Google thinks SpaceX’s Starship has to launch 1,800 times before space data centers get off the ground
Google thinks SpaceX’s Starship has to launch 1,800 times before space data centers get off the ground
谷歌认为 SpaceX 的星舰（Starship）需要发射 1,800 次，太空数据中心才能真正落地
Google’s prototype of its orbital compute satellite took off today onboard a SpaceX rocket launched from California — the first time the tech giant has sent one of its advanced chips into space. Built by Planet Labs, the satellite will prove that a Google Tensor Processing Unit, its competitor to Nvidia’s GPUs, can function in space. That means supplying a kilowatt of continuous power, cooling the chip, and running a series of models through their paces to see if anything goes wrong. 谷歌的轨道计算卫星原型机今日搭乘从加利福尼亚州发射的 SpaceX 火箭升空——这是这家科技巨头首次将其先进芯片送入太空。该卫星由 Planet Labs 制造，旨在验证谷歌的张量处理单元（TPU，即英伟达 GPU 的竞争对手）能否在太空中正常运行。这意味着要提供一千瓦的持续电力、为芯片散热，并运行一系列模型来测试是否会出现故障。
“We’ve done testing on the ground, but you know, there’s no test that’s completely as good as the real thing,” said Travis Beals, the Google executive managing Project Suncatcher, the tech giant’s plan to develop large-scale compute clusters in orbit around the Earth. Once commissioned, the satellite will fire up its TPU in 15-minute bursts to avoid straining the satellite’s power and thermal management systems. “我们在地面上进行了测试，但你知道，没有任何测试能完全比得上实战，”负责“捕日者计划”（Project Suncatcher）的谷歌高管 Travis Beals 表示。该计划是谷歌在地球轨道上开发大规模计算集群的蓝图。卫星投入使用后，将以 15 分钟为周期启动 TPU，以避免给卫星的电力和热管理系统造成过大负担。
This satellite is based on a standard platform built by Planet Labs, but the two companies are working on a demo expected to take flight next year that will see two satellites more purpose-built for advanced compute that can run more substantial workloads. Those future versions will attempt to collaborate via a laser communications link. 这颗卫星基于 Planet Labs 构建的标准平台，但两家公司正在合作开发一个预计于明年升空的演示项目，届时将有两颗专为高级计算而设计的卫星，能够运行更繁重的任务负载。这些未来的版本将尝试通过激光通信链路进行协作。
Suncatcher isn’t the only space AI payload on this SpaceX rocket, which is launching more than 100 different payloads, including missions from Satlyt and Cowboy Space Company. What sets the Google initiative apart from those startups (and indeed from SpaceX itself) is that it’s a long-term project. The focus of this “long-term moonshot,” as Beals puts it, is on building for the space infrastructure and AI workloads that will exist in the future. “捕日者计划”并非这枚 SpaceX 火箭上唯一的太空 AI 载荷，此次发射共搭载了超过 100 个不同的载荷，包括来自 Satlyt 和 Cowboy Space Company 的任务。谷歌这一举措与那些初创公司（甚至 SpaceX 本身）的区别在于，这是一个长期项目。正如 Beals 所言，这一“长期登月计划”的重点在于为未来将要出现的太空基础设施和 AI 工作负载进行建设。
The company envisions an orbital data center that is a network of 81 satellites flying in close formation, processing in parallel. “The bandwidth and the latency between TPUs really, really matters when you’re trying to run a multi-rack workload…we’re trying to look ahead to not just what workloads exist today, but where they will be in five years,” Beals said. That’s largely because the rockets required to scale up orbital data centers in a cost-effective way don’t yet exist. 该公司设想的轨道数据中心是一个由 81 颗卫星组成的网络，它们以紧密编队飞行并进行并行处理。“当你试图运行多机架工作负载时，TPU 之间的带宽和延迟至关重要……我们不仅在展望今天存在的工作负载，还在展望五年后的情况，”Beals 说道。这在很大程度上是因为，以经济高效的方式扩展轨道数据中心所需的火箭目前尚未问世。
On Thursday, Google also released a peer-reviewed version of its white paper on orbital data centers, one of the most rigorous analyses available of how compute gets to orbit. The paper will be published in Joule. One of the paper’s most notable aspects is how Google thinks about access to space. Although the researchers stress their analysis isn’t an economic feasibility study, it offers an interesting picture of how the company sees rockets becoming cheaper over time. 周四，谷歌还发布了其关于轨道数据中心的同行评审白皮书，这是目前关于计算如何进入轨道最严谨的分析之一。该论文将在《焦耳》（Joule）杂志上发表。论文中最引人注目的方面之一是谷歌对太空准入的看法。尽管研究人员强调他们的分析并非经济可行性研究，但它提供了一个有趣的视角，展示了该公司如何看待火箭成本随时间推移而降低的趋势。
Like all data center companies, Google is looking to SpaceX to get its spacecraft off the ground. (Google is also a major investor in SpaceX.) Arguing that Elon Musk’s rocket builders have achieved a price-reducing “learning curve” of about 20% a year since they launched the Falcon 1 rocket, the authors believe it’s reasonable to expect the company to deliver launch prices close to $200 per kilogram by 2035. 像所有数据中心公司一样，谷歌指望 SpaceX 将其航天器送入太空。（谷歌也是 SpaceX 的主要投资者。）作者认为，自发射猎鹰 1 号火箭以来，埃隆·马斯克的火箭制造团队已经实现了每年约 20% 的降价“学习曲线”，因此他们认为，到 2035 年，该公司将发射价格降至每公斤 200 美元左右是合理的预期。
What will it take to do that? Based on the amount of payload launched by the Falcon 9, they think a similar cost-reduction trajectory will require Starship to fly 370,000 tons of payload into orbit. That’s something that would take it about 1,800 launches over the next 10 years, or 180 a year — and that’s if it can fly 200 metric tons on each mission. That’s a big ask for a vehicle that has never flown more than five times in a year. 要做到这一点需要什么？根据猎鹰 9 号发射的载荷量，他们认为类似的成本降低轨迹将需要星舰将 37 万吨载荷送入轨道。这意味着在未来 10 年内需要进行约 1,800 次发射，即每年 180 次——前提是每次任务都能运载 200 公吨。对于一种一年内从未飞行超过五次的运载工具来说，这是一个巨大的挑战。
SpaceX predicts the company will be flying far more than that — Elon Musk has suggested Starship could achieve an hourly flight rate in 2029, for example, but Musk says a lot of things. The good news, at least, in Google’s updated research, is that it seems likely that its chips will survive the radiation of space. The company had to redo tests blasting the chips in a particle accelerator after they realized the configuration of the chips provided more shielding than they would actually experience. SpaceX 预测其飞行频率将远高于此——例如，埃隆·马斯克曾暗示星舰可能在 2029 年实现每小时一次的飞行频率，但马斯克的话往往听听就好。至少在谷歌更新的研究中，好消息是其芯片很有可能在太空辐射中存活下来。该公司在意识到芯片配置提供的屏蔽效果比实际环境中要好之后，不得不重新在粒子加速器中对芯片进行测试。
This produced slightly more errors in the chip’s logic circuitry, but the company is still confident its chips can handle large inference workloads in orbit for the five-year lifespan of a satellite. “The error rate is very low if you’re thinking about typical inference operations, right? Like one in a million,” Beals said. “On the other hand, it was already problematic for doing, say, some mega-scale training run where you’re going to have many thousands of chips running for months.” 这导致芯片逻辑电路中的错误略有增加，但该公司仍确信其芯片能够在卫星五年的寿命期内处理轨道上的大规模推理工作负载。“如果你考虑的是典型的推理操作，错误率是非常低的，对吧？比如百万分之一，”Beals 说。“另一方面，对于进行大规模训练任务来说，这已经是个问题了，因为你需要成千上万个芯片连续运行数月。”
Correction: The headline for this story originally misstated the learning curve estimate for Starship launches as 1,600; it is 1,800. 更正：本文标题最初将星舰发射的学习曲线估算值误写为 1,600；实际应为 1,800。