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Oil and Gas Supercloud Clears Out Remaining Knights Landing Inventory: All 38,000 Wafers
March 13, 2019
The McCloud HPC service being built by Australia’s DownUnder GeoSolutions (DUG) outside Houston is set to become the largest oil and gas cloud in the world th Read more…
Requiem for a Phi: Knights Landing Discontinued
July 25, 2018
On Monday, Intel made public its end of life strategy for the Knights Landing "KNL" Phi product set. The announcement makes official what has already been wide Read more…
NERSC Scales Scientific Deep Learning to 15 Petaflops
August 28, 2017
A collaborative effort between Intel, NERSC and Stanford has delivered the first 15-petaflops deep learning software running on HPC platforms and is, according Read more…
How ‘Knights Mill’ Gets Its Deep Learning Flops
June 22, 2017
Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…
Advancing Modular Supercomputing with DEEP and DEEP-ER Architectures
February 24, 2017
Knowing that the jump to exascale will require novel architectural approaches capable of delivering dramatic efficiency and performance gains, researchers aroun Read more…
Dell Knights Landing Machine Sets New STAC Records
November 2, 2016
The Securities Technology Analysis Center, commonly known as STAC, has released a new report characterizing the performance of the Knight Landing-based Dell PowerEdge C6320p server on the STAC-A2 benchmarking suite, widely used by the financial services industry to test and evaluate computing platforms. The Dell machine has set new records for both the baseline Greeks benchmark and the large Greeks benchmark. Read more…
Why 2016 Is the Most Important Year in HPC in Over Two Decades
August 23, 2016
In 1994, two NASA employees connected 16 commodity workstations together using a standard Ethernet LAN and installed open-source message passing software that a Read more…
Intel Launches Silicon Photonics Chip, Previews Next-Gen Phi for AI
August 18, 2016
At the Intel Developer Forum, held in San Francisco this week, Intel Senior Vice President and General Manager Diane Bryant announced the launch of Intel's Silicon Photonics product line and teased a brand-new Phi product, codenamed "Knights Mill," aimed at machine learning workloads. Read more…
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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.
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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.
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