Catapult AI NN – From AI/ML Framework to Optimized RTL

As demand for Machine Learning increases, the need for custom hardware acceleration is exploding. Developing hardware that is optimally tuned for Performance, Power & Area (PPA) and optimized to the network and application delivers enormous competitive advantages in silicon. Designers working in AI/ML Frameworks such as TensorFlow, PyTorch have previously relied on “rule of thumb” or RTL design teams to assess the cost of implementation. Catapult AI NN now delivers a methodology and flow from “AI/ML Framework to RTL” enabling rapid exploration of network, quantization, design reuse factors on a layer-by-layer basis for PPA, generating production-ready custom RTL without needing extensive HLS knowledge or RTL skills.