In this video from Moabcon 2013, Bill Magro from Intel presents: Productive Parallel Programming for Intel Xeon Phi Coprocessors.
View the Slides on Slideshare or check out the Moabcon 2013 Video Gallery.
Industry Perspectives
IBM's Plan to bring Machine Learning Capabilities to Data Scientists Everywhere
Over at the IBM Blog, IBM Fellow Hillary Hunter writes that the company anticipates that the world’s volume of digital data will exceed 44 zettabytes, an astounding number. "IBM has worked to build the industry’s most complete data science platform. Integrated with NVIDIA GPUs and software designed specifically for AI and the most data-intensive workloads, IBM has infused AI into offerings that clients can access regardless of their deployment model. Today, we take the next step in that journey in announcing the next evolution of our collaboration with NVIDIA. We plan to leverage their new data science toolkit, RAPIDS, across our portfolio so that our clients can enhance the performance of machine learning and data analytics." [Read More...]
White Papers
PLASTER: A Framework for Deep Learning Performance
Both hardware and software advances in deep learning (DL), a type of ML, appear to be catalysts for the early stages of a phenomenal AI growth trend. Download the new white paper from NVIDIA that addresses the challenges described in PLASTER, which is important in any deep learning solution, and it is especially useful for developing and delivering the inference engines underpinning AI-based services.
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