Datanami
EnterpriseAI
HPCwire Japan
QCwire
HPC & AI Wall Street
US DOD Ends Cloud Drama with $9 Billion Contract to Top Cloud Providers
December 8, 2022
The U.S. Department of Defense wielded its JEDI powers to procure public cloud services with a diplomatic end to a feud between Amazon and Google to win the multi-billion dollar contract. The DoD broke up a $9 billion contract between the top four cloud providers – Google, Amazon, Microsoft and Oracle – for the Joint Warfighting Cloud Capability initiative, which will bring the defense branches – Air Force, Army... Read more…
Deploying Kubernetes Based HPC Clusters in a Multi-Cloud Environment
September 2, 2021
With cloud computing as the de facto deployment model in large enterprises, the usage of multiple clouds within a single enterprise has become omnipresent. The Read more…
Algorithm-Processor Combo Speeds Microservices
February 4, 2020
Computer scientists at the University of Michigan have come up with a faster way to schedule cloud microservices via a new algorithm running on a custom processor. The platform, called Q-Zilla, is based on a widely used scheduling algorithm... Read more…
HPC Cloud on a Roll; Pure Play High Performance Storage Dips
June 28, 2018
HPC in the cloud is one of those “insanely great” ideas that, failing to fire, year after year recedes before our expectations. Until, that is, last year, a Read more…
IBM Bare Metal Cloud Targets AI with New P100 GPUs
April 5, 2017
IBM announced today that it will be adding Nvidia P100 graphics processors to its Bluemix cloud later this month, becoming the "first major global cloud vendor Read more…
Rethinking HPC Platforms for ‘Second Gen’ Applications
February 22, 2017
Just what constitutes HPC and how best to support it is a keen topic currently. A new paper posted last week on arXiv.org – Rethinking HPC Platforms: Challeng Read more…
Stathis Papaefstathiou Takes the R&D Reins at Cray
January 26, 2017
Earlier this month, Cray announced that tech veteran Stathis Papaefstathiou had joined the ranks of the iconic supercomputing company. As senior vice president Read more…
Merged Dell-EMC Targets Hybrid Cloud
September 7, 2016
If bigger is better, the new IT behemoth Dell Technologies Inc. that combines the holdings of Dell and storage leader EMC Corp. fits the bill with the completion a $60 billion merger of cloud, storage, virtualization and hardware components that will seek to be all things to all enterprise IT customers. 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.