Symmetric Multiprocessor OS Considerations
In an SMP system, the kernel can execute on any processor, and typically each
processor does self-scheduling from the pool of available processes or threads.
The kernel can be constructed as multiple processes or multiple threads, allowing
portions of the kernel to execute in parallel. The SMP approach complicates the OS.
The OS designer must deal with the complexity due to sharing resources (like data
structures) and coordinating actions (like accessing devices) from multiple parts of
the OS executing at the same time. Techniques must be employed to resolve and
synchronize claims to resources.
An SMP operating system manages processor and other computer resources
so that the user may view the system in the same fashion as a multiprogramming
uniprocessor system. A user may construct applications that use multiple processes
or multiple threads within processes without regard to whether a single processor
or multiple processors will be available. Thus, a multiprocessor OS must provide all
the functionality of a multiprogramming system plus additional features to accommodate
multiple processors. The key design issues include the following:
Simultaneous concurrent processes or threads:=> Kernel routines need to be
reentrant to allow several processors to execute the same kernel code simultaneously.
With multiple processors executing the same or different parts of the
kernel, kernel tables and management structures must be managed properly
to avoid data corruption or invalid operations.
Scheduling:=> Any processor may perform scheduling, which complicates the
task of enforcing a scheduling policy and assuring that corruption of the scheduler
data structures is avoided. If kernel-level multithreading is used, then the
opportunity exists to schedule multiple threads from the same process simultaneously
on multiple processors.
Synchronization:=> With multiple active processes having potential access to
shared address spaces or shared I/O resources, care must be taken to provide
effective synchronization. Synchronization is a facility that enforces mutual
exclusion and event ordering.
Memory management:=> Memory management on a multiprocessor must deal
with all of the issues found on uniprocessor computers and is discussed in Part
Three. In addition, the OS needs to exploit the available hardware parallelism
to achieve the best performance. The paging mechanisms on different processors
must be coordinated to enforce consistency when several processors
share a page or segment and to decide on page replacement. The reuse of
physical pages is the biggest problem of concern; that is, it must be guaranteed
that a physical page can no longer be accessed with its old contents before the
page is put to a new use.
Reliability and fault tolerance:=> The OS should provide graceful degradation
in the face of processor failure. The scheduler and other portions of the OS
must recognize the loss of a processor and restructure management tables
accordingly.
Because multiprocessor OS design issues generally involve extensions to
solutions to multiprogramming uniprocessor design problems, we do not treat
multiprocessor operating systems separately.
Multicore OS Considerations
The considerations for multicore systems include all the design issues discussed so
far in this section for SMP systems. But additional concerns arise. The issue is one
of the scale of the potential parallelism. Current multicore vendors offer systems
with up to eight cores on a single chip. With each succeeding processor technology
generation, the number of cores and the amount of shared and dedicated cache
memory increases, so that we are now entering the era of “many-core” systems.
The design challenge for a many-core multicore system is to efficiently
harness the multicore processing power and intelligently manage the substantial
on-chip resources efficiently. A central concern is how to match the inherent parallelism
of a many-core system with the performance requirements of applications.
The potential for parallelism in fact exists at three levels in contemporary multicore
system. First, there is hardware parallelism within each core processor, known as
instruction level parallelism, which may or may not be exploited by application programmers
and compilers. Second, there is the potential for multiprogramming and
multithreaded execution within each processor. Finally, there is the potential for
a single application to execute in concurrent processes or threads across multiple
cores. Without strong and effective OS support for the last two types of parallelism
just mentioned, hardware resources will not be efficiently used.
In essence, then, since the advent of multicore technology, OS designers have
been struggling with the problem of how best to extract parallelism from computing
workloads. A variety of approaches are being explored for next-generation operating
systems.
PARALLELISM WITHIN APPLICATIONS:=> Most applications can, in principle, be
subdivided into multiple tasks that can execute in parallel, with these tasks then
being implemented as multiple processes, perhaps each with multiple threads. The
difficulty is that the developer must decide how to split up the application work into
independently executable tasks. That is, the developer must decide what pieces can
or should be executed asynchronously or in parallel. It is primarily the compiler and
the programming language features that support the parallel programming design
process. But, the OS can support this design process, at minimum, by efficiently
allocating resources among parallel tasks as defined by the developer.
Perhaps the most effective initiative to support developers is implemented in
the latest release of the UNIX-based Mac OS X operating system. Mac OS X 10.6
includes a multicore support capability known as Grand Central Dispatch (GCD). GCD does not help the developer decide how to break up a task or application into
separate concurrent parts. But once a developer has identified something that can
be split off into a separate task, GCD makes it as easy and noninvasive as possible
to actually do so.
In essence, GCD is a thread pool mechanism, in which the OS maps tasks onto
threads representing an available degree of concurrency (plus threads for blocking
on I/O). Windows also has a thread pool mechanism (since 2000), and thread
pools have been heavily used in server applications for years. What is new in GCD
is the extension to programming languages to allow anonymous functions (called
blocks) as a way of specifying tasks. GCD is hence not a major evolutionary step.
Nevertheless, it is a new and valuable tool for exploiting the available parallelism of
a multicore system.
One of Apple’s slogans for GCD is “islands of serialization in a sea of concurrency.”
That captures the practical reality of adding more concurrency to run-of-the-mill
desktop applications. Those islands are what isolate developers from the thorny
problems of simultaneous data access, deadlock, and other pitfalls of multithreading.
Developers are encouraged to identify functions of their applications that would be
better executed off the main thread, even if they are made up of several sequential or
otherwise partially interdependent tasks. GCD makes it easy to break off the entire
unit of work while maintaining the existing order and dependencies between subtasks.
In later chapters, we look at some of the details of GCD.
VIRTUAL MACHINE APPROACH:=> An alternative approach is to recognize that
with the ever-increasing number of cores on a chip, the attempt to multiprogram
individual cores to support multiple applications may be a misplaced use of
resources [JACK10]. If instead, we allow one or more cores to be dedicated to a
particular process and then leave the processor alone to devote its efforts to that
process, we avoid much of the overhead of task switching and scheduling decisions.
The multicore OS could then act as a hypervisor that makes a high-level decision
to allocate cores to applications but does little in the way of resource allocation
beyond that.
The reasoning behind this approach is as follows. In the early days of computing,
one program was run on a single processor. With multiprogramming,
each application is given the illusion that it is running on a dedicated processor.
Multiprogramming is based on the concept of a process, which is an abstraction of
an execution environment. To manage processes, the OS requires protected space,
free from user and program interference. For this purpose, the distinction between
kernel mode and user mode was developed. In effect, kernel mode and user mode
abstracted the processor into two processors. With all these virtual processors, however,
come struggles over who gets the attention of the real processor. The overhead
of switching between all these processors starts to grow to the point where responsiveness
suffers, especially when multiple cores are introduced. But with many-core
systems, we can consider dropping the distinction between kernel and user mode.
In this approach, the OS acts more like a hypervisor. The programs themselves take
on many of the duties of resource management. The OS assigns an application a
processor and some memory, and the program itself, using metadata generated by
the compiler, would best know how to use these resources.
