Cerebras built the fastest AI accelerator, based on the largest processor in the industry, and made it easy to use. With Cerebras, blazing fast training, ultra low latency inference, and record-breaking time-to-solution enable you to achieve your most ambitious AI goals.
Purpose built for AI, the CS-2 replaces an entire cluster of graphics processing units (GPUs). Gone are the challenges of parallel programming, distributed training, and cluster management. From chip to system to software – every aspect of the CS-2 is optimized to accelerate and to simplify AI work. The CS-2 produces answers in less time.
The Wafer Scale Engine (WSE-2) is the largest chip ever built and powers the CS-2. The WSE-2 is 56 times larger than the largest GPU, has 123 times more compute cores, and 1000 times more high performance on-chip memory. The only wafer scale processor ever produced, it contains 2.6 trillion transistors, 850,000 AI-optimized cores, and 40 gigabytes of high performance on-wafer memory all aimed at accelerating your AI work.
Harness the AI performance of a supercomputer with a cluster of CS-2 machines. Multiple CS-2 machines can be clustered together to scale up throughput for further training and inference acceleration and support multi-billion to even trillion parameter models. Large-scale data centers and supercomputers typically have hundreds to thousands of nodes, take months or years to build, occupy facilities the size of airport terminals, and often draw more than 10MW. By comparison, each individual CS-2 machine provides the compute-equivalent of 10s-100s of traditional nodes. This means you can deploy datacenter-scale AI compute to unlock world leading innovation in just a few days or weeks – delivering greater performance in a space- and power-efficient package built for the job.
The Lawrence Livermore National Lab’s Lassen supercomputer has incorporated the CS-1 in both classified and non-classified areas for physics-based HPC simulations. The Argonne National Laboratory has been using the CS-1 since 2020 in COVID-19 research and cancer tumor research based on the world’s largest cancer treatment database. In 2020, GlaxoSmithKline (GSK) began using the Cerebras CS-1 AI system in their London AI hub, for neural network models to accelerate genetic and genomic research and reduce the time taken in drug discovery.