IBM Opens Access to Latest Osprey Quantum Processor at 413 Qubits

May 9, 2023

Yesterday, IBM announced its newest quantum processor – Osprey – introduced last December is now accessible as an “as an exploratory technical demonstrati Read more…

Quantum Bits: IBM-Cleveland Clinic Launch; D-Wave Adds Solver; DOE/AWS Offer QICK

March 20, 2023

IBM today launched the first installation of an IBM Quantum System One at a collaborator site in the U.S. – this one is at the Cleveland Clinic where IBM’s Read more…

Google Sheds Quantum Supremacy Notoriety to Focus on Stability

February 27, 2023

Google over the last few years has thrown shade at today's fastest supercomputers with dubious claims of achieving "quantum supremacy." The tech giant may be ba Read more…

IBM Introduces ‘Vela’ Cloud AI Supercomputer Powered by Intel, Nvidia

February 8, 2023

Nearly five years ago, Oak Ridge National Laboratory launched the IBM-built Summit supercomputer, powered by IBM and Nvidia hardware, to the top of the Top500 l Read more…

Shutterstock 1194728515

Quantum-circuit Cutting Fills a Gaping Quantum Computing Hole

December 5, 2022

A universal quantum computer with a million qubits will solve a wide range of problems, but even then, offloading entire problems to a quantum circuit may not be the best use of resources. With that in mind, companies and researchers are paying more attention to the concept of quantum-circuit cutting, which breaks down large quantum circuits into smaller fragments for execution across... Read more…

IBM Quantum Summit: Osprey Flies; Error Handling Progress; Quantum-centric Supercomputing

December 1, 2022

Part scorecard, part grand vision, IBM’s annual Quantum Summit held last month is a fascinating snapshot of IBM’s progress, evolving technology roadmap, and Read more…

Dell, AMD, IBM, and Strangeworks Dig into Quantum’s Future

October 27, 2022

What’s the quantum computing fuss all about? Should you jump into the game or run as fast as you can away from it? A fascinating panel with committed quantum players, IBM and Strangeworks, and traditional computing powerhouses, Dell (systems) and AMD (chips), tackled this topic at the HPC + AI on Wall Street conference held earlier this... Read more…

IBM Reveals New Diamondback Tape Library Archival Storage

October 25, 2022

IBM has introduced a new high-density archival storage system, the IBM Diamondback Tape Library. Unveiled at the 2022 Open Compute Project Global Summit, the new storage solution is physically air-gapped, meaning data is stored as an isolated backup copy with no physical network connection. IBM says Diamondback provides a significantly... Read more…

  • arrow
  • Click Here for More Headlines
  • arrow

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:

SUBSCRIBE for monthly job listings and articles on HPC careers.

HPCwire Resource Library

HPCwire Product Showcase

Subscribe to the Monthly
Technology Product Showcase:

HPCwire