Cerebras Introduction
Cerebras Systems is a pioneering AI computing company that builds the world's largest and fastest AI processor - the Wafer Scale Engine (WSE) - designed to accelerate AI training and inference workloads.
View MoreWhat is Cerebras
Founded in 2015, Cerebras Systems is an American artificial intelligence company headquartered in Sunnyvale, with offices in San Diego, Toronto, and Bangalore. The company specializes in developing revolutionary wafer-scale computer chips and AI systems for complex deep learning applications. Their flagship product, the Cerebras Wafer Scale Engine (WSE), is the largest computer chip ever built, about the size of a dinner plate, containing over 1.2 trillion transistors. The company has recently filed for IPO and is valued at over $4 billion, marking its significant position in the AI hardware market.
How does Cerebras work?
Cerebras' technology centers around its Wafer Scale Engine (WSE) and CS systems, which integrate computing, memory, and interconnect fabric into a single massive chip. Unlike traditional GPUs that struggle with moving data between memory and compute cores, Cerebras' architecture keeps all model layers stored directly on the chip, enabling much faster processing. The latest WSE-3 chip delivers 125 petaflops of compute power and features 44GB of on-chip SRAM memory with 21 PB/s bandwidth. Through their Cerebras Inference service, they offer access to their technology via API, allowing developers to run AI models like Meta's LLaMA 3.1 at speeds up to 2,100 tokens per second - significantly faster than GPU-based solutions.
Benefits of Cerebras
Cerebras' solution offers several key advantages: it delivers up to 20x faster performance than GPU-based alternatives while using only one-sixth the power consumption; it maintains state-of-the-art accuracy by staying in 16-bit domain for inference; it eliminates the complexity of distributed computing since the entire model fits on one chip; and it provides cost-effective solutions with inference costs reported to be one-third of traditional cloud platforms. These benefits make it particularly attractive for developers working on real-time or high-volume AI applications, especially in sectors like healthcare, energy, and scientific computing.
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