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+<!doctype html public "-//w3c//dtd html 4.01 transitional//en">
+<!-- $Id: $ -->
+<html>
+<head>
+<title>TCMalloc : Thread-Caching Malloc</title>
+<link rel="stylesheet" href="designstyle.css">
+<style type="text/css">
+  em {
+    color: red;
+    font-style: normal;
+  }
+</style>
+</head>
+<body>
+
+<h1>TCMalloc : Thread-Caching Malloc</h1>
+
+<address>Sanjay Ghemawat</address>
+
+<h2><A name=motivation>Motivation</A></h2>
+
+<p>TCMalloc is faster than the glibc 2.3 malloc (available as a
+separate library called ptmalloc2) and other mallocs that I have
+tested.  ptmalloc2 takes approximately 300 nanoseconds to execute a
+malloc/free pair on a 2.8 GHz P4 (for small objects).  The TCMalloc
+implementation takes approximately 50 nanoseconds for the same
+operation pair.  Speed is important for a malloc implementation
+because if malloc is not fast enough, application writers are inclined
+to write their own custom free lists on top of malloc.  This can lead
+to extra complexity, and more memory usage unless the application
+writer is very careful to appropriately size the free lists and
+scavenge idle objects out of the free list.</p>
+
+<p>TCMalloc also reduces lock contention for multi-threaded programs.
+For small objects, there is virtually zero contention.  For large
+objects, TCMalloc tries to use fine grained and efficient spinlocks.
+ptmalloc2 also reduces lock contention by using per-thread arenas but
+there is a big problem with ptmalloc2's use of per-thread arenas.  In
+ptmalloc2 memory can never move from one arena to another.  This can
+lead to huge amounts of wasted space.  For example, in one Google
+application, the first phase would allocate approximately 300MB of
+memory for its URL canonicalization data structures.  When the first
+phase finished, a second phase would be started in the same address
+space.  If this second phase was assigned a different arena than the
+one used by the first phase, this phase would not reuse any of the
+memory left after the first phase and would add another 300MB to the
+address space.  Similar memory blowup problems were also noticed in
+other applications.</p>
+
+<p>Another benefit of TCMalloc is space-efficient representation of
+small objects.  For example, N 8-byte objects can be allocated while
+using space approximately <code>8N * 1.01</code> bytes.  I.e., a
+one-percent space overhead.  ptmalloc2 uses a four-byte header for
+each object and (I think) rounds up the size to a multiple of 8 bytes
+and ends up using <code>16N</code> bytes.</p>
+
+
+<h2><A NAME="Usage">Usage</A></h2>
+
+<p>To use TCMalloc, just link TCMalloc into your application via the
+"-ltcmalloc" linker flag.</p>
+
+<p>You can use TCMalloc in applications you didn't compile yourself,
+by using LD_PRELOAD:</p>
+<pre>
+   $ LD_PRELOAD="/usr/lib/libtcmalloc.so" <binary>
+</pre>
+<p>LD_PRELOAD is tricky, and we don't necessarily recommend this mode
+of usage.</p>
+
+<p>TCMalloc includes a <A HREF="heap_checker.html">heap checker</A>
+and <A HREF="heapprofile.html">heap profiler</A> as well.</p>
+
+<p>If you'd rather link in a version of TCMalloc that does not include
+the heap profiler and checker (perhaps to reduce binary size for a
+static binary), you can link in <code>libtcmalloc_minimal</code>
+instead.</p>
+
+
+<h2><A NAME="Overview">Overview</A></h2>
+
+<p>TCMalloc assigns each thread a thread-local cache.  Small
+allocations are satisfied from the thread-local cache.  Objects are
+moved from central data structures into a thread-local cache as
+needed, and periodic garbage collections are used to migrate memory
+back from a thread-local cache into the central data structures.</p>
+<center><img src="overview.gif"></center>
+
+<p>TCMalloc treats objects with size &lt;= 256K ("small" objects)
+differently from larger objects.  Large objects are allocated directly
+from the central heap using a page-level allocator (a page is a 8K
+aligned region of memory).  I.e., a large object is always
+page-aligned and occupies an integral number of pages.</p>
+
+<p>A run of pages can be carved up into a sequence of small objects,
+each equally sized.  For example a run of one page (4K) can be carved
+up into 32 objects of size 128 bytes each.</p>
+
+
+<h2><A NAME="Small_Object_Allocation">Small Object Allocation</A></h2>
+
+<p>Each small object size maps to one of approximately 88 allocatable
+size-classes.  For example, all allocations in the range 961 to 1024
+bytes are rounded up to 1024.  The size-classes are spaced so that
+small sizes are separated by 8 bytes, larger sizes by 16 bytes, even
+larger sizes by 32 bytes, and so forth.  The maximal spacing is
+controlled so that not too much space is wasted when an allocation
+request falls just past the end of a size class and has to be rounded
+up to the next class.</p>
+
+<p>A thread cache contains a singly linked list of free objects per
+size-class.</p>
+<center><img src="threadheap.gif"></center>
+
+<p>When allocating a small object: (1) We map its size to the
+corresponding size-class.  (2) Look in the corresponding free list in
+the thread cache for the current thread.  (3) If the free list is not
+empty, we remove the first object from the list and return it.  When
+following this fast path, TCMalloc acquires no locks at all.  This
+helps speed-up allocation significantly because a lock/unlock pair
+takes approximately 100 nanoseconds on a 2.8 GHz Xeon.</p>
+
+<p>If the free list is empty: (1) We fetch a bunch of objects from a
+central free list for this size-class (the central free list is shared
+by all threads).  (2) Place them in the thread-local free list.  (3)
+Return one of the newly fetched objects to the applications.</p>
+
+<p>If the central free list is also empty: (1) We allocate a run of
+pages from the central page allocator.  (2) Split the run into a set
+of objects of this size-class.  (3) Place the new objects on the
+central free list.  (4) As before, move some of these objects to the
+thread-local free list.</p>
+
+<h3><A NAME="Sizing_Thread_Cache_Free_Lists">
+  Sizing Thread Cache Free Lists</A></h3>
+
+<p>It is important to size the thread cache free lists correctly.  If
+the free list is too small, we'll need to go to the central free list
+too often.  If the free list is too big, we'll waste memory as objects
+sit idle in the free list.</p>
+
+<p>Note that the thread caches are just as important for deallocation
+as they are for allocation.  Without a cache, each deallocation would
+require moving the memory to the central free list.  Also, some threads
+have asymmetric alloc/free behavior (e.g. producer and consumer threads),
+so sizing the free list correctly gets trickier.</p>
+
+<p>To size the free lists appropriately, we use a slow-start algorithm
+to determine the maximum length of each individual free list.  As the
+free list is used more frequently, its maximum length grows.  However,
+if a free list is used more for deallocation than allocation, its
+maximum length will grow only up to a point where the whole list can
+be efficiently moved to the central free list at once.</p>
+
+<p>The psuedo-code below illustrates this slow-start algorithm.  Note
+that <code>num_objects_to_move</code> is specific to each size class.
+By moving a list of objects with a well-known length, the central
+cache can efficiently pass these lists between thread caches.  If
+a thread cache wants fewer than <code>num_objects_to_move</code>,
+the operation on the central free list has linear time complexity.
+The downside of always using <code>num_objects_to_move</code> as
+the number of objects to transfer to and from the central cache is
+that it wastes memory in threads that don't need all of those objects.
+
+<pre>
+Start each freelist max_length at 1.
+
+Allocation
+  if freelist empty {
+    fetch min(max_length, num_objects_to_move) from central list;
+    if max_length < num_objects_to_move {  // slow-start
+      max_length++;
+    } else {
+      max_length += num_objects_to_move;
+    }
+  }
+
+Deallocation
+  if length > max_length {
+    // Don't try to release num_objects_to_move if we don't have that many.
+    release min(max_length, num_objects_to_move) objects to central list
+    if max_length < num_objects_to_move {
+      // Slow-start up to num_objects_to_move.
+      max_length++;
+    } else if max_length > num_objects_to_move {
+      // If we consistently go over max_length, shrink max_length.
+      overages++;
+      if overages > kMaxOverages {
+        max_length -= num_objects_to_move;
+        overages = 0;
+      }
+    }
+  }
+</pre>
+
+See also the section on <a href="#Garbage_Collection">Garbage Collection</a>
+to see how it affects the <code>max_length</code>.
+
+<h2><A NAME="Large_Object_Allocation">Large Object Allocation</A></h2>
+
+<p>A large object size (&gt; 256K) is rounded up to a page size (8K)
+and is handled by a central page heap.  The central page heap is again
+an array of free lists.  For <code>i &lt; 128</code>, the
+<code>k</code>th entry is a free list of runs that consist of
+<code>k</code> pages.  The <code>128</code>th entry is a free list of
+runs that have length <code>&gt;= 128</code> pages: </p>
+<center><img src="pageheap.gif"></center>
+
+<p>An allocation for <code>k</code> pages is satisfied by looking in
+the <code>k</code>th free list.  If that free list is empty, we look
+in the next free list, and so forth.  Eventually, we look in the last
+free list if necessary.  If that fails, we fetch memory from the
+system (using <code>sbrk</code>, <code>mmap</code>, or by mapping in
+portions of <code>/dev/mem</code>).</p>
+
+<p>If an allocation for <code>k</code> pages is satisfied by a run
+of pages of length &gt; <code>k</code>, the remainder of the
+run is re-inserted back into the appropriate free list in the
+page heap.</p>
+
+
+<h2><A NAME="Spans">Spans</A></h2>
+
+<p>The heap managed by TCMalloc consists of a set of pages.  A run of
+contiguous pages is represented by a <code>Span</code> object.  A span
+can either be <em>allocated</em>, or <em>free</em>.  If free, the span
+is one of the entries in a page heap linked-list.  If allocated, it is
+either a large object that has been handed off to the application, or
+a run of pages that have been split up into a sequence of small
+objects.  If split into small objects, the size-class of the objects
+is recorded in the span.</p>
+
+<p>A central array indexed by page number can be used to find the span to
+which a page belongs.  For example, span <em>a</em> below occupies 2
+pages, span <em>b</em> occupies 1 page, span <em>c</em> occupies 5
+pages and span <em>d</em> occupies 3 pages.</p>
+<center><img src="spanmap.gif"></center>
+
+<p>In a 32-bit address space, the central array is represented by a a
+2-level radix tree where the root contains 32 entries and each leaf
+contains 2^14 entries (a 32-bit address space has 2^19 8K pages, and
+the first level of tree divides the 2^19 pages by 2^5).  This leads to
+a starting memory usage of 64KB of space (2^14*4 bytes) for the
+central array, which seems acceptable.</p>
+
+<p>On 64-bit machines, we use a 3-level radix tree.</p>
+
+
+<h2><A NAME="Deallocation">Deallocation</A></h2>
+
+<p>When an object is deallocated, we compute its page number and look
+it up in the central array to find the corresponding span object.  The
+span tells us whether or not the object is small, and its size-class
+if it is small.  If the object is small, we insert it into the
+appropriate free list in the current thread's thread cache.  If the
+thread cache now exceeds a predetermined size (2MB by default), we run
+a garbage collector that moves unused objects from the thread cache
+into central free lists.</p>
+
+<p>If the object is large, the span tells us the range of pages covered
+by the object.  Suppose this range is <code>[p,q]</code>.  We also
+lookup the spans for pages <code>p-1</code> and <code>q+1</code>.  If
+either of these neighboring spans are free, we coalesce them with the
+<code>[p,q]</code> span.  The resulting span is inserted into the
+appropriate free list in the page heap.</p>
+
+
+<h2>Central Free Lists for Small Objects</h2>
+
+<p>As mentioned before, we keep a central free list for each
+size-class.  Each central free list is organized as a two-level data
+structure: a set of spans, and a linked list of free objects per
+span.</p>
+
+<p>An object is allocated from a central free list by removing the
+first entry from the linked list of some span.  (If all spans have
+empty linked lists, a suitably sized span is first allocated from the
+central page heap.)</p>
+
+<p>An object is returned to a central free list by adding it to the
+linked list of its containing span.  If the linked list length now
+equals the total number of small objects in the span, this span is now
+completely free and is returned to the page heap.</p>
+
+
+<h2><A NAME="Garbage_Collection">Garbage Collection of Thread Caches</A></h2>
+
+<p>Garbage collecting objects from a thread cache keeps the size of
+the cache under control and returns unused objects to the central free
+lists.  Some threads need large caches to perform well while others
+can get by with little or no cache at all.  When a thread cache goes
+over its <code>max_size</code>, garbage collection kicks in and then the
+thread competes with the other threads for a larger cache.</p>
+
+<p>Garbage collection is run only during a deallocation.  We walk over
+all free lists in the cache and move some number of objects from the
+free list to the corresponding central list.</p>
+
+<p>The number of objects to be moved from a free list is determined
+using a per-list low-water-mark <code>L</code>.  <code>L</code>
+records the minimum length of the list since the last garbage
+collection.  Note that we could have shortened the list by
+<code>L</code> objects at the last garbage collection without
+requiring any extra accesses to the central list.  We use this past
+history as a predictor of future accesses and move <code>L/2</code>
+objects from the thread cache free list to the corresponding central
+free list.  This algorithm has the nice property that if a thread
+stops using a particular size, all objects of that size will quickly
+move from the thread cache to the central free list where they can be
+used by other threads.</p>
+
+<p>If a thread consistently deallocates more objects of a certain size
+than it allocates, this <code>L/2</code> behavior will cause at least
+<code>L/2</code> objects to always sit in the free list.  To avoid
+wasting memory this way, we shrink the maximum length of the freelist
+to converge on <code>num_objects_to_move</code> (see also
+<a href="#Sizing_Thread_Cache_Free_Lists">Sizing Thread Cache Free Lists</a>).
+
+<pre>
+Garbage Collection
+  if (L != 0 && max_length > num_objects_to_move) {
+    max_length = max(max_length - num_objects_to_move, num_objects_to_move)
+  }
+</pre>
+
+<p>The fact that the thread cache went over its <code>max_size</code> is
+an indication that the thread would benefit from a larger cache.  Simply
+increasing <code>max_size</code> would use an inordinate amount of memory
+in programs that have lots of active threads.  Developers can bound the
+memory used with the flag --tcmalloc_max_total_thread_cache_bytes.</p>
+
+<p>Each thread cache starts with a small <code>max_size</code>
+(e.g. 64KB) so that idle threads won't pre-allocate memory they don't
+need.  Each time the cache runs a garbage collection, it will also try
+to grow its <code>max_size</code>.  If the sum of the thread cache
+sizes is less than --tcmalloc_max_total_thread_cache_bytes,
+<code>max_size</code> grows easily.  If not, thread cache 1 will try
+to steal from thread cache 2 (picked round-robin) by decreasing thread
+cache 2's <code>max_size</code>.  In this way, threads that are more
+active will steal memory from other threads more often than they are
+have memory stolen from themselves.  Mostly idle threads end up with
+small caches and active threads end up with big caches.  Note that
+this stealing can cause the sum of the thread cache sizes to be
+greater than --tcmalloc_max_total_thread_cache_bytes until thread
+cache 2 deallocates some memory to trigger a garbage collection.</p>
+
+<h2><A NAME="performance">Performance Notes</A></h2>
+
+<h3>PTMalloc2 unittest</h3>
+
+<p>The PTMalloc2 package (now part of glibc) contains a unittest
+program <code>t-test1.c</code>. This forks a number of threads and
+performs a series of allocations and deallocations in each thread; the
+threads do not communicate other than by synchronization in the memory
+allocator.</p>
+
+<p><code>t-test1</code> (included in
+<code>tests/tcmalloc/</code>, and compiled as
+<code>ptmalloc_unittest1</code>) was run with a varying numbers of
+threads (1-20) and maximum allocation sizes (64 bytes -
+32Kbytes). These tests were run on a 2.4GHz dual Xeon system with
+hyper-threading enabled, using Linux glibc-2.3.2 from RedHat 9, with
+one million operations per thread in each test. In each case, the test
+was run once normally, and once with
+<code>LD_PRELOAD=libtcmalloc.so</code>.
+
+<p>The graphs below show the performance of TCMalloc vs PTMalloc2 for
+several different metrics. Firstly, total operations (millions) per
+elapsed second vs max allocation size, for varying numbers of
+threads. The raw data used to generate these graphs (the output of the
+<code>time</code> utility) is available in
+<code>t-test1.times.txt</code>.</p>
+
+<table>
+<tr>
+  <td><img src="tcmalloc-opspersec.vs.size.1.threads.png"></td>
+  <td><img src="tcmalloc-opspersec.vs.size.2.threads.png"></td>
+  <td><img src="tcmalloc-opspersec.vs.size.3.threads.png"></td>
+</tr>
+<tr>
+  <td><img src="tcmalloc-opspersec.vs.size.4.threads.png"></td>
+  <td><img src="tcmalloc-opspersec.vs.size.5.threads.png"></td>
+  <td><img src="tcmalloc-opspersec.vs.size.8.threads.png"></td>
+</tr>
+<tr>
+  <td><img src="tcmalloc-opspersec.vs.size.12.threads.png"></td>
+  <td><img src="tcmalloc-opspersec.vs.size.16.threads.png"></td>
+  <td><img src="tcmalloc-opspersec.vs.size.20.threads.png"></td>
+</tr>
+</table>
+
+
+<ul> 
+  <li> TCMalloc is much more consistently scalable than PTMalloc2 - for
+       all thread counts &gt;1 it achieves ~7-9 million ops/sec for small
+       allocations, falling to ~2 million ops/sec for larger
+       allocations. The single-thread case is an obvious outlier,
+       since it is only able to keep a single processor busy and hence
+       can achieve fewer ops/sec. PTMalloc2 has a much higher variance
+       on operations/sec - peaking somewhere around 4 million ops/sec
+       for small allocations and falling to &lt;1 million ops/sec for
+       larger allocations.
+
+  <li> TCMalloc is faster than PTMalloc2 in the vast majority of
+       cases, and particularly for small allocations. Contention
+       between threads is less of a problem in TCMalloc.
+
+  <li> TCMalloc's performance drops off as the allocation size
+       increases. This is because the per-thread cache is
+       garbage-collected when it hits a threshold (defaulting to
+       2MB). With larger allocation sizes, fewer objects can be stored
+       in the cache before it is garbage-collected.
+
+  <li> There is a noticeable drop in TCMalloc's performance at ~32K
+       maximum allocation size; at larger sizes performance drops less
+       quickly. This is due to the 32K maximum size of objects in the
+       per-thread caches; for objects larger than this TCMalloc
+       allocates from the central page heap.
+</ul>
+
+<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 &lt;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>