In an interesting twist on quantum-inspired work making its way into traditional HPC – and in this case a step further into cloud-based HPC – AWS today introduced Palace, short for PArallel, …
A Google-led program to design and manufacture chips for free is becoming popular among researchers and computer enthusiasts. The search giant's open silicon program is providing the tools for an …
June 30, 2022
You may be surprised how ready Python is for heterogeneous programming, and how easy it is to use today. Our first three articles about heterogeneous programming focused primarily on C++ as we ponder “how to enable programming in the face of an explosion of hardware diversity that is coming?” For a refresher on what motivates this question... Read more…
May 30, 2022
During a special address at ISC today, general manager and vice president of Accelerated Computing at Nvidia, Ian Buck, shared promising news for the future of Read more…
April 26, 2022
In the third of a series of guest posts on heterogeneous computing, James Reinders shares experiences surrounding the creation of ASCI Red and ties that system' Read more…
February 3, 2022
Commentary -- In the second of a series of guest posts on heterogeneous computing, James Reinders, who returned to Intel last year after a short “retirement, Read more…
January 20, 2022
Researchers in Australia and the U.S. have made exciting headway in the quantum computing arms race. A multi-institutional team including the University of New Read more…
November 10, 2021
It was with a hint of nostalgia that Argonne Lab’s Bill Allcock described the Argonne Leadership Computing Facility’s (ALCF) decision to switch to a commercially-supported workload management suite after 20+ years spent developing and using ALCF’s custom workload manager, Cobalt. Argonne National Laboratory announced today that it is deploying Altair PBS Professional across the organization’s HPC systems and clusters. “From the inception of ALCF, we wrote our own scheduler called Cobalt... Read more…
February 9, 2021
The Khronos Group today formally launched SYCL 2020, the parallel programming framework based on IS0 standard C++ that has been gaining traction in HPC and will Read more…
January 13, 2021
The rapid adoption of Julia, the open source, high level programing language with roots at MIT, shows no sign of slowing according to data from Julialang.org. I Read more…
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.
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.
© 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.