Igniting the Next Generation of Deep Learning

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Increased processing power, massive amounts of data, and the development of more advanced algorithms have brought deep learning to the forefront, and TensorFlow has emerged as one of the world’s most popular machine learning frameworks. Penporn Koanantakool, Google Senior Software Engineer, and Ramesh, Intel Principal Engineer, share how their teams are collaborating to optimize TensorFlow for the latest Intel technologies using oneAPI Deep Neural Network Library (oneDNN). The result: remarkable performance gains that will benefit applications spanning natural language processing, image and object recognition, autonomous vehicles, fraud detection, medical diagnosis and treatment, and much more. Intel-optimized TensorFlow is now made available through Intel AI Analytics Toolkit and is being used within Google Cloud Platform and a Google Health project.

To learn more:
Intel oneAPI Deep Neural Network Library
Intel AI Analytics Toolkit
Accelerating DeepVariant with Intel’s AVX-512 Optimizations
TensorFlow-MKL int8 Optimizations for Cascade Lake
TensorFlow-MKL bfloat16 Optimizations for Cooper Lake

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Posted in: Artificial Intelligence, Audio Podcast, Code Together, Intel