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diff --git a/trunk/doc/tcmalloc.html b/trunk/doc/tcmalloc.html new file mode 100644 index 0000000..4f60f92 --- /dev/null +++ b/trunk/doc/tcmalloc.html @@ -0,0 +1,732 @@ +<!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 <= 32K ("small" objects) +differently from larger objects. Large objects are allocated directly +from the central heap using a page-level allocator (a page is a 4K +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 60 allocatable +size-classes. For example, all allocations in the range 833 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 (> 32K) is rounded up to a page size (4K) +and is handled by a central page heap. The central page heap is again +an array of free lists. For <code>i < 256</code>, the +<code>k</code>th entry is a free list of runs that consist of +<code>k</code> pages. The <code>256</code>th entry is a free list of +runs that have length <code>>= 256</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 > <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 2^15 entries (a 32-bit address spave has 2^20 4K pages, and +the first level of tree divides the 2^20 pages by 2^5). This leads to +a starting memory usage of 128KB of space (2^15*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 >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 <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 <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: 524288</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. + </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=<i>x</i></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> + + +</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.slack_bytes</code></td> + <td> + A measure of memory fragmentation (how much memory is reserved by + TCMalloc but unlikely to ever be able to serve an allocation + request). + </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> |