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Google’s New AI-Focused ‘A3’ Supercomputer Has 26,000 GPUs
May 10, 2023
Cloud providers are building armies of GPUs to provide more AI firepower. Google is joining the gang with a new supercomputer that has almost 2.5 times the number of GPUs than the world’s third-fastest supercomputer called LUMI. Google announced an AI supercomputer with 26,000 GPUs at its developer conference on Wednesday. Read more…
Groq Designs Chip that Hands Over Controls to Software
August 25, 2022
Groq has deconstructed the conventional CPU, and designed its chip in which software takes over control of the chip. The Groq Tensor Streaming Processor Architecture follows a growing trend of software controlling system functions, which has happened in autonomous cars, networking and other hardware. The architecture hands over hardware controls of the chip to the compiler. The chip has integrated... Read more…
Video: Sneak Preview of the AI Hardware Summit
August 19, 2022
Next month the AI Hardware Summit returns to the Bay Area, bringing AI technologists and end users together to share ideas and get up to speed on all the latest AI hardware developments. The event – which takes place September 13-15, 2022, at the Santa Clara Marriott, Calif. – will be co-located with the Edge AI Summit. Both events are organized by... Read more…
AI Silicon Startup Graphcore Launches Channel Partner Program
September 23, 2020
AI compute platform vendor Graphcore has launched its first formal global channel partner program to promote and boost the sales of its AI processors and blade computing products. The formalized, all-new Graphcore Elite Partner Program follows the company’s past history of working with several... 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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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.
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