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Processing Deep Learning Workloads with Intel

To deliver a frictionless interaction with the user, systems should be capable to analyze millions of small files very quickly, providing what seems like a real-time answer to the inquiry. The required computer demand is met by leveraging a cluster of servers that utilize a GPU to aid the CPU in inspecting information. The weak link in these designs is the storage architecture.
Much of the AI spotlight is focused on deep learning, a branch of machine learning that uses neural networks to comprehend complex and unstructured data (training) and use that understanding to classify, recognize and process new inputs (inference). Deep learning is delivering breakthroughs in areas like image recognition, speech recognition, natural language processing and other complex tasks.
Deep learning workloads require a tremendous amount of computational power to run complex mathematical algorithms and process huge amounts of data. While GPUs have been used for some deep learning training applications, they don’t necessarily have a performance edge for deep learning inference.
That’s why many organizations are running AI workloads, Intel® Xeon® Scalable processors provide an ideal computational foundation. Intel Xeon Scalable processors are optimized for AI, scale up quickly and seamlessly for 2.1x faster deep learning performance over the previous generations, and offer server-class reliability and workload flexibility.
Intel’s optimizations for popular deep learning frameworks have significantly increased processor-level performance, but there is, even more, we can do. In particular, system level optimizations can greatly increase the performance of CNN workloads on Intel® Xeon® and Intel® Xeon Phi™ processors used in deep learning and high-performance computing applications.
Most organizations have at least 35 percent free utilization of processing capacity, if not more. This means they have could be obtaining better ROI from their infrastructure investments. With Intel Xeon Scalable processors, they can leverage this unused capacity to implement AI while still meeting the needs of other applications.

A Processor Designed for Deep Learning

Moving forward, Intel has also developed the Intel® Nervana™ Neural Network Processor (NNP), the world’s first processor specifically designed from the ground up for deep learning. The Intel Nervana NNP promises to further enhance medical imaging and other healthcare applications.
With new thoughts in mind, Tyrone Systems is pleased to be engaged with different industries. We know that our collective work is helping move the needle – with even more promise and unlimited possibilities for the future.

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