> All portability issues aside, if one is writing an application in
> Linux that one would be tempted to make multithreaded for
> whatever reason, what would be the better Linux way of doing
Let's go back to basics. Look inside your computer. See what's there:
1) one (or more) CPUs
2) some RAM
3) a PCI bus, containing:
4) -- a SCSI/IDE controller
5) -- a network card
6) -- a graphics card
These are all the parts of your computer that are smart enough to accomplish
some amount of work on their own. The SCSI or IDE controller can read data
from disk without bothering any other components. The network card can send
and receive packets fairly autonomously. Each CPU in an SMP system operates
nearly independently. An ideal application could have all of these devices
doing useful work at the same time.
When people think of "multithreading," often they are just looking for a way
to extract more concurrency from their machine. You want all these
independent parts to be working on your task simultaneously. There are many
different mechanisms for achieveing this. Here we go...
A naively-written "server" program (eg a web server) might be coded like so:
* Read configuration file - all other work stops while data is fetched from
* Parse configuration file - all other work stops while CPU/RAM work on
parsing the file
* Wait for a network connection - all other work stops while waiting for
* Read request from client - all other work stops while waiting for incoming
* Process request - all other work stops while CPU/RAM figure out what to do
- all other work stops while disk fetches requested file
* Write reply to client - all other work stops until final buffer
I've phrased the descriptions to emphasize that only one resource is being
used at once - the rest of the system sits twiddling its thumbs until the
one device in question finishes its task.
Can we do better? Yes, thanks to various programming techniques that allow
us to keep more of the system busy. The most important bottleneck is
probably the network - it makes no sense for our server to wait while a slow
client takes its time acknowledging our packets. By using standard UNIX
multiplexed I/O (select()/poll()), we can send buffers of data to the kernel
just when space becomes available in the outgoing queue; we can also accept
client requests piecemeal, as the individual packets flow in. And while
we're waiting for packets from one client, we can be processing another
The improved program performs better since it keeps the CPU and network busy
at the same time. However, it will be more difficult to write, since we have
to maintain the connection state manually, rather than implicitly on the
So now the server handles many clients at once, and it gracefully handles
slow clients. Can we do even better? Yes, let's look at the next
bottleneck - disk I/O. If a client asks for a file that's not in memory, the
whole server will come to a halt while it read()s the data in. But the
SCSI/IDE controller is smart enough to handle this alone; why not let the
CPU and network take care of other clients while the disk does its work?
How do we go about doing this? Well, it's UNIX, right? We talk to disk files
the same way we talk to network sockets, so let's just select()/poll() on
the disk files too, and everything will be dandy... (Unfortunately we can't
do that - the designers of UNIX made a huge mistake and decided against
implementing non-blocking disk I/O as they had with network I/O. Big booboo.
For that reason, it was impossible to do concurrent disk I/O until the POSIX
Asynchronous I/O standard came along. So we go learn this whole bloated API,
in the process finding out that we can no longer use select()/poll(), and
must switch to POSIX RT signals - sigwaitinfo() - to control our server***).
After the dust has settled, we can now keep the CPU, network card, and the
disk busy all the time -- so our server is even faster.
Notice that our program has been made heavily concurrent, and I haven't even
used the word "thread" yet!
Let's take it one step further. Packets and buffers are now coming in and
out so quickly that the CPU is sweating just handling all the I/O. But say
we have one or three more CPU's sitting there idle - how can we get them
going, too? We need to run multiple request handlers at once.
Conventional multithreading is *one* possible way to accomplish this; it's
rather brute-force, since the threads share all their memory, sockets, etc.
(and full VM sharing doesn't scale optimally, since interrupts must be sent
to all the CPUs when the memory layout changes).
Lots of UNIX servers run multiple *processes*- the "sub-servers" might not
share anything, or they might file cache or request queue. If we were brave,
we'd think carefully about what resources really should be shared between
the sub-servers, and then implement it manually using Linux's awesome
clone() API. But we're not, so let's retreat to the brightly-lit
neightborhood that is pthreads.
We break out the POSIX pthread standard, and find it's quite a bit more
usable than AIO. We set up one server thread for each CPU; the threads now
share a common queue of requests****. We add locking primitives around the
shared data structures in our file cache. Now as soon as a new packet or
disk buffer arrives, any one of the CPUs can grab it and perform the
associated processing, while the other CPUs handle their own work. The
server gets even faster.
That's basically the state-of-the-art in concurrent servers as it stands
today. All of the independent devices in the computer are being used
simultaneously; the server plows through its workload, never waiting for
network packets or disk I/O. There are still bottlenecks - for instance, RAM
and PCI bandwidth are limited resources. We can't just keep adding more CPUs
to make it faster, since they all contend for access to the same pool of RAM
and the same bus. If the server still isn't fast enough, we need a better
machine architecture that separates RAM and I/O busses into
concurrently-accessible pools (e.g. a high-end SGI server).
There are various other tricks that can be done to speed up network servers,
like passing files directly from the buffer cache to the network card. This
one is currently frowned upon by the Linux community, since the time spent
copying data around the system is small compared to the overhead imposed by
fiddling with virtual memory. Lots of work does go into reducing system call
and context switch overhead; that's one of the reasons TUX was developed.
Let's drop the "web server" example and talk about another application that
benefits from concurrency - number crunching. This is a much simpler case,
since the only resources you're worried about are the CPUs and RAM. To get
all the CPU's going at once, you'll need to run multiple threads or
processes. To get truly optimal throughput, you might choose to go the
process route, so that shared memory is kept to an absolute minimum. (Not
that pthreads is a terrible choice; it can work very well for this purpose)
In summary, when "multithreading" floats into your mind, think
"concurrency." Think very carefully about how you might simultaneously
exploit all of the independent resources in your computer. Due to the long
and complex history of OS development, a different API is usually required
to communicate with each device. (e.g. old-school UNIX has always handled
non-blocking network I/O with select(), but non-blocking disk I/O is rather
new and must be done with AIO or threads; and don't even ask about
asynchronous access to the graphics card =).
Don't let these differences obscure your goal: just figure out how to use
the machine to its fullest potential. That's the Linux way of doing things:
think, then act.
The ideas here mostly come from informative pages like Dan Kegel's "C10K"
http://www.kegel.com/c10k.html, and from reading various newsgroup postings
and UNIX books.
*** POSIX AIO is so ugly, in fact, that it's not unheard-of to simply spawn
a pool of threads that handle disk I/O. You can send requests and replies
via a pipe or socket, which fits right in with the old select()/poll() event
*** If we're servicing many, many clients at once, then running a huge
select()/poll() in each thread will have outrageous overhead. In that case,
we'd have to use a shared POSIX I/O signal queue, which can be done with
clone(), but not pthreads()... See Zach Brown's phhttpd
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