@node Multithreading
@chapter Multithreading

Multithreading is a programming paradigm.  In a multithreaded program,
multiple threads execute concurrently (or quasi concurrently) at different
places in the program.

There are three motivations for using multithreading in a program:
@itemize @bullet
@item
Exploiting CPU hardware with multiple execution units.  Nowadays, many CPUs
have 2 to 8 execution cores in a single chip.  Additionally, often multiple
CPU chips are combined in a single package.  Thus, some CPU packages support
64 or 96 simultaneous threads of execution.
@item
Simplifying program architecture.  When a program has to read from different
file descriptors, network sockets, or event channels at the same time, the
classical single-threaded architecture is to have a main loop which uses
@code{select} or @code{poll} on all the descriptors and then dispatches
according to from which descriptor input arrived.  In a multi-threaded
program, you allocate one thread for each descriptor, and these threads can
be programmed and managed independently.
@item
Offloading work from signal handlers.  A signal handler is not allowed to
call @code{malloc}; therefore you are very limited in what you can do in
a signal handler.  But a signal handler can notify a thread, and the thread
can then do the appropriate processing, as complex as it needs to be.
@end itemize

A multithreading API offers
@itemize @bullet
@item
Primitives for creating threads, for waiting until threads are terminated,
and for reaping their results.
@item
Primitives through which different threads can operate on the same data or
use some data structures for communicating between the threads.  These are
called ``mutexes'' or ``locks''.
@item
Primitives for executing a certain (initialization) code at most once.
@item
Primitives for notifying one or more other threads.  These are called wait
queues or ``condition variables''.
@item
Primitives for allowing different threads to have different values for a
variable.  Such a variable is said to reside in ``thread-local storage'' or
``thread-specific storage''.
@item
Primitives for relinquishing control for some time and letting other threads
go.
@end itemize

Note: Programs that achieve multithreading through OpenMP (cf. the gnulib
module @samp{openmp}) don't create and manage their threads themselves.
Nevertheless, they need to use mutexes/locks in many cases.

@menu
* Multithreading APIs::
* Choosing a multithreading API::
* POSIX multithreading::
* ISO C multithreading::
* Gnulib multithreading::
* Multithreading Optimizations::
@end menu

@node Multithreading APIs
@section The three multithreading APIs

Three multithreading APIs are available to Gnulib users:
@itemize @bullet
@item
POSIX multithreading,
@item
ISO C multithreading,
@item
Gnulib multithreading.
@end itemize

They are supported on all platforms that have multithreading in one form or
the other.  Currently, these are all platforms supported by Gnulib, except
for Minix.

The main differences are:
@itemize @bullet
@item
The exit code of a thread is a pointer in the POSIX and Gnulib APIs, but
only an @code{int} in the ISO C API.
@item
The POSIX API has additional facilities for detaching threads, setting the
priority of a thread, assigning a thread to a certain set of processors,
and much more.
@item
In the POSIX and ISO C APIs, most functions have a return code, and you
are supposed to check the return code; even locking and unlocking a lock
can fail.  In the Gnulib API, many functions don't have a return code; if
they cannot complete, the program aborts.  This sounds harsh, but such
aborts have not been reported in 12 years.
@item
In the ISO C API, the initialization of a statically allocated lock is
clumsy: You have to initialize it through a once-only function.
@end itemize

@node Choosing a multithreading API
@section Choosing the right multithreading API

Here are guidelines for determining which multithreading API is best for
your code.

In programs that use advanced POSIX APIs, such as spin locks,
detached threads (@code{pthread_detach}),
signal blocking (@code{pthread_sigmask}),
priorities (@code{pthread_setschedparam}),
processor affinity (@code{pthread_setaffinity_np}), it is best to use
the POSIX API.  This is because you cannot convert an ISO C @code{thrd_t}
or a Gnulib @code{gl_thread_t} to a POSIX @code{pthread_t}.

In code that is shared with glibc, it is best to use the POSIX API as well.

In libraries, it is best to use the Gnulib API.  This is because it gives
the person who builds the library an option
@samp{--enable-threads=@{isoc,posix,windows@}}, that determines on which
native multithreading API of the platform to rely.  In other words, with
this choice, you can minimize the amount of glue code that your library
needs to contain.

In the other cases, the POSIX API and the Gnulib API are equally well suited.

The ISO C API is never the best choice, as of this writing (2020).

@node POSIX multithreading
@section The POSIX multithreading API

The POSIX multithreading API is documented in POSIX
@url{https://pubs.opengroup.org/onlinepubs/9699919799/}.

To make use of POSIX multithreading, even on platforms that don't support it
natively (most prominently, native Windows), use the following Gnulib modules:
@multitable @columnfractions .75 .25
@headitem Purpose @tab Module
@item For thread creation and management:@tie{} @tab @code{pthread-thread}
@item For simple and recursive locks:@tie{} @tab @code{pthread-mutex}
@item For read-write locks:@tie{} @tab @code{pthread-rwlock}
@item For once-only execution:@tie{} @tab @code{pthread-once}
@item For ``condition variables'' (wait queues):@tie{} @tab @code{pthread-cond}
@item For thread-local storage:@tie{} @tab @code{pthread-tss}
@item For relinquishing control:@tie{} @tab @code{sched_yield}
@item For spin locks:@tie{} @tab @code{pthread-spin}
@end multitable

There is also a convenience module named @code{pthread} which depends on all
of these (except @code{sched_yield}); so you don't need to enumerate these
modules one by one.

@node ISO C multithreading
@section The ISO C multithreading API

The ISO C multithreading API is documented in ISO C 11
@url{http://www.open-std.org/jtc1/sc22/wg14/www/docs/n1570.pdf}.

To make use of ISO C multithreading, even on platforms that don't support it
or have severe bugs, use the following Gnulib modules:
@multitable @columnfractions .85 .15
@headitem Purpose @tab Module
@item For thread creation and management:@tie{} @tab @code{thrd}
@item For simple locks, recursive locks, and read-write locks:@tie{}
      @tab @code{mtx}
@item For once-only execution:@tie{} @tab @code{mtx}
@item For ``condition variables'' (wait queues):@tie{} @tab @code{cnd}
@item For thread-local storage:@tie{} @tab @code{tss}
@end multitable

There is also a convenience module named @code{threads} which depends on all
of these; so you don't need to enumerate these modules one by one.

@node Gnulib multithreading
@section The Gnulib multithreading API

The Gnulib multithreading API is documented in the respective include files:
@itemize
@item
@code{<glthread/thread.h>}
@item
@code{<glthread/lock.h>}
@item
@code{<glthread/cond.h>}
@item
@code{<glthread/tls.h>}
@item
@code{<glthread/yield.h>}
@end itemize

To make use of Gnulib multithreading, use the following Gnulib modules:
@multitable @columnfractions .85 .15
@headitem Purpose @tab Module
@item For thread creation and management:@tie{} @tab @code{thread}
@item For simple locks, recursive locks, and read-write locks:@tie{}
      @tab @code{lock}
@item For once-only execution:@tie{} @tab @code{lock}
@item For ``condition variables'' (wait queues):@tie{} @tab @code{cond}
@item For thread-local storage:@tie{} @tab @code{tls}
@item For relinquishing control:@tie{} @tab @code{yield}
@end multitable

The Gnulib multithreading supports a configure option
@samp{--enable-threads=@{isoc,posix,windows@}}, that chooses the underlying
thread implementation.  Currently (2020):
@itemize @bullet
@item
@code{--enable-threads=posix} is supported and is the best choice on all
platforms except for native Windows.  It may also work, to a limited extent,
on mingw with the @code{winpthreads} library, but is not recommended there.
@item
@code{--enable-threads=windows} is supported and is the best choice on
native Windows platforms (mingw and MSVC).
@item
@code{--enable-threads=isoc} is supported on all platforms that have the
ISO C multithreading API.  However, @code{--enable-threads=posix} is always
a better choice.
@end itemize

@node Multithreading Optimizations
@section Optimizations of multithreaded code

Despite all the optimizations of multithreading primitives that have been
implemented over the years --- from
@url{https://en.wikipedia.org/wiki/Compare-and-swap,
atomic operations in hardware},
over @url{https://en.wikipedia.org/wiki/Futex, futexes} and
@url{https://www.efficios.com/blog/2019/02/08/linux-restartable-sequences/,
restartable sequences}
in the Linux kernel, to lock elision
@url{https://lwn.net/Articles/534758/, [1]}
@url{https://www.gnu.org/software/libc/manual/html_node/Elision-Tunables.html,
[2]})
--- single-threaded programs can still profit performance-wise from the
assertion that they are single-threaded.

Gnulib defines four facilities that help optimizing for the single-threaded
case.

@itemize @bullet
@item
The Gnulib multithreading API, when used on glibc @leq{} 2.32 and *BSD systems,
uses weak symbols to detect whether the program is linked with
@code{libpthread}.  If not, the program has no way to create additional
threads and must therefore be single-threaded.  This optimization applies
to all the Gnulib multithreading API (locks, thread-local storage, and more).
@item
The @code{thread-optim} module, on glibc @geq{} 2.32 systems, allows your code
to skip locking between threads (regardless which of the three multithreading
APIs you use).  You need extra code for this: include the
@code{"thread-optim.h"} header file, and use the macro @code{gl_multithreaded}
like this:
@smallexample
bool mt = gl_multithreaded ();
if (mt) gl_lock_lock (some_lock);
...
if (mt) gl_lock_unlock (some_lock);
@end smallexample
@item
The @code{unlocked-io} module is applicable only if all the programs in your
package are single-threaded.  It optimizes the operations on @code{FILE}
streams.  You need extra code for this: include the @code{"unlocked-io.h"}
header file.  Some Gnulib modules that do operations on @code{FILE} streams
have these preparations already included.
@item
You may define the C macro @code{GNULIB_WCHAR_SINGLE}, if all the programs in
your package are single-threaded and won't change the locale after it has
been initialized.  This macro optimizes the functions @code{mbrtowc} and
@code{wcwidth}.
@end itemize
