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Multi-Threaded Programming Without the Pain
holden karau writes "Gigahertz are out and cores are in. Programmers must begin to develop applications that take full advantage of the increasing number of cores present in modern computers. However, multi-threaded development has been notoriously hard to do. Researcher Stefanus Du Toit discusses and demonstrates RapidMind, a software system he co-authored, that takes the pain out of multi-threaded programming in C++. For his demo he created a program on the PlayStation 3 representing thousands of chickens, each independently tracked by a single processing core. The talk itself is interesting but the demo is golden."
I didn't know the PS3 had thousands of cores ;)
I think what he meant was 'each tracked in a separate thread'...obviously each core is still handling many threads. I haven't watched the presentation and don't plan on it until later today, too much to do and I'd rather read something about it. It just sounds like it provides an efficient high level way to write a multi threaded app. Evolutionary but not revolutionary?
Both, RapidMind and Peakstream are proprietary commercial solutions and those companies are trying to lock users into their particular framework. What we really need is the equivalent as true open-source solution, perhaps as a gcc extension. Does anyone know if there is progress being made on this?
From the site:
Man thats some funny stuff. Wow that cracked me up. A *games* company using a tool that has this level of indirection?!? I sure hope these guys got a lot of money from their sucker VC to roll in.
Look guys. There is no multi-processing silver bullet. It isn't even such a hard problem, *if you stop trying to solve it at such a low level*. Break your application into separate pieces that, *don't need to communicate very often.* Then this is the same kind of problem scalable websites like Google, MySpace, Hotmail and so on, have already, just without having to factor in the reliability issues. Finer grained multi-threading just leads to deadlocks and is really hard to debug. If you *really must* render the same sphere on 100 processors at the same time, then you need the speed of a custom coded solution. But you don't so let it go. The main loop of your program will be just fine as a single threaded implementation, 1 processor will do, and farm the 10% code / 90 % heavy lifting out in big clean chunks to other processors. If you find yourself writing some bizzare multi-threaded message passing system so that you can have 100s of threads all modifying the same live object model at the same time -- you are fucked, just forget about it 'cause you will never be able to debug that one killer bug that you know is going to get you right as you go to ship.
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You are, of course, correct. The other thing that people need to keep in mind is that there is rarely only a single process running on a given machine. For applications where it makes sense, such as video rendering on a machine doing nothing else, multithreading can increase overall performance. For applications where it doesn't or where there are other things running on the same machine, you normally end up with worse overall performance by trying to get your naturally single-threaded program to run on multiple cores at once when the extra cores would be better dedicated to running things other than your program.
Multithreading is a tool. Just like more traditional tools, like the hammer, this one is useful for certain applications. But multithreading is not the only tool at your disposal - people need to stop looking at everything as if it were a nail.
I think you've missed the mark a little.
I believe what he is saying is that if your an application developer who is pushing the limits of what a single core is capable of in terms of performance, then you are going to see decreasing rate of improvement and then stagnation because the focus of hardware development is shifting away from more power in a single core to more power because there are more cores.
At some point you will hit a wall, and for single-threaded applications you're going to reach a point where there isn't any more power to be had.
Therefore if you want to tap that extra power that a multi-core processor has, you will by definition *need* to start multi-threaded programming. This isn't about you people who are happy with the speed and power that you already have, research is pointless if you already have everything you could possibly need. This is for the people who push the edge, at some point if you need more you will need to learn to multi-thread correctly.
And a simpler way to do it, is gold in my books.
*From a former University classmate of Stephanos*
This is not a sig.
"old-style Unix development, because of the 'lightweight process model'. It's a unix-ism that's on the way out but until it disappears we will have some things like Ruby that don't 'get it'."
I'm not sure I follow you there. Lightweight process models are perfect for multi-cores. The more the merrier. Given the andundance of high-quality networking and commodity machines, heavyweight programs outside of very niche areas that use internal threads are less suitable for distributed computing than lighteight process models that can call across the network or the OS to other lightweight processes. A heavywight process can only scale to the number of cores avaiable on the machine it is running on, whereas a flock of lightweight processes can scale to the locally available cores and onto to other machines in a distributed fashion without a major bump in the road between local and remote. Any machine that has multi-cores today could easily run, say, one Ruby process per core with negligible overhead.
And it's silly for it to be "on the way out".
Anyone remember the Amiga? It had a preemptive multitasking OS that lacked hardware memory protection because the hardware it was running on couldn't support it. And while the OS itself was very fast and efficient, the overall system was relatively crash-prone, because any memory-related programming error in any running application had a decent chance of taking down the system.
Fast forward to today. Every computer sold has hardware memory protection built-in. Anyone who doesn't know why that's a good thing needs to spend time on an Amiga.
And yet, despite that, threads are all the rage. Why? Because people have this idiotic belief that they're somehow "more efficient" than processes. Such people probably program about as well as they think, which is to say not very well. Threads are indeed more efficient at context switching than processes, but the real question is: does that really matter? In the vast majority of cases, it doesn't, because in the vast majority of cases multiple threads are being used to make the user interface responsive. There's no way a human being can tell the difference between a millisecond-level context switch time and a microsecond-level one.
On top of that, processes bring one critical advantage to the table that threads don't: memory protection. And for the same reason memory protection is important at the OS and hardware level, so too is it important at the process and thread level: it allows clean, protected separation of concern and greater overall application stability.
The vast, vast majority of applications that are multithreaded don't actually need the slight additional context switch performance advantage that threads bring to the table, but they very much need the memory protection facilities that processes bring to the table. Which is another way of saying that if your application needs concurrency, you're a fool if you blindly use threads instead of processes.
Even Windows supports fork() these days, with the POSIX subsystem (available, as far as I know, on any Windows 2000 and later system), so creating a clone of your current process is dirt simple even under Windows. End result: application authors have no good reason to use threads over processes unless they've actually done the math and can prove that their application really needs the slight performance advantage of threads more than the significant reliability advantage of processes.
As to the other reason for using threads, the sharing of memory, there's this really cool new technology out these days. Maybe you've heard of it. It's called "shared memory". It's only been available for 20 years or so. No wonder most people haven't heard of it. Being forced to explicitly declare what's shared and what isn't is a good thing, because it makes you program easier to maintain, easier to debug, and more reliable -- all at the same time.
The bottom line is this: if you need concurrency in your application, you should be using processes, not threads. If you insist on using threads, you'd better have a damned good reason for it, because the reliability implications of threads are hugely negative while the performance implications are modest at best.
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Good morning slashdot!
As the (slightly terrified to find himself mentioned on slashdot) presenter in the video linked to above I thought I'd respond to a couple of comments in bulk. First off, I'm part of a much bigger team at RapidMind that builds this software to make targeting multicore and stream processors easier -- the system and the "chicken demo" was a group effort, and you can read more about it and the company in general in the article linked to from here, which unfortunately is PDF-only.
For those crying out about multi-threading not being the solution: you're absolutely right! Our platform's approach to programming multi-core processors is to expose a data parallel model. In this model, the programmer explicitly deals with parallel programming (writing algorithms to work well on arbitrarily many cores) but all of the standard multi-threading issues such as deadlocks and race conditions are avoided, and the developer doesn't worry about how many cores there actually are.
And no, the chicken demo didn't run each chicken on an individual core ;). But it did automatically scale to however many cores were available -- 6 SPUs and a PPU on the PS3, and 16 SPUs and 2 PPUs on a Cell Blade (on which we originally showed the simulation at GDC 2006).
If you want to learn more, drop by our website at http://www.rapidmind.net. You can sign up for a free no-strings-attached evaluation version if you want to try it yourself.
I'm sure the demonstration would've been a lot more difficult if he'd used philosophers instead of chickens. Thing is, chickens can't even hold chopsticks. A chicken just goes straight for the feed, so there's just one resource being acquired. It's still possible for a chicken to starve, but as chickens don't eat that much it's more likely that any shut-out chickens would simply go hungry for a while, and then get to eat before starving.
---GEC
I'm but the humble pupil, seeking to snatch the scratchbuilt pebble from the master's fully articulated hand
On a single core without hyperthreading, your best bet (if you can) is to write very efficient single-threaded code, using non-blocking I/O as much as possible. Some language runtimes require the use of lots of threads even on single-core systems, but that's horrible.
Once you've got multiple cores, getting multiple threads of execution (either in multiple processes or in multiple threads) makes a lot of sense. I believe hyperthreading benefits particularly such code that has multiple threads executing in the same bit of code since the parallelism there is within a memory management domain, so OpenMP is better there than pthreads, and pthreads is (probably) better than processes. On the other hand, if you're potentially working across a cluster (cue the beowulf jokes!) your code had better be written with processes (and probably MPI) in mind. Of course if you're going that way, you also ought to spend on getting a good interconnect network...
All in all, getting proper high performance is tricky. The best guide to making things go faster is to try to reduce the amount of shared state between threads-of-execution. Reducing shared state also helps to make the code easier to debug. (Alas, dealing with the bits of state that must be shared is what makes life hard.)
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