Go doesn't really have parallelism features either. A language designed for parallelism needs to have data-parallel features like parallel iterators, good support for SIMD, and concurrent data structures, neither of which Go has. (In fact, due to lack of generics, you can't even build your own generic concurrent data structures!)
"Parallel computing is a type of computation in which many calculations or the execution of processes are carried out simultaneously."
Do you enjoy trolling and dismissing Go in general? Reading your comments sounds like some envy toward Go popularity. When you're not complaining about concurrency features it's about Go GC.
And Node has workers and can thus achieve parallelism as well. What matters isn't whether the language can achieve parallelism: it's whether the language is designed for it. Go is designed for concurrency, not parallelism.
It's Rob Pike's view [1] that concurrency enables parallelism "for free". I think that's oversimplified and at odds with the way people who write CPU-bound code actually use parallelism features, but that's how Go was designed: it omits traditional parallelism features in favor of concurrency features.
I didn't say it was impossible to do parallel work in Go. You can get parallelism in Node, too, by using workers, or by just forking processes and having them communicate with pipes. Rather, what I was trying to emphasize is that Go—and Node—aren't designed for parallelism. Go has good support for concurrency, not parallelism. Parallel languages have feature sets more like CUDA, C++ with OpenMP, OpenCL, etc.
The traditional definition was doing multiple operations at the same time. SIMD, SMP, multicore, and clustering would qualify. So, yeah, you could do parallel processing in dual- or quad-CPU configuration. Beowulf clusters started with 486 using MPI and PVM. So, scale the Pentium Pro's up and out.
EDIT: Glanced at Wikipedia out of curiosity. Forgot it was used in ASCI Red. So, definitely can use them for parallel computing. To pass a teraflop, you just need 1,600 sq. ft. of them running at 850 kW. ;)
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Go doesn't really have parallelism features either. A language designed for parallelism needs to have data-parallel features like parallel iterators, good support for SIMD, and concurrent data structures, neither of which Go has. (In fact, due to lack of generics, you can't even build your own generic concurrent data structures!)
Your comment makes no sense, goroutines are multiplexed on each cores thus it has parallelism.
https://en.wikipedia.org/wiki/Parallel_computing
"Parallel computing is a type of computation in which many calculations or the execution of processes are carried out simultaneously."
Do you enjoy trolling and dismissing Go in general? Reading your comments sounds like some envy toward Go popularity. When you're not complaining about concurrency features it's about Go GC.
And Node has workers and can thus achieve parallelism as well. What matters isn't whether the language can achieve parallelism: it's whether the language is designed for it. Go is designed for concurrency, not parallelism.
It's Rob Pike's view [1] that concurrency enables parallelism "for free". I think that's oversimplified and at odds with the way people who write CPU-bound code actually use parallelism features, but that's how Go was designed: it omits traditional parallelism features in favor of concurrency features.
[1]: https://blog.golang.org/concurrency-is-not-parallelism
Yikes. It's impossible to do parallel processing on my old pentium pro because it lacks MMX?
I didn't say it was impossible to do parallel work in Go. You can get parallelism in Node, too, by using workers, or by just forking processes and having them communicate with pipes. Rather, what I was trying to emphasize is that Go—and Node—aren't designed for parallelism. Go has good support for concurrency, not parallelism. Parallel languages have feature sets more like CUDA, C++ with OpenMP, OpenCL, etc.
The traditional definition was doing multiple operations at the same time. SIMD, SMP, multicore, and clustering would qualify. So, yeah, you could do parallel processing in dual- or quad-CPU configuration. Beowulf clusters started with 486 using MPI and PVM. So, scale the Pentium Pro's up and out.
EDIT: Glanced at Wikipedia out of curiosity. Forgot it was used in ASCI Red. So, definitely can use them for parallel computing. To pass a teraflop, you just need 1,600 sq. ft. of them running at 850 kW. ;)
https://en.wikipedia.org/wiki/ASCI_Red
Well, also because it only features a single processor.
You could mimic parallel processing effects with multitasking tho.
Note however how parent didn't say that Go "can't do" parallelism, but that Go is not "a language designed for parallelism".