up Arm-based server platforms for a diverse range of HPC, AI and cloud applications. The new systems employ Nvidia’s custom Grace Arm CPUs in Read more…
Nvidia Serves Up Its First Arm Datacenter CPU ‘Grace’ During Kitchen Keynote
April 12, 2021
Today at Nvidia’s annual spring GPU Technology Conference (GTC), held virtually once more due to the pandemic, the company unveiled its first ever Arm-based CPU, called Grace in honor of the famous American programmer Grace Hopper. The announcement of the new... Read more…
- Click Here for More Headlines
Leading Solution Providers
ISC 2023 Booth Videos
 |
 |
 |
 |
 |
 |
Whitepaper
Powering Up Automotive Simulation: Why Migrating to the Cloud is a Game Changer
The increasing complexity of electric vehicles result in large and complex computational models for simulations that demand enormous compute resources. On-premises high-performance computing (HPC) clusters and computer-aided engineering (CAE) tools are commonly used but some limitations occur when the models are too big or when multiple iterations need to be done in a very short term, leading to a lack of available compute resources. In this hybrid approach, cloud computing offers a flexible and cost-effective alternative, allowing engineers to utilize the latest hardware and software on-demand. Ansys Gateway powered by AWS, a cloud-based simulation software platform, drives efficiencies in automotive engineering simulations. Complete Ansys simulation and CAE/CAD developments can be managed in the cloud with access to AWS’s latest hardware instances, providing significant runtime acceleration.
Two recent studies show how Ansys Gateway powered by AWS can balance run times and costs, making it a compelling solution for automotive development.
Download Now
Sponsored by ANSYS
Whitepaper
How to Save 80% with TotalCAE Managed On-prem Clusters and Cloud
Five Recommendations to Optimize Data Pipelines
When building AI systems at scale, managing the flow of data can make or break a business. The various stages of the AI data pipeline pose unique challenges that can disrupt or misdirect the flow of data, ultimately impacting the effectiveness of AI storage and systems.
With so many applications and diverse requirements for data types, management systems, workloads, and compliance regulations, these challenges are only amplified. Without a clear, continuous flow of data throughout the AI data lifecycle, AI models can perform poorly or even dangerously.
To ensure your AI systems are optimized, follow these five essential steps to eliminate bottlenecks and maximize efficiency.
Download Now
Sponsored by TotalCAE
Advanced Scale Career Development & Workforce Enhancement Center
Featured Advanced Scale Jobs:
HPCwire Resource Library
-
Whitepaper: Streamlining AI Data Management
-
Whitepaper: Reducing Bias and Increasing Accuracy in AI Models
-
Whitepaper: A New Standard in CAE Solutions for Manufacturing
-
Whitepaper: Porting CUDA Applications to Run on AMD GPUs
-
Whitepaper: QCT HPC BeeGFS Storage: A Performance Environment for I/O Intensive Workloads
-
Webcasts and webinars: Leveraging Exascale Era Technology for Advanced Computer-Aided Engineering
HPCwire Product Showcase
© 2023 HPCwire. All Rights Reserved. A Tabor Communications Publication
HPCwire is a registered trademark of Tabor Communications, Inc. Use of this site is governed by our Terms of Use and Privacy Policy.
Reproduction in whole or in part in any form or medium without express written permission of Tabor Communications, Inc. is prohibited.