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CUDA Refresher: The GPU Computing Ecosystem

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. This is the third post in the CUDA Refresher series, which has the goal of refreshing key concepts in CUDA, tools, and optimization for beginning or intermediate developers. Ease of programming and a giant leap in performance […]

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Intel Announces Unmatched AI and Analytics Platform with New Processor, Memory, Storage and FPGA Solutions

What’s New: Intel today introduced its 3rd Gen Intel® Xeon® Scalable processors and additions to its hardware and software AI portfolio, enabling customers to accelerate the development and use of artificial intelligence (AI) and analytics workloads running in data center, network and intelligent-edge environments. As the industry’s first mainstream server processor with built-in bfloat16 support, Intel’s

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CUDA Refresher: Getting Started with CUDA

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. This is the second post in the CUDA Refresher series, which has the goal of refreshing key concepts in CUDA, tools, and optimization for beginning or intermediate developers. Advancements in science and business drive an insatiable demand

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CUDA Refresher: Reviewing the Origins of GPU Computing

This blog post was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. This is the first post in the CUDA Refresher series, which has the goal of refreshing key concepts in CUDA, tools, and optimization for beginning or intermediate developers. Scientific discovery and business analytics drive an insatiable demand

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New Long-Term Support Release Marks Second Anniversary of Intel Distribution of OpenVINO Toolkit

This blog post was originally published at Intel’s website. It is reprinted here with the permission of Intel. We’re coming up on the second anniversary of Intel Distribution of OpenVINO toolkit, which makes this the perfect time to look at the past, present, and future of the toolkit that’s helping companies worldwide accelerate the performance

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Open Sourcing the AI Model Efficiency Toolkit: Contributing State-of-the-art Compression and Quantization Techniques from Qualcomm AI Research

This blog post was originally published at Qualcomm’s website. It is reprinted here with the permission of Qualcomm. QuIC is excited to open source the AI Model Efficiency Toolkit on GitHub to collaborate with other leading AI researchers and to provide a simple library plugin for AI developers to utilize for state-of-the-art model efficiency performance.

Open Sourcing the AI Model Efficiency Toolkit: Contributing State-of-the-art Compression and Quantization Techniques from Qualcomm AI Research Read More +

Allied Vision’s Vimba Suite Now with Python Application Programming Interface

With the new Python API, Vimba Suite 4.0 Enables Rapid Prototyping of Vision Applications Stadtroda, Germany, May 26, 2020 – Allied Vision has released a new version of its Software Development Kit Vimba. Vimba 4.0 offers a Python Application Programming Interface (API). In addition to the established APIs for C, C++ and .NET, developers can

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Upcoming Virtual Seminar Series Discusses Smart Devices That Understand and Seamlessly Communicate With the World Around Them

On June 2 (Communication), 3 (Connectivity and Sensing), 9 (AI and Vision), and 10 (Wireless Audio), Edge AI and Vision Alliance Member company CEVA will deliver a four-part virtual seminar series focusing on how to create smart devices that understand the world around them and seamlessly communicate. Also included in the event, and available in

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Unified Programming Model Critical to Uncompromised Application Performance, Saves Time and Money, Study Finds

What’s New: New computing accelerators are rapidly emerging, and organizations need to examine time and financial considerations associated with developing performance-sensitive applications that can run on both new and existing computing platforms. Commissioned by Intel, a recent research report from J.Gold Associates, “oneAPI: Software Abstraction for a Heterogeneous Computing World,” discusses the importance of application

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Training with Custom Pretrained Models Using the NVIDIA Transfer Learning Toolkit

This article was originally published at NVIDIA’s website. It is reprinted here with the permission of NVIDIA. Supervised training of deep neural networks is now a common method of creating AI applications. To achieve accurate AI for your application, you generally need a very large dataset especially if you create… Training with Custom Pretrained Models

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