Stuff The Internet Says On Scalability For September 7th, 2018

Hey, it's HighScalability time:

Get antsy waiting 60 seconds for a shot? Imagine taking over 300,000 photos over 14 years, waiting for Mount Colima to erupt. Sergio Tapiro studied, waited, and snapped.
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- 3.5 Pflop/s: fully synchronous tensorflow data-parallel training; 3.3 million: new image/caption training set; 32,408,715: queries sent to Pwned Passwords; 53%: Memory ICs Total 2018 Semi Capex; 11: story Facebook datacenter prison in Singapore; $740,357: ave cost of network downtime;
- Quotable Quotes:
- @BenedictEvans: Recorded music: $18 billion. Cars: $1 trillion. Retail: $20 trillion.
- @JoeEmison: Lies that developers tell (themselves): (1) This is the best stack/IaaS for us to use [reality: I know it and want to start now] (2) DevOps doesn’t matter until scaling [you’ll spend 30% of your time dealing with ops then] (3) We’ll just rebuild it if we get traction [hahahaha]
- @sapessi: Lambda simplifies concurrency at the frontend, enforcing one event per function at a time. This makes it easy to reason about complex distributed system. Once inside the function, there's nothing wrong with multi-threading to do the work as efficiently as possible
- @JonErlichman~ Comparing valuations: Amazon: $1 trillion; Combined $960 billion: Best Buy Macy’s Target Costco Nike Sears Home Depot Starbucks McDonald’s Barnes & Noble J.C. Penney Dollar Tree Office Depot Nordstrom Kroger Kohls
- Kevin Kelly: The biggest invention in Silicon Valley was not the transistor but the start-up model, the culture of the entrepreneurial start-up.
- Dare Obasanjo: Amazon made $2.2B from search ads last quarter. This is twice as much as Snapchat ($262M) and Twitter ($711M) combined. However still far from Google ($28B) and Facebook ($13.2B). Expect next step is for Amazon ads to start show scale
- Matthew Dillon: This is *very* impressive efficiency. Whod a thought that one would be
able to run an 8-core/16-thread CPU at full load at only 85W and still reapmost of the benefit in a memory-heavy workload! This is *very* impressive efficiency. Whod a thought that one would beable to run an 8-core/16-thread CPU at full load at only 85W and still reapmost of the benefit in a memory-heavy workload!
- @laurencetratt: When we set out to look at how long VMs take to warm up, we didn’t expect to discover that they often don’t warm up. But, alas, the evidence that they frequently don’t warm up is hard to argue with. Of course, in some cases the difference to performance is small enough that one can live with it, but it’s often bad enough to be a problem. We fairly frequently see performance get 5% or more worse over time in a single process execution. 5% might not sound like much, but it’s a huge figure when you consider that many VM optimisations aim to speed things up by 1% at most. It means that many optimisations that VM developers have slaved away on may have been incorrectly judged to speed things up or slow things down, because the optimisation is well within the variance that VMs exhibit.
- Eli Bendersky: Just for fun, I rewrote the same benchmark in Go; two goroutines ping-ponging short message between themselves over a channel. The throughput this achieves is dramatically higher - around 2.8 million iterations per second, which leads to an estimate of ~170 ns switching between goroutines [3]. Since switching between goroutines doesn't require an actual kernel context switch (or even a system call), this isn't too surprising. For comparison, Google's fibers use a new Linux system call that can switch between two tasks in about the same time, including the kernel time.
- @ben11kehoe: So instead of a processor [for @iRobot] that is maxed out by the features it supports at launch (which is the route to the lowest build cost), we've got headroom to keep pace even with software features we're planning for the generation of robots after this.
- It was a quiet week this week. Just a few more quotes...