accelerate deep learning
Accelerate Deep Learning on Raspberry Pi
Getting Started with Raspberry Pi even if you are a beginner, Deep Learning Basics, Object Detection Models - Pros and Cons of each CNN, Setup and Install Movidius Neural Compute Stick (NCS) SDK, Currently, the OpenVINO is available for Raspbian, so the NCS2 is already compatible with the Raspberry Pi, but this course is mainly for the Movidius (NCS version 1).
Cray launches AI products to accelerate deep learning - AI News
Supercomputer manufacturer Cray has introduced a new set of four artificial intelligence (AI) products to accelerate the adoption of deep learning in science and enterprise. The new products include Cray Accel AI Lab, which aims to advance the development of deep learning technologies and workflows, and Cray Accel AI Offerings, featured with NVIDIA Tesla V100 GPU accelerators. The new Cray Urika-XC software suite, which brings graph analytics, deep learning, and big data analytics tools the Cray XC supercomputers, will now include the TensorFlow computational framework and enhancements to the Cray software environment that are particularly designed to accelerate machine learning frameworks. Also included is a collaboration agreement with Intel. The Cray-Intel team up will deliver a productised software stack for deep learning at scale on Cray systems and leverage Intel's AI technologies to advance the state-of-the-art in distributed deep learning and machine learning.
Exploiting Typical Values to Accelerate Deep Learning
To deliver the hardware computation power advances needed to support deep learning innovations, identifying deep learning properties that designers could potentially exploit is invaluable. This article articulates our strategy and overviews several value properties of deep learning models that we identified and some of our hardware designs that exploit them to reduce computation, and on- and off-chip storage and communication.
Microsoft releases open-source toolkit to accelerate deep learning - The AI Blog
A toolkit used across Microsoft to achieve breakthroughs in artificial intelligence is generally available to the public via an open-source license, a team of researchers and software engineers announced today. "The 2.0 version of the toolkit is now in full release," said Chris Basoglu, a partner engineering manager at Microsoft. He has played a key role in developing Microsoft Cognitive Toolkit (previously known as CNTK). The full release of Microsoft Cognitive Toolkit 2.0 for use in production-grade and enterprise-grade deep learning workloads includes hundreds of new features incorporated since the beta to streamline the process of deep learning and to ensure the toolkit's seamless integration throughout the wider AI ecosystem. New with the full release today is support for Keras, a user-friendly open-source neural network library that is popular with developers working on deep learning applications.
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Microsoft releases open-source toolkit to accelerate deep learning - Next at Microsoft
A toolkit used across Microsoft to achieve breakthroughs in artificial intelligence is generally available to the public via an open-source license, a team of researchers and software engineers announced today. "The 2.0 version of the toolkit is now in full release," said Chris Basoglu, a partner engineering manager at Microsoft. He has played a key role in developing Microsoft Cognitive Toolkit (previously known as CNTK). The full release of Microsoft Cognitive Toolkit 2.0 for use in production-grade and enterprise-grade deep learning workloads includes hundreds of new features incorporated since the beta to streamline the process of deep learning and to ensure the toolkit's seamless integration throughout the wider AI ecosystem. New with the full release today is support for Keras, a user-friendly open-source neural network library that is popular with developers working on deep learning applications.
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