- iWave Systems’ evaluation kit (EVK) incorporates tools and libraries for reduced complexity in developing AI solutions
- Arm-based FPGA architecture provides advantage of using the Arm cores as a regular SoC for high-level management functionalities
As AI is increasingly becoming part of various application areas, there is an increasing requirement for adaptive intelligent solutions capable of AI workloads, particularly in edge devices. FPGA based development solutions offer exceptional inference capability with the help of complex neural networks and deep learning algorithms while maintaining flexibility, low latency and power efficiency.
Now, iWave Systems has announced the successful implementation of the open-source Xilinx Vitis
The powerful Zynq® UltraScale+
The solution incorporates a configurable deep-learning processor unit in the PL of the Zynq MPSoC chip. The DPU is an AI inference engine dedicated to Convolution Neural Networks such as VGG, SSD, Yolov2/v3, FPN, Resnet50 and others. The DPU AI inference engine provides multi-dimensional parallel architecture capable of performing major convolutional calculations through deep pipelined computing engines.
The EVK supports interfaces to connect 8 IP cameras, multiple USB cameras and SDI Camera, providing the ability to capture multi-angle high-resolution video/image frames. The solution also supports high-speed connectivity options such as Dual Gigabit Ethernet and 3G/4G/5G via an M.2 expansion slot. There is also a provision for extended storage for an mSATA / NVMe SSD via the M.2 expansion slot. Additional interfaces such as FMC, SATA, SDI Video In & Out, USB3.0, SFP+ and a host of other interfaces allow for a wide range of networking options helping customers towards various use cases based on the on-premise architecture and requirements.
The EVK is built around a highly adaptive Zynq® UltraScale+
The Zynq® UltraScale+
Through the support of key features such as the Zynq® UltraScale+