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    Cerebras is a computer systems company dedicated to accelerating deep learning.

    The pioneering Wafer-Scale Engine (WSE) – the largest chip ever built – is at the heart of our deep learning system, the Cerebras CS-1.

    56x larger than any other chip, the WSE delivers more compute, more memory, and more communication bandwidth. This enables AI research at previously-impossible speeds and scale.

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    CS-1 is powered by the Cerebras Wafer Scale Engine - the largest chip ever built

    56x the size of the largest Graphics Processing Unit

    The Cerebras Wafer Scale Engine is 46,225 mm2 with 1.2 Trillion transistors and 400,000 AI-optimized cores.

    By comparison, the largest Graphics Processing Unit is 815 mm2 and has 21.1 Billion transistors.

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    komi加速器vqn-快连加速器app

    • 46,225 mm2 chip 56x larger than the biggest GPU ever made
    • 400,000 core 无忧资讯 和平精英新版本爆料:海岛地图2.0迎来重大升级-无 ...:2021-6-15 · 无忧加速器 总体而言,新地图的整体色调非常明亮,游戏画面比当前要清晰很多,模型也更加的精细。游戏整体建筑布局有较大调整,物资也更加的丰富,小伙伴伔无论是打野还是刚枪,都比众前有了更多的跳点选择。
    • 18 GB on-chip SRAM 3000x more on-chip memory
    • 100 Pb/s interconnect 如何访问P站 | Pixiv 被墙无法访问的解决方法 | 码农网:前言 著名的二次元图片网站P站( Pixiv )因为被墙的原因在国内打不开,之前通过更改 DNS 和 Hosts 访问P站的方法现在也失效了。 这里就介绍下 如何一劳永逸的解决P站无法访问的问题的方法——自己搭建 SS (Shadowsocks) 伕理服务。 虽然比起之前无成本 ...

    komi加速器vqn-快连加速器app

    • 15 Rack Units​ Fits in a standard datacenter rack​
    • 1.2 Terabits/sec ​ System IO​ over 12x standard 100 GbE
    • 20 kW​ Maximum power draw​
    Explore our product

    komi加速器vqn-快连加速器app

    The Cerebras software stack is designed to meet users where they are, integrating with open source ML frameworks like TensorFlow and PyTorch. Our software makes cluster-scale compute resources available to users with today's tools.

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    Accelerate your AI research

    • komi加速器vqn-快连加速器app

      Provides faster time to solution, with cluster-scale resources on a single chip and with full utilization at any batch size, including batch size 1

    • komi加速器vqn-快连加速器app

      Runs at full utilization with tensors of any shapes, fat, square and thin, dense and sparse, enabling researchers to explore novel network architectures and optimization techniques

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      Translates sparsity in model and data into performance, via a vast array of programmable cores and flexible interconnect

    Explore more ideas in less time. Reduce the cost of curiosity.

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