Imagine a world where technology for humans doesn't require humans to operate. Where data is analyzed in industrial, automotive, and even medical settings by the machines themselves. And where factory line workers, long-haul truckers, and surgeons are not obsolete but more efficient and more capable than ever before.
Automatic text reading from natural environments, also known as scene text detection/recognition or PhotoOCR, has become an increasingly popular and important research topic in computer vision. Softnautics has been working on Xilinx FPGA based solutions that require design and software framework implementation.
Cars are becoming safer, thanks to Advanced Driver Assistance Systems (ADAS) features such as automatic emergency braking (AEB) and driver monitoring systems.
These features are becoming ever more sophisticated, making automated driving robust. For instance, AEB began with merely watching cars in front. Now, it detects pedestrians, weaving traffic, cyclists, and objects in the road. Realizing the importance of AI to assist drivers, 20 automakers have readily agreed to equip most new passenger vehicles with low-speed AEB and forward-collision warning by September 2022.
To make that happen, cars need a sophisticated system of vehicle sensors and related processing.
This year, Xilinx is excited to sponsor the FPGA image classification track as part of the Low-Power Computer Vision Challenge 2020 CVPR Workshop. We would like you to participate and experience the ease of deploying and developing inference models using Vitis-AI + PYNQ (no FPGA knowledge is needed). The top 3 entries will get $1500, $1000, $500, and the top 20 team submissions get $270! Bring your innovation in model optimization to image classification algorithms running on the Xilinx platforms. Get started and register today!
Cloud computing has become the new computing paradigm. For cloud computing, virtualization is necessary to enable isolation between users, high flexibility and scalability, high security, and maximized utilization of hardware resources.
We have seen that the proposed FPGA virtualization framework provided excellent performance isolation, scalability, and flexibility. With an online reconfiguration overhead of about 1ms and 1.12% single-core performance loss, it achieves 1.07x – 1.69x and 1.88x – 3.12x performance improvement compared with the baseline design. The virtualized FPGA design also achieves great isolation and linearity to hardware resources. It will help further reduce TCO of all deep learning applications in the cloud.
Amazon Elastic Compute Cloud (Amazon EC2) F1 instances make the power of Xilinx adaptable computing accessible to all developers – You only pay-as-you-go for the computing power you use – no upfront hardware purchases. Vitis Unified Software Platform 2019.2 is now available for all developers to harness the power of EC2 F1 instances - access everything you need to develop, simulate, debug, and compile your accelerated algorithms on F1 – no local software setups required !
What's more ? Amazon is now offering up to $10,000 in free AWS credits, making it easier than ever before to leverage FPGA acceleration in the AWS Cloud and evaluate the benefits it can bring to your applications.
Each February, Amsterdam hosts the largest AV and systems integration showcase in the world - Integrated Systems Europe (ISE). Here, the global AV industry gathers to celebrate leading AV projects as well as..