Lock Versus Lock-Free..

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Lock Versus Lock-Free..


The class of problems that can be solved by lock-free approaches is limited.

Furthermore, lock-free approaches can require restructuring a problem.
As soon as multiple shared data-structures are modified 
simultaneously,the only practical approach is to use a lock.

All lock-free dynamic-size data-structures using such CAA 
(Compare-and-assign) require some form of garbage collector to lazily 
delete storage when it is no longer referenced. In languages with 
garbage collection, this capability comes for free (at the cost of 
garbage collection). For languages without garbage collection, the code 
is complex and error prone in comparison with locks, requiring 
epoch-based reclamation, read-copy-update (RCU), or hazard pointers.

While better performance is claimed for lock-free data-structures, there 
is no long-term evidence to support this claim. Many high-performance 
locking situations, e.g., operating system kernels and databases, 
continue to use locking in various forms, even though there are a broad 
class of lock-free data-structure readily available.

While lock-free data-structures cannot have deadlock, there is seldom 
deadlock using locks for the simple class of problems solvable using 
lock-free approaches. For example, protecting basic data-structure 
operations with locks is usually very straightforward. Normally deadlock 
occurs when accessing multiple resources simultaneously, which is not a 
class of problems dealt with by lock-free approaches. Furthermore, 
disciplined lock usage, such as ranking locks to avoid deadlock, works 
well in practice and is not onerous for the programmer.Finally, some 
static analysis tools are helpful for detecting deadlock scenarios.

Lock-free approaches have thread-kill tolerance, meaning no thread owns 
a lock, so any thread can terminate at an arbitrary point without 
leaving a lock in the closed state. However, within an application, 
thread kill is an unusual operation and thread failure means an 
unrecoverable error or major reset.

A lock-free approach always allows progress of other threads, whereas 
locks can cause delays if the lock owner is preempted. However,this 
issue is a foundational aspect of preemptive concurrency. And there are 
ways to mitigate this issue for locks using scheduler-activation 
techniques. However, lock-free is not immune to delays. If a page is 
evicted containing part of the lock-based or lockfree data, there is a 
delay. Hence, lock free is no better than lock based if the page
fault occurs on frequently accessed shared data. Given the increasing 
number of processors and large amount of memory on modern computers, 
neither of these delays should occur often.

Lock-free approaches are reentrant, and hence, can be used in signal 
handlers, which are implicitly concurrent. Locking approaches cannot 
deal with this issue. Lock-free approaches are claimed not to have 
priority inversion. However, inversion can occur because of the spinning 
required with atomic instructions, like CAA, as the hardware does not 
provide a bound for spinning threads. Hence, a low-priority thread can 
barge head of a high-priority thread because the low-priority thread 
just happens to win the race at the CAA instruction. Essentially,
priority inversion is a foundational aspect of preemptive concurrency 
and can only be mitigated.

The conclusion is that for unmanaged programming language (i.e., no 
garbage collection), using classical locks is simple, efficient, 
general, and causes issues only when the problem scales to multiple 
locks. For managed programming-languages, lock-free data-structures are 
easier to implement, but only handle a specific set of problems, and the 
programmer must accept other idiosyncrasies, like pauses in
execution for garbage collection.



Thank you,
Amine Moulay Ramdane.