D-Wave Systems, a pioneer in quantum annealing-based computing, today announced significant upgrades to its constrained quadratic model (CQM) hybrid solver that should make it easier to use and a …
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 …
Find out which 12 HPC luminaries are being recognized this year for driving innovation within their particular fields.
October 4, 2022
Last week the Quantum Economic Development Consortium (QED-C) released a new report – Public-Private Partnerships in Quantum Computing – that calls for incr Read more…
September 8, 2022
The steady maturation of MLCommons/MLPerf as an AI benchmarking tool was apparent in today’s release of MLPerf v2.1 Inference results. Twenty-one organization Read more…
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…
June 9, 2022
Imagine some years hence the HPC landscape, already confusing in its heterogeneity, also includes quantum computing resources. How does a user choose from among Read more…
May 30, 2022
While echoes of the pandemic continue rippling through the HPC landscape – primarily lingering supply chain issues – the outlook for the HPC market writ large is strong, according to Hyperion Research, which delivered its ISC 2022 HPC market update today. Last year, HPC spending (on premise, cloud, and AI) neared $35 billion and is on track to reach... Read more…
May 30, 2022
The 59th installment of the Top500 list, issued today from ISC 2022 in Hamburg, Germany, officially marks a new era in supercomputing with the debut of the first-ever exascale system on the list. Frontier, deployed at the Department of Energy’s Oak Ridge National Laboratory, achieved 1.102 exaflops in its fastest High Performance Linpack run, which was completed... Read more…
May 4, 2022
President Joe Biden today issued an Executive Order and a National Security Memorandum boosting the national focus on quantum information sciences (QIS), including quantum computing and cybersecurity concerns. There is currently a global race heating up to leverage QIS for economic and security purposes. The U.S., China, Europe, Japan, the U.K., and many others have mounted well-funded, expanding efforts... Read more…
April 6, 2022
MLCommons today released its latest MLPerf inferencing results, with another strong showing by Nvidia accelerators inside a diverse array of systems. Roughly fo Read more…
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.
Karlsruhe Institute of Technology (KIT) is an elite public research university located in Karlsruhe, Germany and is engaged in a broad range of disciplines in natural sciences, engineering, economics, humanities, and social sciences. For institutions like KIT, HPC has become indispensable to cutting-edge research in these areas.
KIT’s HoreKa supercomputer supports hundreds of research initiatives including a project aimed at predicting when the Earth’s ozone layer will be fully healed. With HoreKa, projects like these can process larger amounts of data enabling researchers to deepen their understanding of highly complex natural processes.
Read this case study to learn how KIT implemented their supercomputer powered by Lenovo ThinkSystem servers, featuring Lenovo Neptune™ liquid cooling technology, to attain higher performance while reducing power consumption.
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