If Makefile.direct is used, in its default configuration the
Boehm-Demers-Weiser garbage collector is not thread-safe. Generally, it can be
made thread-safe by building the collector with -DGC_THREADS compilation
flag. This has primarily the following effects:
- It causes the garbage collector to stop all other threads when it needs to see a consistent memory state. It intercepts thread creation and termination events to maintain a list of client threads to be stopped when needed.
- It causes the collector to acquire the allocator lock around essentially all allocation and garbage collection activity. Since this lock is used for all allocation-related activity, only one thread can be allocating or collecting at one point. This inherently limits performance of multi-threaded applications on multiprocessors.
On most platforms, the allocator lock is implemented as a spin lock with exponential back-off. Longer wait times are implemented by yielding and/or sleeping. If a collection is in progress, the pure spinning stage is skipped. This has the uncontested advantage that most uniprocessor lock acquisitions are very cheap. It has the disadvantage that the application may sleep for small periods of time even when there is work to be done. And threads may be unnecessarily woken up for short periods. Nonetheless, this scheme empirically outperforms native queue-based mutual exclusion implementations in most cases, sometimes drastically so.
The collector uses two facilities to enhance collector scalability on multiprocessors. They are intended to be used together. (The following refers to Makefile.direct again.)
- Building the collector with
-DPARALLEL_MARKallows the collector to run the mark phase in parallel in multiple threads, and thus on multiple processors (or processor cores). The mark phase typically consumes the large majority of the collection time. Thus, this largely parallelizes the garbage collector itself, though not the allocation process. Currently the marking is performed by the thread that triggered the collection, together with N - 1 dedicated threads, where N is the number of processors (cores) detected by the collector. The dedicated marker threads are created when the client callsGC_start_mark_threads()or when the client starts the first non-main thread after the GC initialization (or after fork operation in a child process). Another effect of this flag is to switch to a more concurrent implementation ofGC_malloc_many, so that free lists can be built and memory can be cleared by more than one thread concurrently. - Building the collector with
-DTHREAD_LOCAL_ALLOCadds support for thread-local allocation. This causesGC_malloc(actuallyGC_malloc_kind) andGC_gcj_mallocto be redefined to perform thread-local allocation.
Memory returned from thread-local allocators is completely interchangeable
with that returned by the standard allocators. It may be used by other
threads. The only difference is that, if the thread allocates enough memory
of a certain kind, it will build a thread-local free list for objects of that
kind, and allocate from that. This greatly reduces locking. The thread-local
free lists are refilled using GC_malloc_many.
An important side effect of this flag is to replace the default spin-then-sleep lock to be replaced by a spin-then-queue based implementation. This reduces performance for the standard allocation functions, though it usually improves performance when thread-local allocation is used heavily, and, thus, the number of short-duration lock acquisitions is greatly reduced.
Also, USE_RWLOCK macro (experimental) should be noted which changes the
allocator lock implementation base from a mutex (CRITICAL_SECTION in case
of Win32) to pthread_rwlock_t (SRWLOCK, respectively), thus enabling
acquisition of a slim lock in the reader (shared) mode where possible. See
the description of GC_call_with_reader_lock and GC_REVEAL_POINTER entities
in gc.h for more details.
We use an algorithm similar to that developed by Endo, Taura, and Yonezawa at the University of Tokyo. However, the data structures and implementation are different, and represent a smaller change to the original collector source, probably at the expense of extreme scalability. Some of the refinements they suggest, e.g. splitting large objects, were also incorporated into our approach.
The global mark stack is transformed into a global work queue. Unlike the usual case, it never shrinks during a mark phase. The mark threads remove objects from the queue by copying them to a local mark stack and changing the global descriptor to zero, indicating that there is no more work to be done for this entry. This removal is done with no synchronization. Thus it is possible for more than one worker to remove the same entry, resulting in some work duplication.
The global work queue grows only if a marker thread decides to return some of its local mark stack to the global one. This is done if the global queue appears to be running low, or if the local stack is in danger of overflowing. It does require synchronization, but should be relatively rare.
The sequential marking code is reused to process local mark stacks. Hence the amount of additional code required for parallel marking is minimal.
It should be possible to use incremental/generational collection in the
presence of the parallel collector by calling GC_enable_incremental, but
the current implementation does not allow interruption of the parallel marker,
so the latter is mostly avoided if the client sets the collection time limit.
Gcj-style mark descriptors do not currently mix with the combination of local allocation and incremental collection. They should work correctly with one or the other, but not both.
The number of marker threads is set on startup to the number of available
processor cores (or to the value of either GC_MARKERS or GC_NPROCS
environment variable, if provided). If only a single processor is detected,
parallel marking is disabled.
Note that setting GC_NPROCS to 1 also causes some lock acquisitions inside
the collector to immediately yield the processor instead of busy waiting
first. In the case of a multiprocessor and a client with multiple
simultaneously runnable threads, this may have disastrous performance
consequences (e.g. a factor of 10 slowdown).
We conducted some simple experiments with a version of our GC benchmark that was slightly modified to run multiple concurrent client threads in the same address space. Each client thread does the same work as the original benchmark, but they share a heap. This benchmark involves very little work outside of memory allocation. This was run with an ancient GC (released in 2000) on a dual processor Pentium III/500 machine under Linux 2.2.12.
Running with a thread-unsafe collector, the benchmark ran in 9 seconds. With
the simple thread-safe collector, built with -DGC_THREADS, the execution
time increased to 10.3 seconds, or 23.5 elapsed seconds with two clients. (The
times for the malloc/free version with glibc malloc are 10.51 (standard
library, pthreads not linked), 20.90 (one thread, pthreads linked), and 24.55
seconds, respectively. The benchmark favors a garbage collector, since most
objects are small.)
The following table gives execution times for the collector built with
parallel marking and thread-local allocation support
(-DGC_THREADS -DPARALLEL_MARK -DTHREAD_LOCAL_ALLOC). We tested the client
using either one or two marker threads, and running one or two client threads.
Note that the client uses thread-local allocation exclusively. With
-DTHREAD_LOCAL_ALLOC the collector switches to a locking strategy that
is better tuned to less frequent lock acquisition. The standard allocation
primitives thus perform slightly worse than without -DTHREAD_LOCAL_ALLOC,
and should be avoided in time-critical code.
(The results using pthread_mutex_lock directly for acquiring the allocator
lock would have been worse still, at least for older versions of LinuxThreads.
With -DTHREAD_LOCAL_ALLOC, we first repeatedly try to acquire the allocator
lock with pthread_mutex_try_lock, busy-waiting between attempts. After
a fixed number of attempts, we use pthread_mutex_lock.)
These measurements do not use incremental collection, nor was prefetching enabled in the marker. We used the C version of the benchmark. All measurements are in elapsed seconds on an unloaded machine.
| Number of client threads | 1 marker thread (secs.) | 2 marker threads (secs.) |
|---|---|---|
| 1 | 10.45 | 7.85 |
| 2 | 19.95 | 12.3 |
The execution time for the single threaded case is slightly worse than with simple locking. However, even the single-threaded benchmark runs faster than even the thread-unsafe version if a second processor is available. The execution time for two clients with thread-local allocation time is only 1.4 times the sequential execution time for a single thread in a thread-unsafe environment, even though it involves twice the client work. That represents close to a factor of 2 improvement over the 2 client case with the old collector. The old collector clearly still suffered from some contention overhead, in spite of the fact that the locking scheme had been fairly well tuned.
Full linear speedup (i.e. the same execution time for 1 client on one processor as 2 clients on 2 processors) is probably not achievable on this kind of hardware even with such a small number of processors, since the memory system is a major constraint for the garbage collector, the processors usually share a single memory bus, and thus the aggregate memory bandwidth does not increase in proportion to the number of processors (cores).
These results are likely to be very sensitive to both hardware and OS issues. Preliminary experiments with an older Pentium Pro machine running an older kernel were far less encouraging.