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Unleashing the Power of OpenFOAM for CFD
OpenFOAM offers widely used open-source tools for computational fluid dynamics, but scalability can be a challenge. Research indicates that Intel® processors may help users scale up their OpenFO …
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Xilinx Moves FPGAs Deeper into Datacenters
Three Chinese infrastructure vendors are embracing FPGA technology as a way of accelerating datacenter workloads. FPGA specialist Xilinx Inc. announced during a developer forum in Beijing this we …
IBM Introduces AI OpenScale to Spur Artificial Intelligence Adoption and Transparency
ARMONK, N.Y., Oct. 16, 2018 -- IBM today introduced AI OpenScale, a new technology platform that addresses key challenges of artificial intelligence (AI) adoption, such as concerns over how …
HPCwire's People to Watch in 2018
Click here to find out more about the luminaries, influencers and thought leaders poised to push our industry forward in the coming year!
Building a Diverse Workforce for Next-Generation Analytics and AI
October 15, 2018
High-performance computing (HPC) has a well-known diversity problem, and groups such as Women in HPC are working to address it. But while the diversity challeng Read more…
Nvidia, Oracle Expand Cloud GPU Ties for AI, HPC
October 11, 2018
Oracle is collaborating with Nvidia to bring the GPU leader’s unified AI and HPC platform to the public cloud for accelerating analytics and machine learning workloads. The move makes Oracle the first public cloud vendor to support Nvidia’s HGX-2 platform, the partners said this week. Read more…
Kings College London Tackles Medical Imaging with AI
October 11, 2018
Nvidia announced this week at GTC Europe that Kings College London would deploy Nvidia’s DGX-2 and Clara medical imaging analysis platform to improve radiology and pathology practices. This is the first Clara deployment in Europe and evidence of AI’s growing adoption in health care where for years a wide variety of instruments, not least imaging devices, have been producing large datasets. Read more…
Nvidia Platform Pushes GPUs into Machine Learning, High Performance Data Analytics
October 10, 2018
GPU leader Nvidia, generally associated with deep learning, autonomous vehicles and other higher-end enterprise and scientific workloads (and gaming, of course) Read more…
SyLabs Releases Singularity 3.0 Container Platform; Cites AI Support
October 8, 2018
SyLabs today introduced Singularity version 3.0 of its container software platform targeting HPC and advanced enterprise workloads. The latest release provides Read more…
In-Memory Neural Net Chip Cuts Data Movement
October 8, 2018
A university-industry research team is reporting a performance advance for neural networks with the development of a chip with potential applications for image recognition in autonomous vehicles and robots. The chip design relies on in-memory processing and the replacement of standard transistors with capacitors used to store electrical charges. Read more…
DDN, Nvidia Blueprint Unified AI Appliance with Up to 9 DGX-1s
October 4, 2018
Continuing the roll-out of the A3I (Accelerated, Any-Scale AI) storage strategy kicked off in June, DDN today announced a new set of solutions that combine the Read more…
D-Wave Is Latest to Offer Quantum Cloud Platform
October 4, 2018
D-Wave Systems today launched its cloud platform for quantum computing – Leap – which combines a development environment, community features, and "real-time Read more…
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Whitepaper:
Strategies for the Spectrum of Cloud Adoptions
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Sponsored by Microsoft
Whitepaper:
Adaptive Flexibility is the Future of Supercomputing – The Arm advantage for HPC workloads
Researchers in academic labs and commercial R&D groups continue to need more compute capacity, which means leveraging the latest innovations in HPC technologies as well as an assortment of resources to meet the unique needs of different workloads. Increasingly, systems based on Arm processors are stepping into that role, offering low power consumption and strategic advantages for HPC workloads.
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Sponsored by Cray
Whitepaper:
HPC Goes Mainstream
Whether it's for fraud detection, personalized medicine, manufacturing, smart cities, autonomous vehicles and many other areas, advanced-scale computing has exploded beyond the realm of academia and government and into the private sector. And with data-intensive workloads on the rise, commercial users are turning to HPC-based infrastructure to run the AI, ML and cognitive computing applications that their organizations depend on.
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