766 lines
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766 lines
30 KiB
HTML
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<title>TCMalloc : Thread-Caching Malloc</title>
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<h1>TCMalloc : Thread-Caching Malloc</h1>
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<address>Sanjay Ghemawat</address>
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<h2><A name=motivation>Motivation</A></h2>
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<p>TCMalloc is faster than the glibc 2.3 malloc (available as a
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separate library called ptmalloc2) and other mallocs that I have
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tested. ptmalloc2 takes approximately 300 nanoseconds to execute a
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malloc/free pair on a 2.8 GHz P4 (for small objects). The TCMalloc
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implementation takes approximately 50 nanoseconds for the same
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operation pair. Speed is important for a malloc implementation
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because if malloc is not fast enough, application writers are inclined
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to write their own custom free lists on top of malloc. This can lead
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to extra complexity, and more memory usage unless the application
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writer is very careful to appropriately size the free lists and
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scavenge idle objects out of the free list.</p>
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<p>TCMalloc also reduces lock contention for multi-threaded programs.
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For small objects, there is virtually zero contention. For large
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objects, TCMalloc tries to use fine grained and efficient spinlocks.
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ptmalloc2 also reduces lock contention by using per-thread arenas but
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there is a big problem with ptmalloc2's use of per-thread arenas. In
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ptmalloc2 memory can never move from one arena to another. This can
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lead to huge amounts of wasted space. For example, in one Google
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application, the first phase would allocate approximately 300MB of
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memory for its URL canonicalization data structures. When the first
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phase finished, a second phase would be started in the same address
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space. If this second phase was assigned a different arena than the
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one used by the first phase, this phase would not reuse any of the
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memory left after the first phase and would add another 300MB to the
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address space. Similar memory blowup problems were also noticed in
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other applications.</p>
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<p>Another benefit of TCMalloc is space-efficient representation of
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small objects. For example, N 8-byte objects can be allocated while
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using space approximately <code>8N * 1.01</code> bytes. I.e., a
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one-percent space overhead. ptmalloc2 uses a four-byte header for
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each object and (I think) rounds up the size to a multiple of 8 bytes
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and ends up using <code>16N</code> bytes.</p>
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<h2><A NAME="Usage">Usage</A></h2>
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<p>To use TCMalloc, just link TCMalloc into your application via the
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"-ltcmalloc" linker flag.</p>
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<p>You can use TCMalloc in applications you didn't compile yourself,
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by using LD_PRELOAD:</p>
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<pre>
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$ LD_PRELOAD="/usr/lib/libtcmalloc.so" <binary>
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</pre>
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<p>LD_PRELOAD is tricky, and we don't necessarily recommend this mode
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of usage.</p>
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<p>TCMalloc includes a <A HREF="heap_checker.html">heap checker</A>
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and <A HREF="heapprofile.html">heap profiler</A> as well.</p>
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<p>If you'd rather link in a version of TCMalloc that does not include
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the heap profiler and checker (perhaps to reduce binary size for a
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static binary), you can link in <code>libtcmalloc_minimal</code>
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instead.</p>
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<h2><A NAME="Overview">Overview</A></h2>
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<p>TCMalloc assigns each thread a thread-local cache. Small
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allocations are satisfied from the thread-local cache. Objects are
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moved from central data structures into a thread-local cache as
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needed, and periodic garbage collections are used to migrate memory
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back from a thread-local cache into the central data structures.</p>
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<center><img src="overview.gif"></center>
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<p>TCMalloc treats objects with size <= 256K ("small" objects)
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differently from larger objects. Large objects are allocated directly
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from the central heap using a page-level allocator (a page is a 8K
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aligned region of memory). I.e., a large object is always
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page-aligned and occupies an integral number of pages.</p>
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<p>A run of pages can be carved up into a sequence of small objects,
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each equally sized. For example a run of one page (4K) can be carved
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up into 32 objects of size 128 bytes each.</p>
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<h2><A NAME="Small_Object_Allocation">Small Object Allocation</A></h2>
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<p>Each small object size maps to one of approximately 88 allocatable
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size-classes. For example, all allocations in the range 961 to 1024
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bytes are rounded up to 1024. The size-classes are spaced so that
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small sizes are separated by 8 bytes, larger sizes by 16 bytes, even
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larger sizes by 32 bytes, and so forth. The maximal spacing is
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controlled so that not too much space is wasted when an allocation
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request falls just past the end of a size class and has to be rounded
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up to the next class.</p>
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<p>A thread cache contains a singly linked list of free objects per
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size-class.</p>
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<center><img src="threadheap.gif"></center>
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<p>When allocating a small object: (1) We map its size to the
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corresponding size-class. (2) Look in the corresponding free list in
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the thread cache for the current thread. (3) If the free list is not
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empty, we remove the first object from the list and return it. When
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following this fast path, TCMalloc acquires no locks at all. This
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helps speed-up allocation significantly because a lock/unlock pair
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takes approximately 100 nanoseconds on a 2.8 GHz Xeon.</p>
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<p>If the free list is empty: (1) We fetch a bunch of objects from a
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central free list for this size-class (the central free list is shared
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by all threads). (2) Place them in the thread-local free list. (3)
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Return one of the newly fetched objects to the applications.</p>
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<p>If the central free list is also empty: (1) We allocate a run of
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pages from the central page allocator. (2) Split the run into a set
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of objects of this size-class. (3) Place the new objects on the
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central free list. (4) As before, move some of these objects to the
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thread-local free list.</p>
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<h3><A NAME="Sizing_Thread_Cache_Free_Lists">
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Sizing Thread Cache Free Lists</A></h3>
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<p>It is important to size the thread cache free lists correctly. If
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the free list is too small, we'll need to go to the central free list
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too often. If the free list is too big, we'll waste memory as objects
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sit idle in the free list.</p>
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<p>Note that the thread caches are just as important for deallocation
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as they are for allocation. Without a cache, each deallocation would
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require moving the memory to the central free list. Also, some threads
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have asymmetric alloc/free behavior (e.g. producer and consumer threads),
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so sizing the free list correctly gets trickier.</p>
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<p>To size the free lists appropriately, we use a slow-start algorithm
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to determine the maximum length of each individual free list. As the
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free list is used more frequently, its maximum length grows. However,
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if a free list is used more for deallocation than allocation, its
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maximum length will grow only up to a point where the whole list can
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be efficiently moved to the central free list at once.</p>
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<p>The psuedo-code below illustrates this slow-start algorithm. Note
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that <code>num_objects_to_move</code> is specific to each size class.
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By moving a list of objects with a well-known length, the central
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cache can efficiently pass these lists between thread caches. If
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a thread cache wants fewer than <code>num_objects_to_move</code>,
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the operation on the central free list has linear time complexity.
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The downside of always using <code>num_objects_to_move</code> as
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the number of objects to transfer to and from the central cache is
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that it wastes memory in threads that don't need all of those objects.
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<pre>
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Start each freelist max_length at 1.
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Allocation
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if freelist empty {
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fetch min(max_length, num_objects_to_move) from central list;
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if max_length < num_objects_to_move { // slow-start
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max_length++;
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} else {
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max_length += num_objects_to_move;
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}
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}
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Deallocation
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if length > max_length {
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// Don't try to release num_objects_to_move if we don't have that many.
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release min(max_length, num_objects_to_move) objects to central list
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if max_length < num_objects_to_move {
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// Slow-start up to num_objects_to_move.
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max_length++;
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} else if max_length > num_objects_to_move {
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// If we consistently go over max_length, shrink max_length.
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overages++;
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if overages > kMaxOverages {
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max_length -= num_objects_to_move;
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overages = 0;
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}
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}
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}
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</pre>
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See also the section on <a href="#Garbage_Collection">Garbage Collection</a>
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to see how it affects the <code>max_length</code>.
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<h2><A NAME="Large_Object_Allocation">Large Object Allocation</A></h2>
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<p>A large object size (> 256K) is rounded up to a page size (8K)
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and is handled by a central page heap. The central page heap is again
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an array of free lists. For <code>i < 128</code>, the
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<code>k</code>th entry is a free list of runs that consist of
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<code>k</code> pages. The <code>128</code>th entry is a free list of
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runs that have length <code>>= 128</code> pages: </p>
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<center><img src="pageheap.gif"></center>
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<p>An allocation for <code>k</code> pages is satisfied by looking in
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the <code>k</code>th free list. If that free list is empty, we look
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in the next free list, and so forth. Eventually, we look in the last
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free list if necessary. If that fails, we fetch memory from the
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system (using <code>sbrk</code>, <code>mmap</code>, or by mapping in
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portions of <code>/dev/mem</code>).</p>
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<p>If an allocation for <code>k</code> pages is satisfied by a run
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of pages of length > <code>k</code>, the remainder of the
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run is re-inserted back into the appropriate free list in the
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page heap.</p>
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<h2><A NAME="Spans">Spans</A></h2>
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<p>The heap managed by TCMalloc consists of a set of pages. A run of
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contiguous pages is represented by a <code>Span</code> object. A span
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can either be <em>allocated</em>, or <em>free</em>. If free, the span
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is one of the entries in a page heap linked-list. If allocated, it is
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either a large object that has been handed off to the application, or
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a run of pages that have been split up into a sequence of small
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objects. If split into small objects, the size-class of the objects
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is recorded in the span.</p>
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<p>A central array indexed by page number can be used to find the span to
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which a page belongs. For example, span <em>a</em> below occupies 2
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pages, span <em>b</em> occupies 1 page, span <em>c</em> occupies 5
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pages and span <em>d</em> occupies 3 pages.</p>
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<center><img src="spanmap.gif"></center>
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<p>In a 32-bit address space, the central array is represented by a a
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2-level radix tree where the root contains 32 entries and each leaf
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contains 2^14 entries (a 32-bit address space has 2^19 8K pages, and
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the first level of tree divides the 2^19 pages by 2^5). This leads to
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a starting memory usage of 64KB of space (2^14*4 bytes) for the
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central array, which seems acceptable.</p>
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<p>On 64-bit machines, we use a 3-level radix tree.</p>
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<h2><A NAME="Deallocation">Deallocation</A></h2>
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<p>When an object is deallocated, we compute its page number and look
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it up in the central array to find the corresponding span object. The
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span tells us whether or not the object is small, and its size-class
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if it is small. If the object is small, we insert it into the
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appropriate free list in the current thread's thread cache. If the
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thread cache now exceeds a predetermined size (2MB by default), we run
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a garbage collector that moves unused objects from the thread cache
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into central free lists.</p>
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<p>If the object is large, the span tells us the range of pages covered
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by the object. Suppose this range is <code>[p,q]</code>. We also
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lookup the spans for pages <code>p-1</code> and <code>q+1</code>. If
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either of these neighboring spans are free, we coalesce them with the
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<code>[p,q]</code> span. The resulting span is inserted into the
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appropriate free list in the page heap.</p>
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<h2>Central Free Lists for Small Objects</h2>
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<p>As mentioned before, we keep a central free list for each
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size-class. Each central free list is organized as a two-level data
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structure: a set of spans, and a linked list of free objects per
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span.</p>
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<p>An object is allocated from a central free list by removing the
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first entry from the linked list of some span. (If all spans have
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empty linked lists, a suitably sized span is first allocated from the
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central page heap.)</p>
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<p>An object is returned to a central free list by adding it to the
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linked list of its containing span. If the linked list length now
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equals the total number of small objects in the span, this span is now
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completely free and is returned to the page heap.</p>
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<h2><A NAME="Garbage_Collection">Garbage Collection of Thread Caches</A></h2>
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<p>Garbage collecting objects from a thread cache keeps the size of
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the cache under control and returns unused objects to the central free
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lists. Some threads need large caches to perform well while others
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can get by with little or no cache at all. When a thread cache goes
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over its <code>max_size</code>, garbage collection kicks in and then the
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thread competes with the other threads for a larger cache.</p>
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<p>Garbage collection is run only during a deallocation. We walk over
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all free lists in the cache and move some number of objects from the
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free list to the corresponding central list.</p>
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<p>The number of objects to be moved from a free list is determined
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using a per-list low-water-mark <code>L</code>. <code>L</code>
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records the minimum length of the list since the last garbage
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collection. Note that we could have shortened the list by
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<code>L</code> objects at the last garbage collection without
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requiring any extra accesses to the central list. We use this past
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history as a predictor of future accesses and move <code>L/2</code>
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objects from the thread cache free list to the corresponding central
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free list. This algorithm has the nice property that if a thread
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stops using a particular size, all objects of that size will quickly
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move from the thread cache to the central free list where they can be
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used by other threads.</p>
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<p>If a thread consistently deallocates more objects of a certain size
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than it allocates, this <code>L/2</code> behavior will cause at least
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<code>L/2</code> objects to always sit in the free list. To avoid
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wasting memory this way, we shrink the maximum length of the freelist
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to converge on <code>num_objects_to_move</code> (see also
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<a href="#Sizing_Thread_Cache_Free_Lists">Sizing Thread Cache Free Lists</a>).
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<pre>
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Garbage Collection
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if (L != 0 && max_length > num_objects_to_move) {
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max_length = max(max_length - num_objects_to_move, num_objects_to_move)
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}
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</pre>
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<p>The fact that the thread cache went over its <code>max_size</code> is
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an indication that the thread would benefit from a larger cache. Simply
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increasing <code>max_size</code> would use an inordinate amount of memory
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in programs that have lots of active threads. Developers can bound the
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memory used with the flag --tcmalloc_max_total_thread_cache_bytes.</p>
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<p>Each thread cache starts with a small <code>max_size</code>
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(e.g. 64KB) so that idle threads won't pre-allocate memory they don't
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need. Each time the cache runs a garbage collection, it will also try
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to grow its <code>max_size</code>. If the sum of the thread cache
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sizes is less than --tcmalloc_max_total_thread_cache_bytes,
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<code>max_size</code> grows easily. If not, thread cache 1 will try
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to steal from thread cache 2 (picked round-robin) by decreasing thread
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cache 2's <code>max_size</code>. In this way, threads that are more
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active will steal memory from other threads more often than they are
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have memory stolen from themselves. Mostly idle threads end up with
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small caches and active threads end up with big caches. Note that
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this stealing can cause the sum of the thread cache sizes to be
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greater than --tcmalloc_max_total_thread_cache_bytes until thread
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cache 2 deallocates some memory to trigger a garbage collection.</p>
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<h2><A NAME="performance">Performance Notes</A></h2>
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<h3>PTMalloc2 unittest</h3>
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<p>The PTMalloc2 package (now part of glibc) contains a unittest
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program <code>t-test1.c</code>. This forks a number of threads and
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performs a series of allocations and deallocations in each thread; the
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threads do not communicate other than by synchronization in the memory
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allocator.</p>
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<p><code>t-test1</code> (included in
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<code>tests/tcmalloc/</code>, and compiled as
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<code>ptmalloc_unittest1</code>) was run with a varying numbers of
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threads (1-20) and maximum allocation sizes (64 bytes -
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32Kbytes). These tests were run on a 2.4GHz dual Xeon system with
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hyper-threading enabled, using Linux glibc-2.3.2 from RedHat 9, with
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one million operations per thread in each test. In each case, the test
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was run once normally, and once with
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<code>LD_PRELOAD=libtcmalloc.so</code>.
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<p>The graphs below show the performance of TCMalloc vs PTMalloc2 for
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several different metrics. Firstly, total operations (millions) per
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elapsed second vs max allocation size, for varying numbers of
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threads. The raw data used to generate these graphs (the output of the
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<code>time</code> utility) is available in
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<code>t-test1.times.txt</code>.</p>
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<table>
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<tr>
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<td><img src="tcmalloc-opspersec.vs.size.1.threads.png"></td>
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<td><img src="tcmalloc-opspersec.vs.size.2.threads.png"></td>
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<td><img src="tcmalloc-opspersec.vs.size.3.threads.png"></td>
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</tr>
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<tr>
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<td><img src="tcmalloc-opspersec.vs.size.4.threads.png"></td>
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<td><img src="tcmalloc-opspersec.vs.size.5.threads.png"></td>
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<td><img src="tcmalloc-opspersec.vs.size.8.threads.png"></td>
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</tr>
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<tr>
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<td><img src="tcmalloc-opspersec.vs.size.12.threads.png"></td>
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<td><img src="tcmalloc-opspersec.vs.size.16.threads.png"></td>
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<td><img src="tcmalloc-opspersec.vs.size.20.threads.png"></td>
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</tr>
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</table>
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<ul>
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<li> TCMalloc is much more consistently scalable than PTMalloc2 - for
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all thread counts >1 it achieves ~7-9 million ops/sec for small
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allocations, falling to ~2 million ops/sec for larger
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allocations. The single-thread case is an obvious outlier,
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since it is only able to keep a single processor busy and hence
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can achieve fewer ops/sec. PTMalloc2 has a much higher variance
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on operations/sec - peaking somewhere around 4 million ops/sec
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for small allocations and falling to <1 million ops/sec for
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larger allocations.
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<li> TCMalloc is faster than PTMalloc2 in the vast majority of
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cases, and particularly for small allocations. Contention
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between threads is less of a problem in TCMalloc.
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<li> TCMalloc's performance drops off as the allocation size
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increases. This is because the per-thread cache is
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garbage-collected when it hits a threshold (defaulting to
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2MB). With larger allocation sizes, fewer objects can be stored
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in the cache before it is garbage-collected.
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<li> There is a noticeable drop in TCMalloc's performance at ~32K
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maximum allocation size; at larger sizes performance drops less
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quickly. This is due to the 32K maximum size of objects in the
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per-thread caches; for objects larger than this TCMalloc
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allocates from the central page heap.
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</ul>
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<p>Next, operations (millions) per second of CPU time vs number of
|
|
threads, for max allocation size 64 bytes - 128 Kbytes.</p>
|
|
|
|
<table>
|
|
<tr>
|
|
<td><img src="tcmalloc-opspercpusec.vs.threads.64.bytes.png"></td>
|
|
<td><img src="tcmalloc-opspercpusec.vs.threads.256.bytes.png"></td>
|
|
<td><img src="tcmalloc-opspercpusec.vs.threads.1024.bytes.png"></td>
|
|
</tr>
|
|
<tr>
|
|
<td><img src="tcmalloc-opspercpusec.vs.threads.4096.bytes.png"></td>
|
|
<td><img src="tcmalloc-opspercpusec.vs.threads.8192.bytes.png"></td>
|
|
<td><img src="tcmalloc-opspercpusec.vs.threads.16384.bytes.png"></td>
|
|
</tr>
|
|
<tr>
|
|
<td><img src="tcmalloc-opspercpusec.vs.threads.32768.bytes.png"></td>
|
|
<td><img src="tcmalloc-opspercpusec.vs.threads.65536.bytes.png"></td>
|
|
<td><img src="tcmalloc-opspercpusec.vs.threads.131072.bytes.png"></td>
|
|
</tr>
|
|
</table>
|
|
|
|
<p>Here we see again that TCMalloc is both more consistent and more
|
|
efficient than PTMalloc2. For max allocation sizes <32K, TCMalloc
|
|
typically achieves ~2-2.5 million ops per second of CPU time with a
|
|
large number of threads, whereas PTMalloc achieves generally 0.5-1
|
|
million ops per second of CPU time, with a lot of cases achieving much
|
|
less than this figure. Above 32K max allocation size, TCMalloc drops
|
|
to 1-1.5 million ops per second of CPU time, and PTMalloc drops almost
|
|
to zero for large numbers of threads (i.e. with PTMalloc, lots of CPU
|
|
time is being burned spinning waiting for locks in the heavily
|
|
multi-threaded case).</p>
|
|
|
|
|
|
<H2><A NAME="runtime">Modifying Runtime Behavior</A></H2>
|
|
|
|
<p>You can more finely control the behavior of the tcmalloc via
|
|
environment variables.</p>
|
|
|
|
<p>Generally useful flags:</p>
|
|
|
|
<table frame=box rules=sides cellpadding=5 width=100%>
|
|
|
|
<tr valign=top>
|
|
<td><code>TCMALLOC_SAMPLE_PARAMETER</code></td>
|
|
<td>default: 0</td>
|
|
<td>
|
|
The approximate gap between sampling actions. That is, we
|
|
take one sample approximately once every
|
|
<code>tcmalloc_sample_parmeter</code> bytes of allocation.
|
|
This sampled heap information is available via
|
|
<code>MallocExtension::GetHeapSample()</code> or
|
|
<code>MallocExtension::ReadStackTraces()</code>. A reasonable
|
|
value is 524288.
|
|
</td>
|
|
</tr>
|
|
|
|
<tr valign=top>
|
|
<td><code>TCMALLOC_RELEASE_RATE</code></td>
|
|
<td>default: 1.0</td>
|
|
<td>
|
|
Rate at which we release unused memory to the system, via
|
|
<code>madvise(MADV_DONTNEED)</code>, on systems that support
|
|
it. Zero means we never release memory back to the system.
|
|
Increase this flag to return memory faster; decrease it
|
|
to return memory slower. Reasonable rates are in the
|
|
range [0,10].
|
|
</td>
|
|
</tr>
|
|
|
|
<tr valign=top>
|
|
<td><code>TCMALLOC_LARGE_ALLOC_REPORT_THRESHOLD</code></td>
|
|
<td>default: 1073741824</td>
|
|
<td>
|
|
Allocations larger than this value cause a stack trace to be
|
|
dumped to stderr. The threshold for dumping stack traces is
|
|
increased by a factor of 1.125 every time we print a message so
|
|
that the threshold automatically goes up by a factor of ~1000
|
|
every 60 messages. This bounds the amount of extra logging
|
|
generated by this flag. Default value of this flag is very large
|
|
and therefore you should see no extra logging unless the flag is
|
|
overridden.
|
|
</td>
|
|
</tr>
|
|
|
|
<tr valign=top>
|
|
<td><code>TCMALLOC_MAX_TOTAL_THREAD_CACHE_BYTES</code></td>
|
|
<td>default: 16777216</td>
|
|
<td>
|
|
Bound on the total amount of bytes allocated to thread caches. This
|
|
bound is not strict, so it is possible for the cache to go over this
|
|
bound in certain circumstances. This value defaults to 16MB. For
|
|
applications with many threads, this may not be a large enough cache,
|
|
which can affect performance. If you suspect your application is not
|
|
scaling to many threads due to lock contention in TCMalloc, you can
|
|
try increasing this value. This may improve performance, at a cost
|
|
of extra memory use by TCMalloc. See <a href="#Garbage_Collection">
|
|
Garbage Collection</a> for more details.
|
|
</td>
|
|
</tr>
|
|
|
|
</table>
|
|
|
|
<p>Advanced "tweaking" flags, that control more precisely how tcmalloc
|
|
tries to allocate memory from the kernel.</p>
|
|
|
|
<table frame=box rules=sides cellpadding=5 width=100%>
|
|
|
|
<tr valign=top>
|
|
<td><code>TCMALLOC_SKIP_MMAP</code></td>
|
|
<td>default: false</td>
|
|
<td>
|
|
If true, do not try to use <code>mmap</code> to obtain memory
|
|
from the kernel.
|
|
</td>
|
|
</tr>
|
|
|
|
<tr valign=top>
|
|
<td><code>TCMALLOC_SKIP_SBRK</code></td>
|
|
<td>default: false</td>
|
|
<td>
|
|
If true, do not try to use <code>sbrk</code> to obtain memory
|
|
from the kernel.
|
|
</td>
|
|
</tr>
|
|
|
|
<tr valign=top>
|
|
<td><code>TCMALLOC_DEVMEM_START</code></td>
|
|
<td>default: 0</td>
|
|
<td>
|
|
Physical memory starting location in MB for <code>/dev/mem</code>
|
|
allocation. Setting this to 0 disables <code>/dev/mem</code>
|
|
allocation.
|
|
</td>
|
|
</tr>
|
|
|
|
<tr valign=top>
|
|
<td><code>TCMALLOC_DEVMEM_LIMIT</code></td>
|
|
<td>default: 0</td>
|
|
<td>
|
|
Physical memory limit location in MB for <code>/dev/mem</code>
|
|
allocation. Setting this to 0 means no limit.
|
|
</td>
|
|
</tr>
|
|
|
|
<tr valign=top>
|
|
<td><code>TCMALLOC_DEVMEM_DEVICE</code></td>
|
|
<td>default: /dev/mem</td>
|
|
<td>
|
|
Device to use for allocating unmanaged memory.
|
|
</td>
|
|
</tr>
|
|
|
|
<tr valign=top>
|
|
<td><code>TCMALLOC_MEMFS_MALLOC_PATH</code></td>
|
|
<td>default: ""</td>
|
|
<td>
|
|
If set, specify a path where hugetlbfs or tmpfs is mounted.
|
|
This may allow for speedier allocations.
|
|
</td>
|
|
</tr>
|
|
|
|
<tr valign=top>
|
|
<td><code>TCMALLOC_MEMFS_LIMIT_MB</code></td>
|
|
<td>default: 0</td>
|
|
<td>
|
|
Limit total memfs allocation size to specified number of MB.
|
|
0 means "no limit".
|
|
</td>
|
|
</tr>
|
|
|
|
<tr valign=top>
|
|
<td><code>TCMALLOC_MEMFS_ABORT_ON_FAIL</code></td>
|
|
<td>default: false</td>
|
|
<td>
|
|
If true, abort() whenever memfs_malloc fails to satisfy an allocation.
|
|
</td>
|
|
</tr>
|
|
|
|
<tr valign=top>
|
|
<td><code>TCMALLOC_MEMFS_IGNORE_MMAP_FAIL</code></td>
|
|
<td>default: false</td>
|
|
<td>
|
|
If true, ignore failures from mmap.
|
|
</td>
|
|
</tr>
|
|
|
|
<tr valign=top>
|
|
<td><code>TCMALLOC_MEMFS_MAP_PRVIATE</code></td>
|
|
<td>default: false</td>
|
|
<td>
|
|
If true, use MAP_PRIVATE when mapping via memfs, not MAP_SHARED.
|
|
</td>
|
|
</tr>
|
|
|
|
</table>
|
|
|
|
|
|
<H2><A NAME="compiletime">Modifying Behavior In Code</A></H2>
|
|
|
|
<p>The <code>MallocExtension</code> class, in
|
|
<code>malloc_extension.h</code>, provides a few knobs that you can
|
|
tweak in your program, to affect tcmalloc's behavior.</p>
|
|
|
|
<h3>Releasing Memory Back to the System</h3>
|
|
|
|
<p>By default, tcmalloc will release no-longer-used memory back to the
|
|
kernel gradually, over time. The <a
|
|
href="#runtime">tcmalloc_release_rate</a> flag controls how quickly
|
|
this happens. You can also force a release at a given point in the
|
|
progam execution like so:</p>
|
|
<pre>
|
|
MallocExtension::instance()->ReleaseFreeMemory();
|
|
</pre>
|
|
|
|
<p>You can also call <code>SetMemoryReleaseRate()</code> to change the
|
|
<code>tcmalloc_release_rate</code> value at runtime, or
|
|
<code>GetMemoryReleaseRate</code> to see what the current release rate
|
|
is.</p>
|
|
|
|
<h3>Memory Introspection</h3>
|
|
|
|
<p>There are several routines for getting a human-readable form of the
|
|
current memory usage:</p>
|
|
<pre>
|
|
MallocExtension::instance()->GetStats(buffer, buffer_length);
|
|
MallocExtension::instance()->GetHeapSample(&string);
|
|
MallocExtension::instance()->GetHeapGrowthStacks(&string);
|
|
</pre>
|
|
|
|
<p>The last two create files in the same format as the heap-profiler,
|
|
and can be passed as data files to pprof. The first is human-readable
|
|
and is meant for debugging.</p>
|
|
|
|
<h3>Generic Tcmalloc Status</h3>
|
|
|
|
<p>TCMalloc has support for setting and retrieving arbitrary
|
|
'properties':</p>
|
|
<pre>
|
|
MallocExtension::instance()->SetNumericProperty(property_name, value);
|
|
MallocExtension::instance()->GetNumericProperty(property_name, &value);
|
|
</pre>
|
|
|
|
<p>It is possible for an application to set and get these properties,
|
|
but the most useful is when a library sets the properties so the
|
|
application can read them. Here are the properties TCMalloc defines;
|
|
you can access them with a call like
|
|
<code>MallocExtension::instance()->GetNumericProperty("generic.heap_size",
|
|
&value);</code>:</p>
|
|
|
|
<table frame=box rules=sides cellpadding=5 width=100%>
|
|
|
|
<tr valign=top>
|
|
<td><code>generic.current_allocated_bytes</code></td>
|
|
<td>
|
|
Number of bytes used by the application. This will not typically
|
|
match the memory use reported by the OS, because it does not
|
|
include TCMalloc overhead or memory fragmentation.
|
|
</td>
|
|
</tr>
|
|
|
|
<tr valign=top>
|
|
<td><code>generic.heap_size</code></td>
|
|
<td>
|
|
Bytes of system memory reserved by TCMalloc.
|
|
</td>
|
|
</tr>
|
|
|
|
<tr valign=top>
|
|
<td><code>tcmalloc.pageheap_free_bytes</code></td>
|
|
<td>
|
|
Number of bytes in free, mapped pages in page heap. These bytes
|
|
can be used to fulfill allocation requests. They always count
|
|
towards virtual memory usage, and unless the underlying memory is
|
|
swapped out by the OS, they also count towards physical memory
|
|
usage.
|
|
</td>
|
|
</tr>
|
|
|
|
<tr valign=top>
|
|
<td><code>tcmalloc.pageheap_unmapped_bytes</code></td>
|
|
<td>
|
|
Number of bytes in free, unmapped pages in page heap. These are
|
|
bytes that have been released back to the OS, possibly by one of
|
|
the MallocExtension "Release" calls. They can be used to fulfill
|
|
allocation requests, but typically incur a page fault. They
|
|
always count towards virtual memory usage, and depending on the
|
|
OS, typically do not count towards physical memory usage.
|
|
</td>
|
|
</tr>
|
|
|
|
<tr valign=top>
|
|
<td><code>tcmalloc.slack_bytes</code></td>
|
|
<td>
|
|
Sum of pageheap_free_bytes and pageheap_unmapped_bytes. Provided
|
|
for backwards compatibility only. Do not use.
|
|
</td>
|
|
</tr>
|
|
|
|
<tr valign=top>
|
|
<td><code>tcmalloc.max_total_thread_cache_bytes</code></td>
|
|
<td>
|
|
A limit to how much memory TCMalloc dedicates for small objects.
|
|
Higher numbers trade off more memory use for -- in some situations
|
|
-- improved efficiency.
|
|
</td>
|
|
</tr>
|
|
|
|
<tr valign=top>
|
|
<td><code>tcmalloc.current_total_thread_cache_bytes</code></td>
|
|
<td>
|
|
A measure of some of the memory TCMalloc is using (for
|
|
small objects).
|
|
</td>
|
|
</tr>
|
|
|
|
</table>
|
|
|
|
<h2><A NAME="caveats">Caveats</A></h2>
|
|
|
|
<p>For some systems, TCMalloc may not work correctly with
|
|
applications that aren't linked against <code>libpthread.so</code> (or
|
|
the equivalent on your OS). It should work on Linux using glibc 2.3,
|
|
but other OS/libc combinations have not been tested.</p>
|
|
|
|
<p>TCMalloc may be somewhat more memory hungry than other mallocs,
|
|
(but tends not to have the huge blowups that can happen with other
|
|
mallocs). In particular, at startup TCMalloc allocates approximately
|
|
240KB of internal memory.</p>
|
|
|
|
<p>Don't try to load TCMalloc into a running binary (e.g., using JNI
|
|
in Java programs). The binary will have allocated some objects using
|
|
the system malloc, and may try to pass them to TCMalloc for
|
|
deallocation. TCMalloc will not be able to handle such objects.</p>
|
|
|
|
<hr>
|
|
|
|
<address>Sanjay Ghemawat, Paul Menage<br>
|
|
<!-- Created: Tue Dec 19 10:43:14 PST 2000 -->
|
|
<!-- hhmts start -->
|
|
Last modified: Sat Feb 24 13:11:38 PST 2007 (csilvers)
|
|
<!-- hhmts end -->
|
|
</address>
|
|
|
|
</body>
|
|
</html>
|