I'm trying to understand the actual difference between committed bytes and commit limit.
From the definitions below,
Commit Limit is the amount of virtual memory that can be committed
without having to extend the paging file(s). It is measured in bytes.
Committed memory is the physical memory which has space reserved on the disk paging files.
Committed Bytes is the amount of committed virtual memory, in bytes.
From my computer configurations, i see that my Physical Memory is 1991 MB, Virtual Memory (total paging file for all files) is 1991 MB and
Minimum Allowed is 16 MB, Recommended is 2986 MB and Currently Allocated is 1991 MB.
But when i open my perfmon and monitor Committed Bytes and Commit Limit, the numbers differ a lot. So what exactly are these Committed Bytes and Commit Limit and how do they form.
Right now in my perfmon, Committed Bytes is running at 3041 MB (Sometimes it goes to 4000 MB as well), Commit Limit is 4177 MB. So how are they calculated. Kindly explain. I've read a lot of documents but I wasn't understanding how this works.
Please help. Thanks.
Related
I have a program which accesses a large memory block allocated with mmap. It accesses it unevenly, mostly accessing the first ~1 GB on memory, sometimes the next ~2 GB of memory, and rarely the last ~4 GB of memory. The memory is a shared memory mapping with PROT_READ and PROT_WRITE backed by an unlinked file.
Compared to the Linux version, I've found the MacOS version is exceedingly slow. Yet, the memory pressure is low. (6.42 Used, 9.51 Cached.)
The following usage statistics originate from activity monitor:
"Memory": 1.17 GB
Real memory Size: 3.71 GB
Virtual Memory Size: 51.15 GB
Shared Memory Size: 440 KB
Private Memory Size: 3.74 GB
Why is this? Is there anyway to improve caching behavior?
In Go Should the "Sys" stat or any other stat/combination reported by runtime.ReadMemStats approximately equal the resident memory set reported by ps aux?
Alternatively, assuming some memory may be swapped out, should the Sys stat be approximately greater than or equal to the RSS?
We have a long-running web service that deals with a high frequency of requests and we are finding that the RSS quickly climbs up to consume virtually all of the 64GB memory on our servers. When it hits ~85% we begin to experience considerable degradation in our response times and in how many concurrent requests we can handle. The run I've listed below is after about 20 hours of execution, and is already at 51% memory usage.
I'm trying to determine if the likely cause is a memory leak (we make some calls to CGO). The data seems to indicate that it is, but before I go down that rabbit hole I want to rule out a fundamental misunderstanding of the statistics I'm using to make that call.
This is an amd64 build targeting linux and executing on CentOS.
Reported by runtime.ReadMemStats:
Alloc: 1294777080 bytes (1234.80MB) // bytes allocated and not yet freed
Sys: 3686471104 bytes (3515.69MB) // bytes obtained from system (sum of XxxSys below)
HeapAlloc: 1294777080 bytes (1234.80MB) // bytes allocated and not yet freed (same as Alloc above)
HeapSys: 3104931840 bytes (2961.09MB) // bytes obtained from system
HeapIdle: 1672339456 bytes (1594.87MB) // bytes in idle spans
HeapInuse: 1432592384 bytes (1366.23MB) // bytes in non-idle span
Reported by ps aux:
%CPU %MEM VSZ RSS
1362 51.3 306936436 33742120
How can 8086 processors (or real mode on later processors) access harddrives larger than 1 MB, when they can only access 1 MB (without expanded memory) of RAM?
Access is not linear (by byte) but by sector. Sector size may be for example 512 bytes. The computer reads sectors to memory as needed.
We are running a mixed mode process (managed + unmanaged) on Win 7 64 bit.
Our process is using up too much memory (especially VM). Based on our analysis, the majority of the memory is used by a big native heap. Our theory is that the LFH is saving too many free blocks in committed memory, for future allocations. They sum to about 1.2 GB while our actual allocated native memory is only at most 0.6 GB.
These numbers are from a test run of the process. In production it sometimes exceeded 10 GB of VM - with maybe 6 GB unaccounted for by known allocations.
We'd like to know if this theory of excessive committed-but-free-for-allocation segments is true, and how this waste can be reduced.
Here's the details of our analysis.
First we needed to figure out what's allocated and rule out memory leaks. We ran the excellent Heap Inspector by Jelle van der Beek and we ruled out a leak and established that the known allocations are at most 0.6 deci-GB.
We took a full memory dump and opened in WinDbg.
Ran !heap -stat
It reports a big native heap with 1.83 deci-GB committed memory. Much more than the sum of our allocations!
_HEAP 000000001b480000
Segments 00000078
Reserved bytes 0000000072980000
Committed bytes 000000006d597000
VirtAllocBlocks 0000001e
VirtAlloc bytes 0000000eb7a60118
Then we ran !heap -stat -h 0000001b480000
heap # 000000001b480000
group-by: TOTSIZE max-display: 20
size #blocks total ( %) (percent of total busy bytes)
c0000 12 - d80000 (10.54)
b0000 d - 8f0000 (6.98)
e0000 a - 8c0000 (6.83)
...
If we add up all the 20 reported items, they add up to 85 deci-MB - much less than the 1.79 deci-GB we're looking for.
We ran !heap -h 1b480000
...
Flags: 00001002
ForceFlags: 00000000
Granularity: 16 bytes
Segment Reserve: 72a70000
Segment Commit: 00002000
DeCommit Block Thres: 00000400
DeCommit Total Thres: 00001000
Total Free Size: 013b60f1
Max. Allocation Size: 000007fffffdefff
Lock Variable at: 000000001b480208
Next TagIndex: 0000
Maximum TagIndex: 0000
Tag Entries: 00000000
PsuedoTag Entries: 00000000
Virtual Alloc List: 1b480118
Unable to read nt!_HEAP_VIRTUAL_ALLOC_ENTRY structure at 000000002acf0000
Uncommitted ranges: 1b4800f8
FreeList[ 00 ] at 000000001b480158: 00000000be940080 . 0000000085828c60 (9451 blocks)
...
When adding up up all the segment sizes in the report, we get:
Total Size = 1.83 deci-GB
Segments Marked Busy Size = 1.50 deci-GB
Segments Marked Busy and Internal Size = 1.37 deci-GB
So all the committed bytes in this report do add up to the total commit size. We grouped on block size and the most heavy allocations come from blocks of size 0x3fff0. These don't correspond to allocations that we know of. There were also mystery blocks of other sizes.
We ran !heap -p -all. This reports the LFH internal segments but we don't understand it fully. Those 3fff0 sized blocks in the previous report appear in the LFH report with an asterisk mark and are sometimes Busy and sometimes Free. Then inside them we see many smaller free blocks.
We guess these free blocks are legitimate. They are committed VM that the LFH reserves for future allocations. But why is their total size so much greater than sum of memory allocations, and can this be reduced?
Well, I can sort of answer my own question.
We had been doing lots and lots of tiny allocations and deallocations in our program. There was no leak, but it seems this somehow created a fragmentation of some sort. After consolidating and eliminating most of these allocations our software is running much better and using less peak memory. It is still a mystery why the peak committed memory was so much higher than the peak actually-used memory.
I am trying to understand how heap fragmenation works. What does the following output tell me?
Is this heap overly fragmented?
I have 243010 "free objects" with a total of 53304764 bytes. Are those "free object" spaces in the heap that once contained object but that are now garabage collected?
How can I force a fragmented heap to clean up?
!dumpheap -type Free -stat
total 243233 objects
Statistics:
MT Count TotalSize Class Name
0017d8b0 243010 53304764 Free
It depends on how your heap is organized. You should have a look at how much memory in Gen 0,1,2 is allocated and how much free memory you have there compared to the total used memory.
If you have 500 MB managed heap used but and 50 MB is free then you are doing pretty well. If you do memory intensive operations like creating many WPF controls and releasing them you need a lot more memory for a short time but .NET does not give the memory back to the OS once you allocated it. The GC tries to recognize allocation patterns and tends to keep your memory footprint high although your current heap size is way too big until your machine is running low on physical memory.
I found it much easier to use psscor2 for .NET 3.5 which has some cool commands like ListNearObj where you can find out which objects are around your memory holes (pinned objects?). With the commands from psscor2 you have much better chances to find out what is really going on in your heaps. Most commands are also available in SOS.dll in .NET 4 as well.
To answer your original question: Yes free objects are gaps on the managed heap which can simply be the free memory block after your last allocated object on a GC segement. Or if you do !DumpHeap with the start address of a GC segment you see the objects allocated in that managed heap segment along with your free objects which are GC collected objects.
This memory holes do normally happen in Gen2. The object addresses before and after the free object do tell you what potentially pinned objects are around your hole. From this you should be able to determine your allocation history and optimize it if you need to.
You can find the addresses of the GC Heaps with
0:021> !EEHeap -gc
Number of GC Heaps: 1
generation 0 starts at 0x101da9cc
generation 1 starts at 0x10061000
generation 2 starts at 0x02aa1000
ephemeral segment allocation context: none
segment begin allocated size
02aa0000 02aa1000** 03836a30 0xd95a30(14244400)
10060000 10061000** 103b8ff4 0x357ff4(3506164)
Large object heap starts at 0x03aa1000
segment begin allocated size
03aa0000 03aa1000 03b096f8 0x686f8(427768)
Total Size: Size: 0x115611c (18178332) bytes.
------------------------------
GC Heap Size: Size: 0x115611c (18178332) bytes.
There you see that you have heaps at 02aa1000 and 10061000.
With !DumpHeap 02aa1000 03836a30 you can dump the GC Heap segment.
!DumpHeap 02aa1000 03836a30
Address MT Size
...
037b7b88 5b408350 56
037b7bc0 60876d60 32
037b7be0 5b40838c 20
037b7bf4 5b408350 56
037b7c2c 5b408728 20
037b7c40 5fe4506c 16
037b7c50 60876d60 32
037b7c70 5b408728 20
037b7c84 5fe4506c 16
037b7c94 00135de8 519112 Free
0383685c 5b408728 20
03836870 5fe4506c 16
03836880 608c55b4 96
....
There you find your free memory blocks which was an object which was already GCed. You can dump the surrounding objects (the output is sorted address wise) to find out if they are pinned or have other unusual properties.
You have 50MB of RAM as Free space. This is not good.
Having .NET allocating blocks of 16MB from process, we have a fragmentation issue indeed.
There are plenty of reasons to fragmentation to occure in .NET.
Have a look here and here.
In your case it is possibly a pinning. As 53304764 / 243010 makes 219.35 bytes per object - much lower then LOH objects.