Software development kit supports FPGA vision development
VectorBlox software development kit (SDK) and IP allows software developers to program a trained neural network without prior FPGA expertise, says Microchip.
The rise of artificial intelligence (AI), machine learning (ML) and the IoT has prompted applications to move to the network edge where data is collected. This requires power-efficient solutions to deliver more computational performance in ever smaller, thermally constrained form factors. Microchip’s Smart Embedded Vision makes it easier for software developers to implement their algorithms in PolarFire FPGAs for edge computing. Its VectorBlox Accelerator SDK helps developers create low power, overlay based neural network applications for Microchip’s PolarFire FPGAs without learning an FPGA tool flow.
According to Microchip, FPGAs are ideal for edge AI applications, such as inferencing in power-constrained compute environments, because they can perform more giga operations per second (GOPS) with greater power efficiency than a central processing unit (CPU) or graphics processing unit (GPU). They do require specialised hardware design skills. Microchip’s VectorBlox Accelerator SDK is designed to enable developers to code in C/C++ and program power-efficient neural networks without prior FPGA design experience.
The tool kit can execute models in TensorFlow and the open neural network exchange (ONNX) format which supports many frameworks such as Caffe2, MXNet, PyTorch and MatLab. The SDK is supported on Linux and Windows operating systems and it also includes a bit accurate simulator to validate the accuracy of the hardware while in the software environment. The kit’s neural network IP supports the ability to load different network models at run time.
For inferencing at the edge, PolarFire FPGAs deliver up to 50 per cent lower total power than competing devices, while also offering 25 per cent higher-capacity math blocks that can deliver up to 1.5 tera operations per second (TOPS). By using FPGAs, developers also have greater opportunities for customisation and differentiation through the devices’ inherent upgradability and ability to integrate functions on a single chip. The PolarFire FPGA neural network IP is available in a range of sizes to match the performance, power, and package size trade offs for the application, enabling customers to implement their solutions in package sizes as small as 11 × 11mm.
Microchip’s Smart Embedded Vision initiative was launched last July to provide hardware and software developers with tools, IP cores and boards for meeting the thermally constrained and small form factor requirements of edge applications.
Microchip’s VectorBlox Accelerator SDK is scheduled to be available in Q3 2020, starting with an Early Access Program in June. PolarFire FPGAs are in production today.
