Cerebras’ CS-2 brain-scale chip can power AI models with 120 trillion

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        Cerebras Systems said its CS-2 Wafer Scale Engine 2 processor is a “brain-scale” chip that can power AI models with more than 120 trillion parameters.And that’s why Cerebras believes its latest processor — which is actually built on a wafer instead of just individual chips — is going to be so powerful founder and CEO Andrew Feldman said in an interview with VentureBeat.

        “The industry is moving past a trillion-parameter models and we are extending that boundary by two orders of magnitude enabling brain-scale neural networks with 120 trillion parameters.” Feldman said the Cerebras CS-2 is powered by the Wafer Scale Engine (WSE-2) the largest chip ever made and the fastest AI processor to date.The WSE-2 also has 123 times more cores and 1 000 times more high-performance on-chip memory than graphic processing unit competitors.As noted the largest AI hardware clusters were on the order of 1% of a human brain’s scale or about 1 trillion synapse equivalents or parameters.

        But Feldman said a single CS-2 accelerator — the size of a dorm room refrigerator — can support models of over 120 trillion parameters in size.On top of that he said Cerebras’ new technology portfolio contains four innovations: Cerebras Weight Streaming a new software execution architecture; Cerebras MemoryX a memory extension technology; Cerebras SwarmX a high-performance interconnect fabric technology; and Selectable Sparsity a dynamic sparsity harvesting technology.The Cerebras Weight Streaming technology can store model parameters off-chip while delivering the same training and inference performance as if they were on-chip.This new execution model disaggregates compute and parameter storage — allowing researchers to flexibly scale size and speed independently — and eliminates the latency and memory bandwidth issues that challenge large clusters of small processors.The Cerebras MemoryX will provide the second-generation Cerebras Wafer Scale Engine (WSE-2) up to 2.4 petabytes of high-performance


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