IC speeds machine-learning training

LONDON – Following the launch of its AI inference chip last year, Habana Labs (Tel-Aviv, Israel) has unveiled an AI training chip built on the same architecture that can outpace the incumbent technology by a substantial margin, and features on-chip RoCE (remote direct memory access over Converged Ethernet) communications for scalability. While the company's inference chip, Goya, set records for ResNet-50 inference back in September 2018, the new training chip, Gaudi, offers similar high performance. Gaudi can process 1650 images per second at a batch size of 64 when training a ResNet-50 network, which Habana claims is a new world record for this benchmark. This throughput is delivered at 140W power consumption, also a substantial advantage versus competing solutions, according to the company. Impressive, but is Habana's architecture designed specifically to beat the ResNet-50 benchmark, or will it offer similar throughput advantages for other types of neural networks?