Strange Long ParNew GC Pauses (Sample Code Included)

James Lent jlent at
Fri May 15 13:10:20 UTC 2015

If you do compare implementations that do not eliminate the issue you may want to do do speed comparisons with fairly large heaps.  The problem seems to be sensitive to the size of the heap.

Here is some data for

$ /usr/lib/jvm/java-8-oracle/bin/java -verbose:gc -XX:+PrintGCTimeStamps -XX:+PrintGCDetails -XX:+UseParNewGC -XX:+UseConcMarkSweepGC -Xmx4G -Xms4G LongParNewPause $((511*1024*1024)) 100 10
0.337: [GC (Allocation Failure) 0.337: [ParNew: 272640K->27159K(306688K), 0.0305582 secs] 795904K->550423K(4160256K), 0.0306375 secs] [Times: user=0.07 sys=0.00, real=0.03 secs]
0.426: [GC (Allocation Failure) 0.426: [ParNew: 299799K->34048K(306688K), 6.5059384 secs] 823063K->583430K(4160256K), 6.5059888 secs] [Times: user=18.92 sys=0.11, real=6.51 secs]
6.986: [GC (Allocation Failure) 6.986: [ParNew: 306688K->34048K(306688K), 56.9484514 secs] 856070K->612129K(4160256K), 56.9484954 secs] [Times: user=171.23 sys=0.15, real=56.95 secs]
63.988: [GC (Allocation Failure) 63.988: [ParNew: 306688K->34048K(306688K), 0.0565390 secs] 884769K->637571K(4160256K), 0.0565880 secs] [Times: user=0.13 sys=0.01, real=0.05 secs]

$ /usr/lib/jvm/java-8-oracle/bin/java -verbose:gc -XX:+PrintGCTimeStamps -XX:+PrintGCDetails -XX:+UseParNewGC -XX:+UseConcMarkSweepGC -Xmx6G -Xms6G LongParNewPause $((511*1024*1024)) 100 10
0.334: [GC (Allocation Failure) 0.334: [ParNew: 272640K->27168K(306688K), 0.0351895 secs] 795904K->550432K(6257408K), 0.0352570 secs] [Times: user=0.09 sys=0.01, real=0.04 secs]
0.425: [GC (Allocation Failure) 0.425: [ParNew: 299808K->34048K(306688K), 10.9954310 secs] 823072K->583430K(6257408K), 10.9955119 secs] [Times: user=31.86 sys=0.26, real=11.00 secs]
11.473: [GC (Allocation Failure) 11.473: [ParNew: 306688K->34048K(306688K), 88.3759289 secs] 856070K->613626K(6257408K), 88.3760008 secs] [Times: user=264.53 sys=0.29, real=88.38 secs]
99.902: [GC (Allocation Failure) 99.902: [ParNew: 306688K->34048K(306688K), 0.0389420 secs] 886266K->639328K(6257408K), 0.0389901 secs] [Times: user=0.11 sys=0.00, real=0.04 secs]

j$ /usr/lib/jvm/java-8-oracle/bin/java -verbose:gc -XX:+PrintGCTimeStamps -XX:+PrintGCDetails -XX:+UseParNewGC -XX:+UseConcMarkSweepGC -Xmx8G -Xms8G LongParNewPause $((511*1024*1024)) 100 10
0.340: [GC (Allocation Failure) 0.340: [ParNew: 272640K->27167K(306688K), 0.0494393 secs] 795904K->550431K(8354560K), 0.0494989 secs] [Times: user=0.13 sys=0.01, real=0.05 secs]
0.446: [GC (Allocation Failure) 0.446: [ParNew: 299807K->34048K(306688K), 134.5836909 secs] 823071K->583430K(8354560K), 134.5837641 secs] [Times: user=401.86 sys=1.08, real=134.60 secs]
135.083: [GC (Allocation Failure) 135.083: [ParNew: 306688K->34048K(306688K), 131.0308655 secs] 856070K->611303K(8354560K), 131.0309166 secs] [Times: user=388.81 sys=0.40, real=131.04 secs]
266.168: [GC (Allocation Failure) 266.168: [ParNew: 306688K->34048K(306688K), 0.0733667 secs] 883943K->639714K(8354560K), 0.0734196 secs] [Times: user=0.16 sys=0.00, real=0.08 secs]

For the steady state ParNew pauses (after about 10 iterations) on my machine are about:

Heap    ParNew Pause
(G)             (sec)
2G             0.23
4G             0.62
6G             1.00
8G             1.38


Thanks for the information.

There's a bug in the current code which tries to patch up the BOT after
a block is split.  I don't understand yet what is wrong but a simple
workaround (which is known to be slower than necessary) avoids the
much of the long pauses.  After this has been fixed, we should compare
the performances of our two implementations.


On 5/14/2015 2:52 PM, Jungwoo Ha wrote:
We have a faster implementation for card table scan, and on our implementation ~20s pause goes down to 1~2s with above-mentioned experiments. It doesn't solve the problem but it alleviates it (and actually shows that card table scan is faster).
If someone can sponsor this, I will create a patch for the review.

On Wed, May 13, 2015 at 6:36 PM, Srinivas Ramakrishna <ysr1729 at<mailto:ysr1729 at>> wrote:
Hi Jon --

thanks, just a comment inline below....

On Wed, May 13, 2015 at 4:06 PM, Jon Masamitsu <jon.masamitsu at<mailto:jon.masamitsu at>> wrote:

On 5/13/2015 11:40 AM, Srinivas Ramakrishna wrote:
Hi Jon --

My expectation is that for any large block spanning multiple cards, if you walk the BOT entries for that block from lower addresses to higher addresses, the BOT entries should be monotone increasing (albeit not strictly monotone) until the last card for that block (but one). In the example you gave below, is D > C > N_words, with the BOT entries in some interior window of the same block/object going (low to high addresses in the window) like " .... DDDDCCCCDDDD...." ? In other words, there are lower-valued entries C within a range of higher-valued entries D, with both C and D denoting logarithmic entries for the block in question?

Yes, that's what I'm seeing.

If you look in the BOT methods, there was a parameter "reducing" passed to some of the mark_block() methods which was supposed to do some kind of assertion checking towards maintenance of this monotonicity, but looking at it now, that may not be sufficient and the assert could be strengthened at the "end" of the range being marked. More worryingly, I believe I had turned off even that assert before I left (ca 6uXX?) because it was failing at that time, but the corresponding bug hadn't been fixed, and seems as though it still isn't. This might possibly  have some bearing on the non-monotonicity in the entries you see.

Thanks for that bit of information.   So what I'm seeing is not
necessarily the cause for the long pauses.  But see my next comment.

I'll hopefully get some time to go over this code again. I was looking at the code on the train ride into work this morning, and trying to remember the details, but have not quite delved again into all of its details yet or why the assert I mention above should be failing.

After the logarithmic stride back to find the block containing the
start of the object, there is a object by object walk forward to find the
to find the start of the object

   558    while (n <= addr) {
   559      debug_only(HeapWord* last = q);   // for debugging
   560      q = n;
   561      n += _sp->block_size(n);

>From instrumentation I think the long pauses originate in this forward walk
(mostly in the block_size() method).   So maybe the BOT "DDDDDCCCCC...CDDDD"
indicates that BOT at the start of an objects is being trashed and we're
going way too far back.  I'm trying to use VerifyBlockOffsetArray but it seems to
have bit rotted.    I'll keep trying.

Ah, that's what I was afraid of. This must likely mean that when a large block is split, the suffix from the split
(which is typically returned to the free list) isn't getting fixed  up as was the intention, or when the sweeper
coalesces smaller blocks into a larger one, the new larger block isn't getting fixed correctly (although that seems
unlikely). Using VerifyBlockOffsetArray and asserting if the forward walk is more than a card's worth in length
would seem to be one way to catch that badness closer to when it happens...

Thanks for the update, Jon!
-- ramki


It might be worthwhile (if it is possible) to do a bisect on whatever the first known JDK (7uXX?) where the performance regression appears and try to narrow down the change that may have caused the regression, using James' test program. I have a sneaking suspicion (because of the elided assert) that it might well be a change I had made towards closing some BOT-walking/card-scanning cracks when initializing CMS objects ca 6uXX.

James, in case you have read thus far, can you provide the exact version number of the 6uXX Oracle jdk you used that did _not_ show the performance regression for your test program?

-- ramki

On Tue, May 12, 2015 at 1:50 PM, Jon Masamitsu <jon.masamitsu at<mailto:jon.masamitsu at>> wrote:

The logarithmic BOT is taking big steps back to
find the start of a large object.  But something is odd.

Is there a reason why the BOT entries would decrease for a while
and then increase without a value that gives the start of an object?

&_array->_offset_array[index] = 0xffffffff6550f600 "DDDDDDDDDDDDDD ..."

and then down the road.

 print &_array->_offset_array[0x110600U], _array->_offset_array[0x10f600U >

'D' is 0x44

N_words is 0x40


On 05/12/2015 08:46 AM, Srinivas Ramakrishna wrote:
Thanks for that background Jon; I'll try and look at the 8uxx code and run James's example when I get a few spare cycles (which won't be soon, unfortunately).

-- ramki


On May 8, 2015, at 14:25, Jon Masamitsu <jon.masamitsu at<mailto:jon.masamitsu at>> wrote:


I compared the memory/blockOffsetTable.* files between 6u35 and 7 and there
were essentially no differences.  The .cpp file had some changes in assertions.
The other two were the same except for comments.

Between 6 and 6u35 (didn't pin point it), we changed from the rather
weak N_powers=3  :-) to N_powers=14.

There seem to be two problematic cases.

1)  Spike in ParNew times that lasts for 2 (or a few) GC's
2) Continually growing ParNew times

>From just reading the CR

the test case seems to reproduce 1).  The test case
has a large object that lives till the application exits.
If it were a broken logarithmic BOT, I would not expect
the ParNew pauses to shrink again.


On 5/8/2015 11:49 AM, Srinivas Ramakrishna wrote:
This is indeed interesting...

Jesper, did you figure out why (as James seems to note) the problem is seen in JDK 8 but not in JDK 6 (he's using ParNew in both cases). Also, isn't the BOT logarithmic, which will allow threads to "quickly" traverse back to the start of even a large object? Did something change in the BOT that might have led to what James sees as a regression, or did the range that he characterizes as a "blind spot" merely move from one place to another?

Unfortunately, I have not been keeping up with the changes in this area and am not working with JDK 6 code much, so can't offer any clues, but am surprised that this would be a regression. (I would expect the same performance pathologies in this code to exist in 6 and forward -- has it been established conclusively that this is indeed a regression?)

-- ramki

On Fri, May 8, 2015 at 6:40 AM, James Lent <jlent at<mailto:jlent at>> wrote:
The explanation of the problem added by Jesper Wilhelmsson on 2015-05-06 08:59 to JDK-8079274 is interesting, but, not very satisfying.

1) The problem affects more than this one specific breakpoint.  It impacts objects in at least the range of about 480M to 512M.  The comment "A larger object probably triggers some higher level code that are able to skip scanning of this part of the memory" does not inspire confidence. It makes even more concerned that we do not understand this issue and that there could be other triggers.  It seems like "the higher level code" has a 32M blind spot.  Further I can create scenarios where the GC code takes progressively longer to clear the issue.  Presumably it completes the lower block scan during each GC cycle.  Why does it take longer and longer each time (my guess is it has something to do with the number of objects moved to survivor space).  If I cache 1 in 100 instead of 1 in 10 then there are 11 progressively slower ParNewGC (after several fast one) and the issue takes minutes to clear:

$ /usr/lib/jvm/java-7-oracle/bin/java -verbose:gc -XX:+PrintGCTimeStamps -XX:+PrintGCDetails -XX:+UseParNewGC -XX:+UseConcMarkSweepGC -Xmx4G -Xms4G LongParNewPause 536870384 100 100
0.308: [GC0.308: [ParNew: 272640K->3029K(306688K), 0.0113180 secs] 796927K->527316K(4160256K), 0.0114040 secs] [Times: user=0.05 sys=0.00, real=0.02 secs]
0.367: [GC0.367: [ParNew: 275669K->7766K(306688K), 0.0140840 secs] 799956K->532053K(4160256K), 0.0141630 secs] [Times: user=0.04 sys=0.01, real=0.02 secs]
0.430: [GC0.430: [ParNew: 280406K->10057K(306688K), 0.0120810 secs] 804693K->534344K(4160256K), 0.0121690 secs] [Times: user=0.05 sys=0.00, real=0.02 secs]
0.490: [GC0.490: [ParNew: 282697K->15383K(306688K), 0.0128540 secs] 806984K->539670K(4160256K), 0.0129390 secs] [Times: user=0.05 sys=0.00, real=0.02 secs]
0.551: [GC0.551: [ParNew: 288023K->21006K(306688K), 0.0146480 secs] 812310K->545294K(4160256K), 0.0147650 secs] [Times: user=0.05 sys=0.01, real=0.01 secs]
0.613: [GC0.613: [ParNew: 293646K->26805K(306688K), 0.0141250 secs] 817934K->551092K(4160256K), 0.0142050 secs] [Times: user=0.05 sys=0.00, real=0.01 secs]
0.675: [GC0.675: [ParNew: 299445K->24258K(306688K), 0.4816840 secs] 823732K->551436K(4160256K), 0.4817620 secs] [Times: user=1.90 sys=0.00, real=0.48 secs]
1.205: [GC1.205: [ParNew: 296898K->17914K(306688K), 3.4216550 secs] 824076K->547788K(4160256K), 3.4217180 secs] [Times: user=13.50 sys=0.00, real=3.42 secs]
4.674: [GC4.674: [ParNew: 290554K->17433K(306688K), 6.3406820 secs] 820428K->550031K(4160256K), 6.3407410 secs] [Times: user=25.00 sys=0.02, real=6.34 secs]
11.062: [GC11.062: [ParNew: 290073K->17315K(306688K), 10.9493130 secs] 822671K->552636K(4160256K), 10.9493890 secs] [Times: user=42.98 sys=0.03, real=10.95 secs]
22.059: [GC22.059: [ParNew: 289955K->17758K(306688K), 16.0539650 secs] 825276K->555798K(4160256K), 16.0540250 secs] [Times: user=62.44 sys=0.09, real=16.05 secs]
38.161: [GC38.161: [ParNew: 290398K->17745K(306688K), 20.6900820 secs] 828438K->558512K(4160256K), 20.6901420 secs] [Times: user=80.79 sys=0.08, real=20.69 secs]
58.898: [GC58.898: [ParNew: 290385K->21826K(306688K), 24.6781700 secs] 831152K->565310K(4160256K), 24.6782710 secs] [Times: user=95.58 sys=0.05, real=24.68 secs]
83.625: [GC83.625: [ParNew: 294466K->21834K(306688K), 30.3501800 secs] 837950K->568044K(4160256K), 30.3502610 secs] [Times: user=115.80 sys=0.11, real=30.35 secs]
114.022: [GC114.022: [ParNew: 294474K->21836K(306688K), 33.6648800 secs] 840684K->570772K(4160256K), 33.6649390 secs] [Times: user=127.38 sys=0.14, real=33.67 secs]
147.736: [GC147.736: [ParNew: 294476K->18454K(306688K), 38.9828430 secs] 843412K->570117K(4160256K), 38.9829040 secs] [Times: user=149.14 sys=0.15, real=38.99 secs]
186.766: [GC186.766: [ParNew: 291094K->26602K(306688K), 39.8726730 secs] 842757K->580977K(4160256K), 39.8727330 secs] [Times: user=156.35 sys=0.11, real=39.88 secs]
226.686: [GC226.686: [ParNew: 299242K->26612K(306688K), 0.0174470 secs] 853617K->583714K(4160256K), 0.0175300 secs] [Times: user=0.06 sys=0.00, real=0.02 secs]

2) The suggestion to use only 1 thread is not acceptable to me.  Use parallel GC with one thread?  Further it did not work for me (in fact it made things worse).  "user" time does now equal "real" time (and the new size is 1/4 as big) so I think the parameter took effect:

$ /usr/lib/jvm/java-8-oracle/bin/java -verbose:gc -XX:+PrintGCTimeStamps -XX:+PrintGCDetails -XX:+UseParNewGC -XX:+UseConcMarkSweepGC -Xmx4G -Xms4G -XX:ParallelGCThreads=1 LongParNewPause 536870384 100 10
0.226: [GC (Allocation Failure) 0.226: [ParNew: 68160K->6980K(76672K), 0.0489756 secs] 592447K->531267K(4185792K), 0.0490718 secs] [Times: user=0.05 sys=0.00, real=0.05 secs]
0.291: [GC (Allocation Failure) 0.291: [ParNew: 75140K->8512K(76672K), 29.8707281 secs] 599427K->539479K(4185792K), 29.8707954 secs] [Times: user=29.80 sys=0.00, real=29.88 secs]
30.180: [GC (Allocation Failure) 30.180: [ParNew: 76672K->8093K(76672K), 30.6357699 secs] 607639K->545772K(4185792K), 30.6358257 secs] [Times: user=30.57 sys=0.00, real=30.63 secs]
60.837: [GC (Allocation Failure) 60.837: [ParNew: 76253K->6830K(76672K), 69.2115255 secs] 613932K->552169K(4185792K), 69.2115783 secs] [Times: user=69.05 sys=0.01, real=69.22 secs]
130.068: [GC (Allocation Failure) 130.068: [ParNew: 74990K->8226K(76672K), 132.5118903 secs] 620329K->560381K(4185792K), 132.5119459 secs] [Times: user=132.21 sys=0.00, real=132.52 secs]
262.603: [GC (Allocation Failure) 262.603: [ParNew: 76386K->8512K(76672K), 0.0400138 secs] 628541K->568748K(4185792K), 0.0400687 secs] [Times: user=0.04 sys=0.00, real=0.04 secs]

3) Applications should not be expected to tune the GC settings to account for the size of one static object.  The connection between the size of this object and the GC performance was not easy to even find.  Further the parameter ParGCCardsPerStrideChunk is pretty low level and not one I think many application developers are familiar with.

Error: VM option 'ParGCCardsPerStrideChunk' is diagnostic and must be enabled via -XX:+UnlockDiagnosticVMOptions.
Error: Could not create the Java Virtual Machine.
Error: A fatal exception has occurred. Program will exit.

4) I can not reproduce this issue in Oracle 6.  This appears to be a regression.  How can fixing a regression be called an enhancement request?


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