5 ms·

And what are those advantages? Function call ABIs are a standard way to change what is executing and come back when it is done. Does that really need to change

And what are those advantages? Function call ABIs are a standard way to change what is executing and come back when it is done. Does that really need to change? Other software architecture can be built on top of that, you don't need to change the way you call a function with assembly to structure software differently.

kragen 7y ago
The advantages are that you can do threads, exceptions, lazy sequences, backtracking, tail-call elimination for state machines, and so on. (The disadvantages are the same.) Yes, you can emulate these on top of function-call-based ABIs, but you incur the usual emulation overhead.
cat199 7y ago
this sub-discussion about tail calls, etc. is in reference to: https://dspace.mit.edu/bitstream/handle/1721.1/5753/AIM-443.pdf https://dspace.mit.edu/bitstream/handle/1721.1/5753/AIM-443.... that series of papers was released adjacent to the development of the scheme language which will generally optimize out the need for a call stack and replace it with essentially goto in certain cases. as for 'changing the way you call a function' this subtopic is primarily of importance for language/compiler implementers; while you don't "need" to change the way you call a function, often doing so can speed up the program hugely, or allow things that were not otherwise possible (e.g. infinite recursion without stack overflow)
- dreamcompiler 7y ago
  Tail call elimination isn't always possible, but it's the gateway drug to continuations which are always possible, and continuations are the gateway drug to actors, and once you have actors you're free to move any element of your program anywhere, break it into pieces and put them back together, go nuts, it just works--and now you're able to write code on asynchronous million-node networks without having to worry about locks, mutating global data, shared stuff, and everything else that gets in the way of using modern hardware.
  - tsimionescu 7y ago
    If you have code that doesn't need to mutate data, it is already easy-ish to write on whatever scale you want. The problem is that there are very few algorithms and business problems that don't require shared state to work. I'm not sure how actors or continuations could solve the problem of creating a distributed database of clients, or even of computing histograms on data in parallel, significantly more easily than more traditional programming paradigms.
    - toast0 7y ago
      Rather than accessing the shared data directly, you send a message to the actor that owns that piece of shared data, that message could be a request for some data, or a request to modify it in some way. The actor that owns the data reads its mailbox of requests and processes them without worrying about locks and things, because it has exclusive access. The actor that needs to access the data doesn't worry about locks and things because it's not directly accessing it, it's just sending a message. The system worries about locks and things, because the message mailboxes are shared state to some extent. If you can cleanly separate ownership of different pieces of data into different actors, you get parallelism. If there's too much dependency between the pieces of data, so that separating ownership makes things more complex, maybe that becomes more visible.
      - tsimionescu 7y ago
        That sounds nice, but it means that all reads and writes are serialized. You can't scale a system like this to, say, work for sign-up and retrieval of all Gmail users.
        toast0 7y ago
        To scale up, you need to partition/shard the space. For gmail users, you could hash on the (normalized) username, and all users with hash between A and B would go to one actor, etc. You don't need (or want) parallelism for signup on a single user id, but you could hash or otherwise divide that work to that level. You can also do a partitioned work queue with a (smallish) worker pool per partition; and have the queue keep track of any keys with a current worker, to assign further work to that worker (to avoiding parallel work on the same key and the locking that requires)
gumby 7y ago
There are significantly more calling semantics beyond “push a frame and branch” as Kragen enumerates. Some, like coroutines, are visible to the high-level programmer; others, such as tail call optimization, might be invisible.

kragen 7y ago

The advantages are that you can do threads, exceptions, lazy sequences, backtracking, tail-call elimination for state machines, and so on. (The disadvantages are the same.) Yes, you can emulate these on top of function-call-based ABIs, but you incur the usual emulation overhead.

cat199 7y ago

this sub-discussion about tail calls, etc. is in reference to: https://dspace.mit.edu/bitstream/handle/1721.1/5753/AIM-443.pdf https://dspace.mit.edu/bitstream/handle/1721.1/5753/AIM-443.... that series of papers was released adjacent to the development of the scheme language which will generally optimize out the need for a call stack and replace it with essentially goto in certain cases. as for 'changing the way you call a function' this subtopic is primarily of importance for language/compiler implementers; while you don't "need" to change the way you call a function, often doing so can speed up the program hugely, or allow things that were not otherwise possible (e.g. infinite recursion without stack overflow)

dreamcompiler 7y ago
Tail call elimination isn't always possible, but it's the gateway drug to continuations which are always possible, and continuations are the gateway drug to actors, and once you have actors you're free to move any element of your program anywhere, break it into pieces and put them back together, go nuts, it just works--and now you're able to write code on asynchronous million-node networks without having to worry about locks, mutating global data, shared stuff, and everything else that gets in the way of using modern hardware.
- tsimionescu 7y ago
  If you have code that doesn't need to mutate data, it is already easy-ish to write on whatever scale you want. The problem is that there are very few algorithms and business problems that don't require shared state to work. I'm not sure how actors or continuations could solve the problem of creating a distributed database of clients, or even of computing histograms on data in parallel, significantly more easily than more traditional programming paradigms.
  - toast0 7y ago
    Rather than accessing the shared data directly, you send a message to the actor that owns that piece of shared data, that message could be a request for some data, or a request to modify it in some way. The actor that owns the data reads its mailbox of requests and processes them without worrying about locks and things, because it has exclusive access. The actor that needs to access the data doesn't worry about locks and things because it's not directly accessing it, it's just sending a message. The system worries about locks and things, because the message mailboxes are shared state to some extent. If you can cleanly separate ownership of different pieces of data into different actors, you get parallelism. If there's too much dependency between the pieces of data, so that separating ownership makes things more complex, maybe that becomes more visible.
    - tsimionescu 7y ago
      That sounds nice, but it means that all reads and writes are serialized. You can't scale a system like this to, say, work for sign-up and retrieval of all Gmail users.
      - toast0 7y ago
        To scale up, you need to partition/shard the space. For gmail users, you could hash on the (normalized) username, and all users with hash between A and B would go to one actor, etc. You don't need (or want) parallelism for signup on a single user id, but you could hash or otherwise divide that work to that level. You can also do a partitioned work queue with a (smallish) worker pool per partition; and have the queue keep track of any keys with a current worker, to assign further work to that worker (to avoiding parallel work on the same key and the locking that requires)

gumby 7y ago

There are significantly more calling semantics beyond “push a frame and branch” as Kragen enumerates. Some, like coroutines, are visible to the high-level programmer; others, such as tail call optimization, might be invisible.