Andrew is co-founder and CEO of Cerebras Systems. He is an entrepreneur dedicated to pushing boundaries in the compute space. Prior to Cerebras, he co-founded and was CEO of SeaMicro, a pioneer of energy-efficient, high-bandwidth microservers. SeaMicro was acquired by AMD in 2012 for $357M. Before SeaMicro, Andrew was the Vice President of Product Management, Marketing and BD at Force10 Networks which was later sold to Dell Computing for $800M.

HPE and Cerebras Systems have built a new AI supercomputer in Munich, Germany, pairing a HPE Superdome Flex with the AI accelerator technology from Cerebras for use by the scientific and engineering community. The new system, created for the Leibniz Supercomputing Center (LRZ) in Munich, is being deployed to meet the current and expected future compute needs of researchers, including larger deep learning neural network models and the emergence of multi-modal problems that involve multiple data types such as images and speech, according to Laura Schulz, LRZ's head of Strategic Developments and Partnerships. "We're seeing an increase in large data volumes coming at us that need more and more processing, and models that are taking months to train, we want to be able to speed that up," Schulz said. "And then we're also seeing multi-modal problems, such as integration of natural language processing (NLP) and medical imaging or documents, so we have this complexity, we have this the need for faster, we have this need for bigger that's coming from our user side, from our facility side, and we need to make sure that we're constantly evaluating to have these different novel architectures, to have different usage models to be able to understand all that." The LRZ team decided that the Cerebras technology, with its large shared memory and scalability, was a good match for the "pain points" they were trying to resolve, she said.

SILICON CHIPS have lonely lives. They are born together, often as tens of thousands of identical siblings a few millimetres across, on a single wafer the size of an old-fashioned vinyl record. They are then broken from their natal wafers like squares of chocolate from a bar, and packaged individually in plastic and metal. Only after this is a chip reconnected to others of its kind, as the packages are wired up to work together on circuit boards and inserted into products. Many inventors over the years have noted that if chips were instead wired together from the beginning, on the wafer itself, much expense and trouble would be avoided.

SILICON CHIPS have lonely lives. They are born together, often as tens of thousands of identical siblings a few millimetres across, on a single wafer the size of an old-fashioned vinyl record. They are then broken from their natal wafers like squares of chocolate from a bar, and packaged individually in plastic and metal. Only after this is a chip reconnected to others of its kind, as the packages are wired up to work together on circuit boards and inserted into products. Many inventors over the years have noted that if chips were instead wired together from the beginning, on the wafer itself, much expense and trouble would be avoided.

Today unicorn startup Cerebras disclosed a few details about the wafer-scale AI chip it has been keeping under wraps for some three years. While many unanswered questions remain, the new approach could mark a significant milestone in the semiconductor industry, where chips have historically been constrained by the size of a single chip's mask. Basically, Cerebras designed a wafer of 84 interconnected chips that act as one device for compute and memory, interconnected by a super-fast on-die fabric. While building a supercomputer on a chip sounds like a great idea, building a wafer-scale array of chips is not for the faint of heart or talent. Figure 1: The Cerebras "WSE" is some 50 times larger than the largest chip used in AI Training from NVIDIA.