The engineers at Habana Labs have this week unveiled their second-generation processes designed for AI Deep Learning. Taking the form of the Habana Gaudi 2 Training and Habana Greco Inference processors the new hardware has been purpose-built for AI deep learning applications using 7nm technology. The company has also created the Habana SynapseAI Software Suite, designed for deep learning model development and to ease migration of existing GPU-based models to Gaudi platform hardware.
“Habana Gaudi2 significantly increases training performance, building on the same high-efficiency first-generation architecture that enables customers with up to 40% better price performance in the AWS cloud with Amazon EC2 DL1 Instances and on-premises with the Supermicro X12 Gaudi Training Server. In addition to its 7 nm leap from 16 nm, Gaudi2 also features 24 Tensor Processor Cores, an increase from eight cores in the first Gaudi and designed expressly for large deep learning workloads. The new Gaudi2 AI training processor integrate media processing on-chip, triple on-board memory to 96 GB and double SRAM to 48 MB. These contribute to Gaudi2’s performance – up to three times the training throughput over first-generation Gaudi.”
AI Deep Learning
“The launch of Habana’s new deep learning processors is a prime example of Intel executing on its AI strategy to give customers a wide array of solution choices – from cloud to edge – addressing the growing number and complex nature of AI workloads. Gaudi2 can help Intel customers train increasingly large and complex deep learning workloads with speed and efficiency, and we’re anticipating the inference efficiencies that Greco will bring.”—Sandra Rivera, Intel executive vice president and general manager of the Datacenter and AI Group”
“Compared with the A100 GPU, implemented in the same process node and roughly the same die size, Gaudi2 delivers clear leadership training performance as demonstrated with apples-to-apples comparison on key workloads,” said Eitan Medina, chief operating officer at Habana Labs. “This deep-learning acceleration architecture is fundamentally more efficient and backed with a strong roadmap.”
Source : Habana Labs