AMD EPYC™ 7002 Series processors set 80 performance world records1, provide 2X the performance compared to the previous generation2 and deliver an estimated 25% to 50% lower TCO than competitive offerings3 Google and Twitter join growing list of customers adopting AMD EPYC processors SANTA CLARA, Calif. – 08/07/2019 – At a launch event today, AMD …
Introducing world’s first PCIe® 4.0 ready desktop CPUs and GPUs, designed to push the limits of gamers, enthusiasts, and content creators SANTA CLARA, Calif. – 07/07/2019 – Today, AMD (NASDAQ: AMD) announced the global availability of its new leadership PC gaming platform based on AMD Radeon™ RX 5700 series graphics cards and 3rd Gen AMD …
The AMD Ryzen™ Embedded R1000 SoC provides a new class of performance for the embedded industry with 3X performance per watt vs. previous AMD R-Series SoC1 and 4X performance per dollar compared to the competition2 TAIPEI, Taiwan – 04/16/2019 – At the Taiwan Embedded Forum, AMD (NASDAQ: AMD) announced the Ryzen™ embedded product family is …
Mike Schmit, Director of Software Engineering for computer vision and machine learning at AMD, presents the “Bad Data, Bad Network, or: How to Create the Right Dataset for Your Application” tutorial at the May 2018 Embedded Vision Summit. When training deep neural networks, having the right training data is key. In this talk, Schmit explores …
Auro Tripathy, Founding Principal at ShatterLine Labs (representing AMD), presents the “From Feature Engineering to Network Engineering” tutorial at the May 2018 Embedded Vision Summit. The availability of large labeled image datasets is tilting the balance in favor of “network engineering”instead of “feature engineering”. Hand-designed features dominated recognition tasks in the past, but now features …
Radhakrishna Giduthuri, Software Architect at Advanced Micro Devices (AMD), presents the “OpenVX Computer Vision and Neural Network Inference Library Standard for Portable, Efficient Code” tutorial at the May 2018 Embedded Vision Summit. OpenVX is an industry-standard computer vision and neural network inference API designed for efficient implementation on a variety of embedded platforms. The API …
The ability to "stitch" together (offline or in real-time) multiple images taken simultaneously by multiple cameras and/or sequentially by a single camera, in both cases capturing varying viewpoints of a scene, is becoming an increasingly appealing (if not necessary) capability in an expanding variety of applications. High quality of results is a critical requirement, one …
Allen Rush, Fellow at AMD, presents the "How Computer Vision Is Accelerating the Future of Virtual Reality" tutorial at the May 2016 Embedded Vision Summit. Virtual reality (VR) is the new focus for a wide variety of applications including entertainment, gaming, medical, science, and many others. The technology driving the VR user experience has advanced …
The substantial parallel processing resources available in modern graphics processors makes them a natural choice for implementing vision-processing functions. The rapidly maturing OpenCL framework enables the rapid and efficient development of programs that execute across GPUs and other heterogeneous processing elements within a system. In this article, we briefly review parallelism in computer vision applications, …
Optimizing Computer Vision Applications Using OpenCL and GPUs Read More +
Harris Gasparakis, OpenCV Manager at AMD, presents the "Understanding Adaptive Machine Learning Vision Algorithms and Implementing them on GPUs and Heterogeneous Platforms" tutorial at the May 2015 Embedded Vision Summit. Machine learning algorithms are pervasive in computer vision: from object detection to object tracking to full scene recognition, generative or discriminative learning dominates the space, …
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