Modern web services run across hundreds of thousands of servers in a data center, i.e., at hyperscale. With the end of Moore’s Law and Dennard scaling, successive server generations running these web services exhibit diminishing performance returns, resulting in architects adopting hardware customization. An important question arises: Which web service software operations are worth building custom hardware for? To answer this question, we comprehensively analyze important Facebook production services and identify key acceleration opportunities. We then develop an open-source analytical model, Accelerometer, to help make well-informed hardware decisions for the acceleration opportunities we identify.

中文翻译：

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了解超大规模的加速机会

现代 Web 服务在数据中心（即超大规模）中的数十万台服务器上运行。随着摩尔定律和登纳德缩放的终结，运行这些 Web 服务的连续几代服务器表现出递减的性能回报，导致架构师采用硬件定制。一个重要的问题出现了：哪些Web服务软件操作值得为之构建定制硬件？为了回答这个问题，我们全面分析了重要的 Facebook 生产服务并确定了关键的加速机会。然后，我们开发了一个开源分析模型 Accelerometer，以帮助为我们确定的加速机会做出明智的硬件决策。