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Reference Counting - Part III | ||||||||||||||
Thread 1 | Thread 2 |
>> enter s1's AboutToModify() evaluate "data_->refs > 1" (true, because data_->refs is 2) | |
******** context switch ******** | |
>> enter s2's AboutToModify() (runs all the way to completion, including that it decrements data_->refs to the value 1) << exit s2's AboutToModify() | |
******** context switch ******** | |
evaluate "data_->refs != Unshareable" (true, because data_->refs is now 1) enters AboutToModify's "I'm shared and need to unshare" block, which clones the representation, decrements data_->refs to the value 0, and gives up the last pointer to the StringBuf... poof, we have a memory leak because the StringBuf that had been shared by s1 and s2 can now never be deleted | |
Having covered that, we're ready to see how to solve these safety problems.
2. Demonstrate how to make Optimized::String (from GotW #44) thread-safe:
a) assuming that there atomic operations to get, set, and compare integer values; and
b) assuming that there aren't.
I'm going to answer b) first because it's more general. What's needed here is a lock-management device like a critical section or a mutex. The code is equivalent in either case, so below I'll use a critical section, which is usually a more efficient synchronization device than a general-purpose mutex. The key to what we're about to do is quite simple: It turns out that if we do things right we only need to lock access to the reference count itself.
Before doing anything else, we need to add a CriticalSection member object into Optimized::StringBuf. Let's call the member cs:
namespace Optimized {
struct StringBuf {
StringBuf(); // start off empty
~StringBuf(); // delete the buffer
StringBuf( const StringBuf& other, size_t n = 0 );
// initialize to copy of other,
// and ensure len >= n
void Reserve( size_t n ); // ensure len >= n
char* buf; // allocated buffer
size_t len; // length of buffer
size_t used; // # chars actually used
unsigned refs; // reference count
CriticalSection cs; // serialize work on this object
};The only function that necessarily operates on two StringBuf objects at once is the copy constructor. String only calls StringBuf's copy constructor from two places (from String's own copy constructor, and from AboutToModify()). Note that String only needs to serialize access to the reference count, because by definition no String will do any work on a StringBuf that's shared (if it is shared, it will be read in order to take a copy, but we don't need to worry about anyone else trying to change or Reserve() or otherwise alter/move the buffer).
The default constructor needs no locks:
String::String() : data_(new StringBuf) { }The destructor need only lock its interrogation and update of the refs count:
String::~String() {
bool bDelete = false;
data_->cs.Lock(); //---------------------------
if( data_->refs == Unshareable || --data_->refs < 1 ) {
bDelete = true;
}
data_->cs.Unlock(); //-------------------------
if( bDelete ) {
delete data_;
}
}For the String copy constructor, note that we can assume that the other String's data buffer won't be modified or moved during this operation, since it's the responsibility of the caller to serialize access to visible objects. We must still, however, serialize access to the reference count itself, as we did above:
String::String( const String& other )
{
bool bSharedIt = false;
other.data_->cs.Lock(); //---------------------
if( other.data_->refs != Unshareable ) {
bSharedIt = true;
data_ = other.data_;
++data_->refs;
}
other.data_->cs.Unlock(); //-------------------
if( !bSharedIt ) {
data_ = new StringBuf( *other.data_ );
}
}So making the String copy constructor safe wasn't very hard at all. This brings us to AboutToModify(), which turns out to be very similar, but notice that this sample code actually acquires the lock during the entire deep copy operation... really, the lock is strictly only needed when looking at the refs value, and again when updating the refs value at the end, but I decided to lock the whole operation instead of getting slightly better concurrency by releasing the lock during the deep copy and then reacquiring it just to update refs:
void String::AboutToModify(
size_t n,
bool bMarkUnshareable /* = false */
) {
data_->cs.Lock(); //---------------------------
if( data_->refs > 1 && data_->refs != Unshareable ) {
StringBuf* newdata = new StringBuf( *data_, n );
--data_->refs; // now all the real work is
data_->cs.Unlock(); //-----------------------
data_ = newdata; // done, so take ownership
}
else {
data_->cs.Unlock(); //-----------------------
data_->Reserve( n );
}
data_->refs = bMarkUnshareable ? Unshareable : 1;
}None of the other functions need to be changed. Append() and operator[]() don't need locks because once AboutToModify() completes we're guaranteed that we're not using a shared representation. Length() doesn't need a lock because by definition we're okay if our StringBuf is not shared (there's no one else to change the used count on us), and we're okay if it is shared (the other thread would take its own copy before doing any work and hence still wouldn't modify our used count on us):
void String::Append( char c ) {
AboutToModify( data_->used+1 );
data_->buf[data_->used++] = c;
}
size_t String::Length() const {
return data_->used;
}
char& String::operator[]( size_t n ) {
AboutToModify( data_->len, true );
return *(data_->buf+n);
}
}Again, note the interesting thing in all of this: The only locking we needed to do involved the refs count itself.
With that observation and the above general-purpose solution under our belts, let's look back to the a) part of the question:
a) assuming that there atomic operations to get, set, and compare integer values; and
Some operating systems provide these kinds of functions.
NOTE: These functions are usually much more efficient than general-purpose synchronization primitives like critical sections and mutexes. It is, however, a fallacy so say that we can use atomic integer operations "instead of locks" because locking is still required -- the locking is just generally less expensive than other alternatives, but it's not free by a long shot.
Here is a thread-safe implementation of String that assumes we have three functions: an IntAtomicGet, and IntAtomicDecrement and IntAtomicIncrement that safely return the new value. We'll do essentially the same thing we did above, but use only atomic integer operations to serialize access to the refs count:
namespace Optimized {
String::String() : data_(new StringBuf) { }
String::~String() {
if( IntAtomicGet( data_->refs ) == Unshareable ||
IntAtomicDecrement( data_->refs ) < 1 ) {
delete data_;
}
}
String::String( const String& other )
{
if( IntAtomicGet( other.data_->refs ) != Unshareable ) {
data_ = other.data_;
IntAtomicIncrement( data_->refs );
}
else {
data_ = new StringBuf( *other.data_ );
}
}
void String::AboutToModify(
size_t n,
bool bMarkUnshareable /* = false */
) {
int refs = IntAtomicGet( data_->refs );
if( refs > 1 && refs != Unshareable ) {
StringBuf* newdata = new StringBuf( *data_, n );
if( IntAtomicDecrement( data_->refs ) < 1 ) {
delete newdata; // just in case two threads
} // are trying this at once
else { // now all the real work is
data_ = newdata; // done, so take ownership
}
}
else {
data_->Reserve( n );
}
data_->refs = bMarkUnshareable ? Unshareable : 1;
}
void String::Append( char c ) {
AboutToModify( data_->used+1 );
data_->buf[data_->used++] = c;
}
size_t String::Length() const {
return data_->used;
}
char& String::operator[]( size_t n ) {
AboutToModify( data_->len, true );
return *(data_->buf+n);
}
}3. What are the effects on performance? Discuss.
Without atomic integer operations, copy-on-write typically incurs a significant performance penalty. Even with atomic integer operations, COW can make common String operations take nearly 50% longer -- even in single-threaded programs.
In general, copy-on-write is often a bad idea in multithread-ready code. In short, the reason is that the calling code can no longer know whether two distinct String objects actually share the same representation under the covers, and so String must incur overhead to do enough serialization that calling code can take its normal share of responsibility for thread safety. Depending on the availability of more-efficient options like atomic integer operations, the impact on performance ranges from "moderate" to "profound."
In this test environment I tested six main flavours of string implementations:
Name Description
--------------- ---------------------------------------
Plain Non-use-counted string; all others are
modeled on this (a refined version of
the GotW #43 answer)
COW_Unsafe Plain + COW, not thread-safe (a refined
version of the GotW #44 answer)
COW_AtomicInt Plain + COW + thread-safe (a refined
version of this GotW #45 1(a) answer
above)
COW_AtomicInt2 COW_AtomicInt + StringBuf in same
buffer as the data (another refined
version of this GotW #45 #1(a) above)
COW_CritSec Plain + COW + thread-safe (Win32
critical sections) (a refined version
of this GotW #45 #1(b) answer above)
COW_Mutex Plain + COW + thread-safe (Win32
mutexes) (COW_CritSec with mutexes
instead of critical sections)I also threw in a seventh flavour to measure the result of optimizing memory allocation instead of optimizing copying:
Plain_FastAlloc Plain + an optimized memory allocator
I focused on comparing Plain with COW_AtomicInt. COW_AtomicInt was generally the most efficient thread-safe COW implementation. The results were as follows:
1. For all mutating and possibly-mutating operations, COW_AtomicInt was always worse than Plain. This is natural and expected.
2. COW should shine when there are many unmodified copies, but for an average string length of 50:
a) When 33% of all copies were never modified, and the rest were modified only once each, COW_AtomicInt was still slower than Plain.
b) When 50% of all copies were never modified, and the rest were modified only thrice each, COW_AtomicInt was still slower than Plain.
This result may be more surprising to many -- particularly that COW_AtomicInt is slower in cases where there are more copy operations than mutating operations in the entire system!
Note that, in both cases, traditional thread-unsafe COW did perform better than Plain. This shows that indeed COW can be an optimization for purely single- threaded environments, but it is less often appropriate for thread-safe code.
3. It is a myth that COW's principal advantage lies in avoiding memory allocations. Especially for longer strings, COW's principal advantage is that it avoids copying the characters in the string.
4. Optimized allocation, not COW, was a consistent true speed optimization in all cases (but note that it does trade off space). Here is perhaps the most important conclusion from the Detailed Measurements section:
"* Most of COW's primary advantage for small strings could be gained without COW by using a more efficient allocator. (Of course, you could also do both -- use COW and an efficient allocator.)"
Q: Why measure something as inefficient as COW_CritSec? A: Because at least one popular commercial basic_string implementation used this method as recently as a year ago (and perhaps still does, I haven't seen their code lately), despite the fact that COW_CritSec is nearly always a pessimization. Be sure to check whether your library vendor is doing this, because if the library is built for possible multithreaded use then you will bear the performance cost all the time -- even if your program is single-threaded.
Q: What's COW_AtomicInt2? A: It's the same as COW_AtomicInt except that, instead of allocating a StringBuf and then separately allocating the data buffer, the StringBuf and data are in the same allocated block of memory. Note that all other COW_* variants use a fast allocator for the StringBuf object (so that there's no unfair "double allocation" cost), and the purpose of COW_AtomicInt2 is mainly to demonstrate that I have actually addressed that concern... COW_AtomicInt2 is actually slightly slower than COW_AtomicInt for most operations (because of the extra logic).
I also tested the relative performance of various integer operations (incrementing int, incrementing volatile int, and incrementing int using the Win32 atomic integer operations), to ensure that COW_AtomicInt results were not unfairly skewed by poor implementations or function call overhead.
To assess COW, I performed measurements of three kinds of functions:
- copying (where COW shines, its raison d'etre)
- mutating operations that could trigger reallocation (represented by Append, which gradually lengthens; this is to make sure any conclusions drawn can take into account periodic reallocation overhead due to normal string use)
- possibly-mutating operations that do not change length enough to trigger reallocation, or that do not actually mutate the string at all (represented by operator[])
It turns out that the last two both incur a constant (and similar, within ~20%) cost per operation, and can be roughly considered together. Assuming for simplicity that mutating-and-extending operations like Append (235ms overhead) and possibly-mutating operations like operator[] (280ms overhead) will be about equally frequent, the COW_AtomicInt overhead for mutating and possibly-mutating operations is about 260ms per 1,000,000 operations in this implementation.
Finally, for each of 2(a) and 2(b), I first used the "Raw Measurements" section below to hand-calculate a rough prediction of expected relative performance, then ran the test to check actual performance.
SUMMARY FOR CASE 2(a):
PREDICTION
COW_AtomicInt Cost Plain Cost
------------------------- ----------------------
1M shallow copies 1M deep copies
and dtors 400 and dtors 1600
667K mutations ??? ???
667K deep copies 1060
extra overhead on
667K deep copies ???
extra overhead on
667K mutations 175
----- -----
1635+ 1600+
TEST
(program that makes copies in a tight loop, and
modifies 33% of them with a single Append and
another 33% of them with a single op[])
Running 1000000 iterations with strings of length 50:
Plain_FastAlloc 642ms copies: 1000000 allocs: 1000007
Plain 1726ms copies: 1000000 allocs: 1000007
COW_Unsafe 1629ms copies: 1000000 allocs: 666682
COW_AtomicInt 1949ms copies: 1000000 allocs: 666682
COW_AtomicInt2 1925ms copies: 1000000 allocs: 666683
COW_CritSec 10660ms copies: 1000000 allocs: 666682
COW_Mutex 33298ms copies: 1000000 allocs: 666682
SUMMARY FOR CASE 2(b):
PREDICTION
COW_AtomicInt Cost Plain Cost
------------------------- ----------------------
1M shallow copies 1M deep copies
and dtors 400 and dtors 1600
1.5M mutations ??? ???
500K deep copies 800
extra overhead on
500K deep copies ???
extra overhead on
1.5M mutations 390
----- -----
1590+ 1600+
TEST
(program that makes copies in a tight loop, and
modifies 25% of them with three Appends and
another 25% of them with three operator[]s)
Running 1000000 iterations with strings of length 50:
Plain_FastAlloc 683ms copies: 1000000 allocs: 1000007
Plain 1735ms copies: 1000000 allocs: 1000007
COW_Unsafe 1407ms copies: 1000000 allocs: 500007
COW_AtomicInt 1838ms copies: 1000000 allocs: 500007
COW_AtomicInt2 1700ms copies: 1000000 allocs: 500008
COW_CritSec 8507ms copies: 1000000 allocs: 500007
COW_Mutex 31911ms copies: 1000000 allocs: 500007TESTING CONST COPYING + DESTRUCTION: The target case of COW
Notes:
- COW_AtomicInt always took over twice as long to create and
destroy a const copy as did plain thread-unsafe COW.
- For every copy of a string that was later modified,
COW_AtomicInt added constant unrecoverable overhead
(400ms per 1,000,000) not counting the overhead on other
operations.
* Most of COW's primary advantage for small strings could be
gained without COW by using a more efficient allocator.
(Of course, you could also do both -- use COW and an
efficient allocator.)
* COW's primary advantage for large strings lay, not in
avoiding the allocations, but in avoiding the char copying.
Running 1000000 iterations with strings of length 10:
Plain_FastAlloc 495ms copies: 1000000 allocs: 1000003
Plain 1368ms copies: 1000000 allocs: 1000003
COW_Unsafe 160ms copies: 1000000 allocs: 3
COW_AtomicInt 393ms copies: 1000000 allocs: 3
COW_AtomicInt2 433ms copies: 1000000 allocs: 4
COW_CritSec 428ms copies: 1000000 allocs: 3
COW_Mutex 14369ms copies: 1000000 allocs: 3
Running 1000000 iterations with strings of length 50:
Plain_FastAlloc 558ms copies: 1000000 allocs: 1000007
Plain 1598ms copies: 1000000 allocs: 1000007
COW_Unsafe 165ms copies: 1000000 allocs: 7
COW_AtomicInt 394ms copies: 1000000 allocs: 7
COW_AtomicInt2 412ms copies: 1000000 allocs: 8
COW_CritSec 433ms copies: 1000000 allocs: 7
COW_Mutex 14130ms copies: 1000000 allocs: 7
Running 1000000 iterations with strings of length 100:
Plain_FastAlloc 708ms copies: 1000000 allocs: 1000008
Plain 1884ms copies: 1000000 allocs: 1000008
COW_Unsafe 171ms copies: 1000000 allocs: 8
COW_AtomicInt 391ms copies: 1000000 allocs: 8
COW_AtomicInt2 412ms copies: 1000000 allocs: 9
COW_CritSec 439ms copies: 1000000 allocs: 8
COW_Mutex 14129ms copies: 1000000 allocs: 8
Running 1000000 iterations with strings of length 250:
Plain_FastAlloc 1164ms copies: 1000000 allocs: 1000011
Plain 5721ms copies: 1000000 allocs: 1000011 [*]
COW_Unsafe 176ms copies: 1000000 allocs: 11
COW_AtomicInt 393ms copies: 1000000 allocs: 11
COW_AtomicInt2 419ms copies: 1000000 allocs: 12
COW_CritSec 443ms copies: 1000000 allocs: 11
COW_Mutex 14118ms copies: 1000000 allocs: 11
Running 1000000 iterations with strings of length 1000:
Plain_FastAlloc 2865ms copies: 1000000 allocs: 1000014
Plain 4945ms copies: 1000000 allocs: 1000014
COW_Unsafe 173ms copies: 1000000 allocs: 14
COW_AtomicInt 390ms copies: 1000000 allocs: 14
COW_AtomicInt2 415ms copies: 1000000 allocs: 15
COW_CritSec 439ms copies: 1000000 allocs: 14
COW_Mutex 14059ms copies: 1000000 allocs: 14
Running 1000000 iterations with strings of length 2500:
Plain_FastAlloc 6244ms copies: 1000000 allocs: 1000016
Plain 8343ms copies: 1000000 allocs: 1000016
COW_Unsafe 174ms copies: 1000000 allocs: 16
COW_AtomicInt 397ms copies: 1000000 allocs: 16
COW_AtomicInt2 413ms copies: 1000000 allocs: 17
COW_CritSec 446ms copies: 1000000 allocs: 16
COW_Mutex 14070ms copies: 1000000 allocs: 16
TESTING APPEND: An always-mutating periodically-reallocating operation
Notes:
- Plain always outperformed COW.
- The overhead of COW_AtomicInt compared to Plain did not
vary greatly with string lengths: It was fairly constant
at about 235ms per 1,000,000 operations.
- The overhead of COW_AtomicInt compared to COW_Unsafe did not
vary greatly with string lengths: It was fairly constant
at about 110ms per 1,000,000 operations.
* The overall ever-better performance for longer strings was
due to the allocation strategy (see GotW #43), not COW vs.
Plain issues.
Running 1000000 iterations with strings of length 10:
Plain_FastAlloc 302ms copies: 0 allocs: 272730
Plain 565ms copies: 0 allocs: 272730
COW_Unsafe 683ms copies: 0 allocs: 272730
COW_AtomicInt 804ms copies: 0 allocs: 272730
COW_AtomicInt2 844ms copies: 0 allocs: 363640
COW_CritSec 825ms copies: 0 allocs: 272730
COW_Mutex 8419ms copies: 0 allocs: 272730
Running 1000000 iterations with strings of length 50:
Plain_FastAlloc 218ms copies: 0 allocs: 137262
Plain 354ms copies: 0 allocs: 137262
COW_Unsafe 474ms copies: 0 allocs: 137262
COW_AtomicInt 588ms copies: 0 allocs: 137262
COW_AtomicInt2 536ms copies: 0 allocs: 156871
COW_CritSec 607ms copies: 0 allocs: 137262
COW_Mutex 7614ms copies: 0 allocs: 137262
Running 1000000 iterations with strings of length 100:
Plain_FastAlloc 182ms copies: 0 allocs: 79216
Plain 257ms copies: 0 allocs: 79216
COW_Unsafe 382ms copies: 0 allocs: 79216
COW_AtomicInt 492ms copies: 0 allocs: 79216
COW_AtomicInt2 420ms copies: 0 allocs: 89118
COW_CritSec 535ms copies: 0 allocs: 79216
COW_Mutex 7810ms copies: 0 allocs: 79216
Running 1000000 iterations with strings of length 250:
Plain_FastAlloc 152ms copies: 0 allocs: 43839
Plain 210ms copies: 0 allocs: 43839
COW_Unsafe 331ms copies: 0 allocs: 43839
COW_AtomicInt 438ms copies: 0 allocs: 43839
COW_AtomicInt2 366ms copies: 0 allocs: 47825
COW_CritSec 485ms copies: 0 allocs: 43839
COW_Mutex 7358ms copies: 0 allocs: 43839
Running 1000000 iterations with strings of length 1000:
Plain_FastAlloc 123ms copies: 0 allocs: 14000
Plain 149ms copies: 0 allocs: 14000
COW_Unsafe 275ms copies: 0 allocs: 14000
COW_AtomicInt 384ms copies: 0 allocs: 14000
COW_AtomicInt2 299ms copies: 0 allocs: 15000
COW_CritSec 421ms copies: 0 allocs: 14000
COW_Mutex 7265ms copies: 0 allocs: 14000
Running 1000000 iterations with strings of length 2500:
Plain_FastAlloc 122ms copies: 0 allocs: 6416
Plain 148ms copies: 0 allocs: 6416
COW_Unsafe 279ms copies: 0 allocs: 6416
COW_AtomicInt 380ms copies: 0 allocs: 6416
COW_AtomicInt2 304ms copies: 0 allocs: 6817
COW_CritSec 405ms copies: 0 allocs: 6416
COW_Mutex 7281ms copies: 0 allocs: 6416
TESTING OPERATOR[]: A possibly-mutating operation, never does mutate
Notes:
- Plain always vastly outperformed COW.
- Results were independent of string lengths.
- The overhead of COW_AtomicInt compared to Plain was
constant at about 280ms per 1,000,000 operations.
- COW_AtomicInt2 fared better in this test case, but
COW_AtomicInt did better overall and so I am focusing
on comparing that with Plain.
[10x iterations] Running 10000000 iterations with strings of length 10:
Plain_FastAlloc 3ms copies: 0 allocs: 3 [*]
Plain 2ms copies: 0 allocs: 3 [*]
COW_Unsafe 1698ms copies: 0 allocs: 3
COW_AtomicInt 2833ms copies: 0 allocs: 3
COW_AtomicInt2 2112ms copies: 0 allocs: 4
COW_CritSec 3587ms copies: 0 allocs: 3
COW_Mutex 71787ms copies: 0 allocs: 3
[*] within measurement error margin, both varied from 0ms to 9ms
TESTING VARIOUS INTEGER INCREMENT/DECREMENT OPERATIONS
Test Summary:
- "plain" performs the operations on normal
nonvolatile ints
- "volatile" is the only case to use volatile ints
- "atomic" uses the Win32 InterlockedXxx operations
- "atomic_ass" uses inline x86 assembler locked
integer operations
Notes:
- ++atomic took only three times as long as either
++volatile and unoptimized ++plain
- ++atomic does not incur function call overhead
[100x iterations] Running 100000000 iterations for integer operations:
++plain 2404ms, counter=100000000
--plain 2399ms, counter=0
++volatile 2400ms, counter=100000000
--volatile 2405ms, counter=0
++atomic 7480ms, counter=100000000
--atomic 9340ms, counter=0
++atomic_ass 8881ms, counter=100000000
--atomic_ass 10964ms, counter=0Here are a few extra notes on the relative timings of various flavours of x86 assembler implementations of IntAtomicIncrement (these timings were taken under the same conditions as above and can be compared directly):
Instructions Timing
--------------------------- --------
__asm mov eax, 1
__asm lock xadd i, eax
__asm mov result, eax ~11000ms
__asm mov eax, 1
__asm lock xadd i, eax ~10400ms
__asm lock inc i ~8900ms
(this is the one actually used above)Note that the non-atomic versions are much better, and map directly onto the "plain" timings:
__asm inc i ~2400ms
Conclusion: So there is indeed overhead introduced by the x86 LOCK instruction, even on a single-CPU machine. This is natural and to be expected, but I point it out because some people said there was no difference.
I am very impressed that Win32's InterlockedIncrement is actually faster at 765ms than my hand-coded assembler at 900ms, even though my hand-coded version actually does less work (only a single instruction!) because it doesn't return the new value. Of course, I'm no x86 assembler expert; the explanation is certainly that the OS's wrapper is using a different opcode than my hand-coded version.
Finally, of course, note that the Win32 atomic int functions clearly are not incurring function-call overhead. Never assume -- measure.
A few important points about this test harness:
1. CAVEAT LECTOR: Take this for what it is: A first cut at a test harness. Comments and corrections are welcome. I'm showing raw performance numbers here; I haven't inspected the compiled code, and I've made no attempt to determine the impact of cache hits/misses and other secondary effects. (Even so, this GotW took much more effort than usual to produce, and I guarantee that the next few issues will feature simpler topics!)
2. TANSTAAFL ("there ain't no such thing as a free lunch" -R.A.Heinlein). Even with atomic integer operations, it is incorrect to say "there's no locking required" because the atomic integer operations clearly do perform serialization, and do incur significant overhead.
3. The test harness itself is SINGLE-threaded. A thread-safe COW implementation incurs overhead even in programs that are not themselves multithreaded. At best, COW could be a true optimization only when the COW code does not need to be made thread-safe at all (even then, see Rob Murray's "C++ Strategies and Tactics" book, pages 70-72, for more empirical tests that show COW is only beneficial in certain situations). If thread safety is required, COW imposes a significant performance penalty on all users, even users running only single-threaded code.
Copyright © 2009 Herb Sutter |