Don't get me wrong, I like Go, but in my (and others I work with) experience, it's not the right choice for performance-critical systems.
I see "I couldn't possibly use X for performance reasons" here a lot, as an almost immediate response about a wide range of different tools, and two things come up in my mind: 1) you can always set the standard arbitrarily high. If you're doing AAA shoot-'em-up games or something, yes, use something else. 2) you're often not as good at tools that're new or different. It's possible you could go further with just a few more tricks about profiling or using free pools or whatever, or a little more info about how your code executes or what the runtime does. FWIW, if you hit a specific wall that's a problem for your app, folks on golang-nuts (or StackOverflow, where I've hung out sometimes) are often happy to try and help.
Hope this is more helpful than fussy. Mostly just don't want folks to be discouraged into thinking certain things are impossible when in some cases they're really being done in production out there.
Not as impressive as it sounds. Most of it is cached in memory anyway...
Where I work, we've been trying to build some super-fast systems and things like the GC and even calling interface methods matter. We open sourced some data structures that show just how optimized we're trying to get (https://github.com/Workiva/go-datastructures), but in hindsight, Go might not have been the right tool for the problem.
From my point of view, and the industry I'm in, the latency requirements of a web server stack look completely laughable. That's not to say there aren't challenges in a web stack, because many web servers have to handle orders of magnitude more I/O than we do, and efficient load balancing over a distributed system is extremely difficult and I am fortunate to rarely have to think about that kind of thing. But a requirement like "99% of requests need to have a response time of 200ms or lower" looks like fiddlesticks compared to a requirement like "a round-trip-time of more than 100us will be a large problem and get noticed".
My point is that Google's, CloudFlare's, and Dropbox's "performance-critical backends" don't require the same things as some other workloads. As a more mundane example, the latency requirements of Google's search engine are probably less stringent than the latency requirements of your text editor.
None of this should be taken to mean Go is slow or can't handle 99% of the world's performance requirements. But you can't just say "Go is high performance and fits in all of these company's critical paths. Try harder and it will work." Sometimes it might just not be cut out for it.
I think it really depends on your definition of "performance-critical". I agree Go isn't suitable for all performance-critical tasks, but it covers a vast swathe of them quite comfortably.
I believe this and am counting on it. Go2.0 and beyond should be a solid choice.
You should also note that it is entirely understood that more mature tech e.g. JVM have had the benefit of multibillion Dollar investment by SUN, IBM, Oracle, etc.
I feel it is regrettable that (imo valid and reasonable) criticism of what is currently not up to par with this tech always seemingly requires a disclaimer that "I love Go". I have been using this language since the day it was released. I know it fairly well. I like it. But excessive hype and sensitivity around it is frankly somewhat irritating.
peace out and happy v. day Go <3
(That's not me, to be clear.)
We all like Go. Just wish we could discuss these matters without unduly raising temperatures. "It's just code".
For context, the person whose presentation triggered Kelly's comment, MIT scholar Neha Narula, was experimenting with an 80 core machine, and she replied "it's kind of amazing I could push Go that far," and "to be fair they weren't really optimizing for my use case :)" -- her whole presentation is on YouTube at https://www.youtube.com/watch?v=Mbg1COjhsJU (some wild stuff--she got improvements for >48-core machines pushed into the Go GC) and those replies I quoted are at https://twitter.com/neha/status/564569903219634176 .
We are not all writing web apps. Some of use are in machine learning, NLP, signal processing, etc. where squeezing out as much performance as possible does matter.
In those fields Go is still weak. No autovectorization, no OpenMP, no direct CUDA integration, GC overhead, etc. Luckily, this can often be worked around since cgo is so good. One can write performance-intensive parts in C or C++, compile with the latest gcc or clang and link it with the Go code to drive it. This is often an understated advantage of Go compared to Java, where JNI calls are expensive. But the Go camp always advocate for porting everything to Go (because fast compile times).
E.g. you can make the libsvm library parellalized and scale up to many cores by adding two pragma statements.
I have a Go package that attempts to bring some of this functionality to Go [1]. But it's definitely not the same as having OpenMP.