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If you’ve got the time, we’ve got the HighScalability:
- 9nm : IBM's carbon nanotube transistor that outperforms silicon; YouTube: 4 Billion Views/Day; 864GB RAM: 37signals Memcache, $12K
- Quotable Quotes:
- Chad Dickerson: You can only get growth by feeding opportunities.
- @launchany: It amazes me how many NoSQL database vendors spend more time detailing their scalability and no time detailing the data model and design
- Google: Let's make TCP faster.
- WhatsApp: we are now able to easily push our systems to over 2 million tcp connections!
- Sidney Dekker: In a complex system…doing the same thing twice will not predictably or necessarily lead to the same results.
- @Rasmusfjord: Just heard about an Umbraco site running on Azure that handles 20.000 requests /*second*
- Herb Sutter with an epic post, Welcome to the Jungle, touching on a lot of themes we've explored on HighScalability, only in a dramatically more competent way. What's after the current era of multi-core CPUs has played out? Mainstream computers from desktops to ‘smartphones’ are being permanently transformed into heterogeneous supercomputer clusters. Henceforth, a single compute-intensive application will need to harness different kinds of cores, in immense numbers, to get its job done. Different parts of even the same application naturally want to run on different kinds of cores. Applications will need to be at least massively parallel, and ideally able to use non-local cores and heterogeneous cores. Programming languages and systems will increasingly be forced to deal with heterogeneous distributed parallelism. Perhaps our most difficult mental adjustment, however, will be to learn to think of the cloud as part of the mainstream machine – to view all these local and non-local cores as being equally part of the target machine that executes our application, where the network is just another bus that connects us to more cores. If you haven’t done so already, now is the time to take a hard look at the design of your applications, determine what existing features – or, better still, what potential and currently-unimaginable demanding new features – are CPU-sensitive now or are likely to become so soon, and identify how those places could benefit from local and distributed parallelism. Now is also the time for you and your team to grok the requirements, pitfalls, styles, and idioms of hetero-parallel (e.g., GPGPU) and cloud programming.
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