We are excited to announce that for a limited time, you can purchase the VCK5000 Versal™ development card for AI inference for just $2,495! If you're developing AI inference workloads with pre-built Vitis™ AI accelerators, be sure to take advantage of this limited-time price.
Delivering 100X greater compute power than today’s server-class CPUs and greater MLPerf inference performance than today’s server-class GPUs, the VCK5000 is an ideal development platform for cloud acceleration and edge computing applications.
Last summer, we kicked off the first ever Xilinx Adaptive Computing Challenge, where we challenged developers and startups to create exciting new applications using Vitis or Vitis AI on select Xilinx hardware platforms. We announced the winners for both the developer and startup contests earlier this year and were extremely proud of the innovative projects and solutions that were built. We are excited to announce that you can now find the Deepfield-SR solution by BLUEDOT, the first place startup winner, on the new Xilinx App Store!
Exciting news! As part of yet another milestone in Xilinx’s open source strategy and commitment to enable the broader research and developer community to harness the power of adaptive computing – We have now opened access to the front-end of Vitis HLS on GitHub!
Super Resolution refers to the process of reconstructing a higher-resolution image or sequence from the observed lower – resolution images. An image may have a “lower resolution” due to a smaller spatial resolution (i.e., size) or due to a result of degradation (such as blurring). It has a wide range of applications including but not limited to satellite imaging, medical imaging, video surveillance as well as video streaming which is the primary focus of this article.
Xilinx Add-on for MATLAB & Simulink is a single tool that unifies Model Composer andSystem Generator for DSP. It is a Model-Based Design tool enabling algorithm and RTL/hardware developers to rapidly design and explore within the MathWorks Simulink® environment and target Xilinx devices.
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..