Artificial intelligence. It’s perhaps the water cooler topic of our decade, or perhaps the rest of this century. And nowhere is that more true than in high performance computing. An insideHPC special report, sponsored by Intel, explores one of the most interesting and cutting-edge areas of AI, and that’s the convergence of deep learning, data and HPC. This convergence is making AI technology more accessible to data scientists with no coding background required.
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In fact, according to the report, sponsored by Intel, HPC and the artificial intelligence communities are converging as they are both running similar types of data and compute intensive workloads on HPC hardware, including supercomputers, institutional clusters or the cloud.
“The emerging AI community on HPC infrastructure is critical to achieving the vision of AI: machines that don’t just crunch numbers, but help us make better and more informed complex decisions.” – Pradeep Dubey, Intel Fellow and Director of Parallel Computing Lab
The insideHPC guide begins by giving an overview of the HPC landscape. Understanding popular deep learning terms and value propositions are key. The report goes in-depth on the ins and outs of topics such as training, inferencing, scalability and more. Inferencing is top of mind for many deep learning experts, as this is the operation that makes data derived models valuable because they can work to predict the future and perform recognition tasks better than humans.
The report also covers recent breakthroughs in these areas. For example, a breakthrough in deep learning training outlined in the special report is a result of work by collaborators with the Intel Parallel Computing Center that works to bring deep learning training to everyone, regardless of whether you run a leadership class supercomputer or a simple workstation.
The AI-HPC report also explores specific customer use case results, as well. These include Boston Children’s Hospital’s efforts to to use AI to better diagnose various forms of damage in the human brain, as well as Carnegie Mellon University’s efforts to utilize games and game theory to address the challenges of learning in a limited information environment, among others.
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Continue reading for a breakdown of hot topics in the artificial intelligence software ecosystem, as well as what hardware is out there to support AI software. Software explored includes Intel Nirvana Graph, a scalable intermediate language. Hardware discussed includes Intel Xeon Scalable processors and Intel Xeon Phi CPUs, as well as the Intel Neural Network Processor, FPGAs, Neuromorphic chips, Intel Omni-Path Architecture and more.
This insideHPC special report covers the following information in detail:
- An overview of artificial intelligence in the HPC landscape
- Customer use case results
- The software ecosystem
- Hardware to support the AI software ecosystem
Download the full white paper, “insideHPC Special Report: AI-HPC is Happening Now,” courtesy of Intel, to learn more about the potential of AI and the convergence of AI-HPC.
