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I use a large Platform computational compute cluster often. We use individual processes (not threads) to crunch big data and in general that approach works well

by 16s 14y ago

I use a large Platform computational compute cluster often. We use individual processes (not threads) to crunch big data and in general that approach works well. Each process has its own memory space and its own little bit of the work load to complete. One process can crash or throw and exception and the others keep on going. Having no shared streams or shared data containers to worry with (mutexes, locks, etc) is just wonderful. We call it poor man's parallelism and some guys who have done a lot of threading make light of it. It's so simple (compared to threads) that it seems like a naive approach. But it performs so well that it's hard to argue with the results.

th0ma5 14y ago
I've dabbled in larger than usual parallelism and this has been my experience as well. On *nix systems processes are cheap, while on M$ threads are cheap, but regardless of those, having a shared-nothing lock free approach has me feeling limitless.
eblume 14y ago
We do the same doing some terabyte-scale data processing. We try and load all of the shared state in to a read-only structure ahead of time, then fork off the workers. This way, copy-on-write memory architectures get the advantage of only persisting the data once, yet we get multiple processes working from a very very large shared set of data, all without having to do any sort of IPC or locking. The only locks we used are around streams used for a very basic sort of IPC used to communicate to shared stream controllers like logfiles - these do perform very poorly compared to 'proper' parallelism but they make up for a very tiny fraction of the total workload. We've found that this will beat a 'better' parallelism even if we need to do a lot of extra or redundant work due to the lack of IPC or reduction due to the no-overhead approach, although this will of course be highly dependent on the problem at hand.
KirinDave 14y ago
Actually, it's only "simpler" in that you are familiar with it and perhaps your programming environment of choice lacks good support for multi-threaded programming. It's certainly not "simpler" from the perspective of resource efficiency (e.g., it's so easy to spoil Copy-on-Write's benefits) and usually it asks some other process to do the hard work of coordination. From the perspective of correctness, introducing multiple processes to your system greatly increases the number of failure states and vastly complicates error recovery. I think you're dismissing the state of the art on multiple fronts, as is the article. From single-variable STM (of which Haskell and Clojure both have excellent implementations) to battle-tested and well-understood concurrency primitives in the Java standard concurrency library, multi-threaded programming is more approachable and performant now than it has ever been. But the article is oddest in that it seems to hold up Erlang as a way forward, but Erlang is just a different model built on top of thread-based concurrency. If the argument is the old pthread-ish model of "1 thread per call" and very primitive synchronization tools are antiquated... then who is he arguing with? Erlang uses actors, Haskell uses sorcery (really, it's fancy; they turn normal-looking threaded code into erlang-ish sliced execution under the covers), Go uses fancy structures along with coroutines, Java uses Executors to implement higher-level work off patterns, and everyone is using Futures and Promises now.
- slurgfest 14y ago
  It is gratuitous to take the word "simpler" as some kind of proof that the person you are responding to is an ignorant who uses objectively bad tools. Reality is less clear. "Simpler" clearly referred to the complexity and the mess created by synchronization in a shared-everything environment, which is where most languages are at with threading (Haskell, Clojure and Erlang are not most languages). This is a valid criticism. You may lose Copy-on-Write, but sharing everything by default, at a low level, does raise the need for complex synchronization, which has its own performance issues. And this is very good reason to explore and use other concurrency models. This is something that you and the article and the person you are responding to all seem to agree on. Except that you seem to take any interesting concurrency interface to be threading (no, goroutines are NOT threads) and you draw the strange moral that only the complex problems of threads can be addressed with nice tools and new ideas, but somehow not the problems of other basic concurrency models. Assuming we have available helpful interfaces for using processes, threads and greenlets - all of which have been produced somewhere - the argument should be about the performance of the foolproofed backends. Preferably based on numbers.
  - KirinDave 14y ago
    > It is gratuitous to take the word "simpler" as some kind of proof that the person you are responding to is an ignorant who uses objectively bad tools. Given that you subsequently make the point that most toolkits are bad, I think my assumption was safe. But let's not lose the plot here, process-level parallelism makes sense in many cases. It's just not a valid replacement for per-process concurrency and it is most definitely not "simpler." Your failure modes become incredibly complex and varied, and that was my only point here. More modern environments–the ones you should be using unless you have a compelling reason to do otherwise–use shared-state concurrency as a platform for higher level abstractions. But this is still "multicore in-process parallelism" and the underlying model is still threading. Building abstractions on top of in-process parallelism is not rejecting the underlying layer, it's embracing it. If you are not using modern tools, then yeah correct concurrency is hard and variable degrees of underlying parallelism only exacerbate that. It is also hard to start fires with just flint, steel and tinder. New topic, please. So I'm not sure what you're taking exception to other than your perception of my tone.

by 16s 14y ago

th0ma5 14y ago

I've dabbled in larger than usual parallelism and this has been my experience as well. On *nix systems processes are cheap, while on M$ threads are cheap, but regardless of those, having a shared-nothing lock free approach has me feeling limitless.

eblume 14y ago

We do the same doing some terabyte-scale data processing. We try and load all of the shared state in to a read-only structure ahead of time, then fork off the workers. This way, copy-on-write memory architectures get the advantage of only persisting the data once, yet we get multiple processes working from a very very large shared set of data, all without having to do any sort of IPC or locking. The only locks we used are around streams used for a very basic sort of IPC used to communicate to shared stream controllers like logfiles - these do perform very poorly compared to 'proper' parallelism but they make up for a very tiny fraction of the total workload. We've found that this will beat a 'better' parallelism even if we need to do a lot of extra or redundant work due to the lack of IPC or reduction due to the no-overhead approach, although this will of course be highly dependent on the problem at hand.

KirinDave 14y ago

Actually, it's only "simpler" in that you are familiar with it and perhaps your programming environment of choice lacks good support for multi-threaded programming. It's certainly not "simpler" from the perspective of resource efficiency (e.g., it's so easy to spoil Copy-on-Write's benefits) and usually it asks some other process to do the hard work of coordination. From the perspective of correctness, introducing multiple processes to your system greatly increases the number of failure states and vastly complicates error recovery. I think you're dismissing the state of the art on multiple fronts, as is the article. From single-variable STM (of which Haskell and Clojure both have excellent implementations) to battle-tested and well-understood concurrency primitives in the Java standard concurrency library, multi-threaded programming is more approachable and performant now than it has ever been. But the article is oddest in that it seems to hold up Erlang as a way forward, but Erlang is just a different model built on top of thread-based concurrency. If the argument is the old pthread-ish model of "1 thread per call" and very primitive synchronization tools are antiquated... then who is he arguing with? Erlang uses actors, Haskell uses sorcery (really, it's fancy; they turn normal-looking threaded code into erlang-ish sliced execution under the covers), Go uses fancy structures along with coroutines, Java uses Executors to implement higher-level work off patterns, and everyone is using Futures and Promises now.

slurgfest 14y ago
It is gratuitous to take the word "simpler" as some kind of proof that the person you are responding to is an ignorant who uses objectively bad tools. Reality is less clear. "Simpler" clearly referred to the complexity and the mess created by synchronization in a shared-everything environment, which is where most languages are at with threading (Haskell, Clojure and Erlang are not most languages). This is a valid criticism. You may lose Copy-on-Write, but sharing everything by default, at a low level, does raise the need for complex synchronization, which has its own performance issues. And this is very good reason to explore and use other concurrency models. This is something that you and the article and the person you are responding to all seem to agree on. Except that you seem to take any interesting concurrency interface to be threading (no, goroutines are NOT threads) and you draw the strange moral that only the complex problems of threads can be addressed with nice tools and new ideas, but somehow not the problems of other basic concurrency models. Assuming we have available helpful interfaces for using processes, threads and greenlets - all of which have been produced somewhere - the argument should be about the performance of the foolproofed backends. Preferably based on numbers.
- KirinDave 14y ago
  > It is gratuitous to take the word "simpler" as some kind of proof that the person you are responding to is an ignorant who uses objectively bad tools. Given that you subsequently make the point that most toolkits are bad, I think my assumption was safe. But let's not lose the plot here, process-level parallelism makes sense in many cases. It's just not a valid replacement for per-process concurrency and it is most definitely not "simpler." Your failure modes become incredibly complex and varied, and that was my only point here. More modern environments–the ones you should be using unless you have a compelling reason to do otherwise–use shared-state concurrency as a platform for higher level abstractions. But this is still "multicore in-process parallelism" and the underlying model is still threading. Building abstractions on top of in-process parallelism is not rejecting the underlying layer, it's embracing it. If you are not using modern tools, then yeah correct concurrency is hard and variable degrees of underlying parallelism only exacerbate that. It is also hard to start fires with just flint, steel and tinder. New topic, please. So I'm not sure what you're taking exception to other than your perception of my tone.