4 ms·

basically every program i have written has been concurrent and benefited from multi core support. a language that doesn’t have it just isn’t an option.

pjmlp 8y ago
Security exploits and plugin crashes on the other hand prove there is a benefit in using multiple processes instead.
- nikofeyn 8y ago
  well, trade offs are trade offs because then one has to worry about intraprocess communication. can you elaborate on security exploits? i would assume a closed off system with interprocess communication would be less vulnerable than that with intraprocess communication, which seems like it could be intercepted. but i do not know much about security. process crashes are of course a problem in terms of bringing down the whole process, but that generally isn’t a problem for me.
  - pjmlp 8y ago
    Each process would execute with the minimal set of permissions that it needs to perform its tasks. Whereas in interprocess, each thread can do everything that the whole process is allowed to do, so a security exploit in e.g. file parser, opens the door for doing other stuff that a file parser shouldn't be allowed to start with. An easy to use IPC is to use pipes, mailboxes, message queues, just like channels. Yes it might be slower, but for a large set of problems it is fast enough.
- BubRoss 8y ago
  I think both are more a matter of architecture. There are many different ways of finding parallelism and they all have their place. There is no single silver bullet and more parallelism and concurrency are generally the right direction to make use of modern hardware.
yawaramin 8y ago
Do you have any analytical benchmarks regarding the benefits you've gotten from multicore support?
- nikofeyn 8y ago
  well just today i sped up a simple algorithm by a factor of two or three on larger data sets by simply turning on parallelism in a for loop, which distributes iterations across cores and then merges them afterwards. so multicore performance came for free. in other instances, when programming concurrent programs, i have no worry of performance losses because, again, multicore support comes for free. that is more qualitative, but it is important. and it means my concurrent programs are actually concurrent.
  - yawaramin 8y ago
    Regarding your simple algorithm, that's great but map/reduce is a well-known 'embarrassingly parallelizable' algorithm. If the majority of your code is map/reduce that's great for you but a lot of code is not trivially parallelizable like that. The problem with 'no worry of performance losses' with multicore is that using multiple cores itself has a cost. You need to split up your workload, schedule the work across the cores, pass the actual data as messages to whatever 'task' abstraction you're using, and unless the garbage collector has fancy tricks, this will mean having to deep-copy the data to preserve thread safety. So again, there's no such thing as a free lunch in multicore.
    - nikofeyn 8y ago
      > If the majority of your code is map/reduce that's great for you who said it was? (it isn’t.) you asked for examples, and i gave the most recent one. > You need to split up your workload, schedule the work across the cores, pass the actual data as messages to whatever 'task' abstraction you're using, and unless the garbage collector has fancy tricks, this will mean having to deep-copy the data to preserve thread safety. you’re making a huge amount of assumptions and supposed “costs” here based upon the rather limiting nature of most programming languages when it comes to concurrency. most of the multicore programming i do is with actors with a data flow language. multicore programming is so trivial you don’t even think about it.

pjmlp 8y ago

Security exploits and plugin crashes on the other hand prove there is a benefit in using multiple processes instead.

nikofeyn 8y ago
well, trade offs are trade offs because then one has to worry about intraprocess communication. can you elaborate on security exploits? i would assume a closed off system with interprocess communication would be less vulnerable than that with intraprocess communication, which seems like it could be intercepted. but i do not know much about security. process crashes are of course a problem in terms of bringing down the whole process, but that generally isn’t a problem for me.
- pjmlp 8y ago
  Each process would execute with the minimal set of permissions that it needs to perform its tasks. Whereas in interprocess, each thread can do everything that the whole process is allowed to do, so a security exploit in e.g. file parser, opens the door for doing other stuff that a file parser shouldn't be allowed to start with. An easy to use IPC is to use pipes, mailboxes, message queues, just like channels. Yes it might be slower, but for a large set of problems it is fast enough.
BubRoss 8y ago
I think both are more a matter of architecture. There are many different ways of finding parallelism and they all have their place. There is no single silver bullet and more parallelism and concurrency are generally the right direction to make use of modern hardware.

yawaramin 8y ago

Do you have any analytical benchmarks regarding the benefits you've gotten from multicore support?

nikofeyn 8y ago
well just today i sped up a simple algorithm by a factor of two or three on larger data sets by simply turning on parallelism in a for loop, which distributes iterations across cores and then merges them afterwards. so multicore performance came for free. in other instances, when programming concurrent programs, i have no worry of performance losses because, again, multicore support comes for free. that is more qualitative, but it is important. and it means my concurrent programs are actually concurrent.
- yawaramin 8y ago
  Regarding your simple algorithm, that's great but map/reduce is a well-known 'embarrassingly parallelizable' algorithm. If the majority of your code is map/reduce that's great for you but a lot of code is not trivially parallelizable like that. The problem with 'no worry of performance losses' with multicore is that using multiple cores itself has a cost. You need to split up your workload, schedule the work across the cores, pass the actual data as messages to whatever 'task' abstraction you're using, and unless the garbage collector has fancy tricks, this will mean having to deep-copy the data to preserve thread safety. So again, there's no such thing as a free lunch in multicore.
  - nikofeyn 8y ago
    > If the majority of your code is map/reduce that's great for you who said it was? (it isn’t.) you asked for examples, and i gave the most recent one. > You need to split up your workload, schedule the work across the cores, pass the actual data as messages to whatever 'task' abstraction you're using, and unless the garbage collector has fancy tricks, this will mean having to deep-copy the data to preserve thread safety. you’re making a huge amount of assumptions and supposed “costs” here based upon the rather limiting nature of most programming languages when it comes to concurrency. most of the multicore programming i do is with actors with a data flow language. multicore programming is so trivial you don’t even think about it.