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Let’s refresh our memory!
Memory management in .NET
Maarten Balliauw
@maartenballiauw
.NET runtime
Manages execution of programs
Just-in-time compilation: Intermediate Language (IL) ->machine code
Type safety
Exception handling
Security
Thread management
Memory management
Garbage collection (GC)
Garbage Collector
Memory management and GC
“Virtually unlimited memory for our applications”
Big chunk of memory pre-allocated
Runtime manages allocation in that chunk
Garbage Collector (GC) reclaims unused memory, making it available again
.NET memory management 101
Memory allocation
Objects allocated in “managed heap” (big chunk of memory)
Allocating memory is fast, it’s just adding a pointer
Some unmanaged memory is also consumed (not GC-ed)
.NET CLR, Dynamic libraries, Graphics buffer, …
Memory release or “Garbage Collection” (GC)
Generations
Large Object Heap
.NET memory management 101
Memory allocation
Memory release or “Garbage Collection” (GC)
GC releases objects no longer in use by examining application roots
GC builds a graph of all the objects that are reachable from these roots
Object unreachable? Remove object, release memory, compact heap
Takes time to scan all objects!
Generations
Large Object Heap
.NET memory management 101
Memory allocation
Memory release or “Garbage Collection” (GC)
Generations
Large Object Heap
Generation 0 Generation 1 Generation 2
Short-lived objects (e.g. Local
variables)
In-between objects Long-lived objects (e.g. App’s
main form)
.NET memory management 101
Memory allocation
Memory release or “Garbage Collection” (GC)
Generations
Large Object Heap (LOH)
Special segment for large objects (>85KB)
Collected only during full garbage collection
Not compacted (by default) -> fragmentation!
Fragmentation can cause OutOfMemoryException
The .NET garbage collector
When does it run? Vague… But usually:
Out of memory condition – when the system fails to allocate or re-allocate memory
After some significant allocation – if X memory is allocated since previous GC
Failure of allocating some native resources – internal to .NET
Profiler – when triggered from profiler API
Forced – when calling methods on System.GC
Application moves to background
GC is not guaranteed to run
http://blogs.msdn.com/b/oldnewthing/archive/2010/08/09/10047586.aspx
http://blogs.msdn.com/b/abhinaba/archive/2008/04/29/when-does-the-net-compact-framework-garbage-collector-run.aspx
The .NET garbage collector
Runs very often for gen0
Short-lived objects, few references, fast to clean
Local variable
Web request/response
Higher generation
Usually more references, slower to clean
GC pauses the running application to do its thing
Usually short, except when not…
Background GC (enabled by default)
Concurrent with application threads
May still introduce short locks/pauses, usually just for one thread
Helping the GC, avoid pauses
Optimize allocations (use struct when it makes sense, Span<T>, object pooling)
Don’t allocate at all
Make use of IDisposable / using statement
Clean up references, giving the GC an easy job
Weak references
Allow the GC to collect these objects, no need for checks
Finalizers
Beware! Moved to finalizer queue -> always gen++
Helping the GC
DEMO
https://github.com/maartenba/memory-demos
Allocations
When is memory allocated?
Not for value types (int, bool, struct, decimal, enum, float, byte, long, …)
Allocated on stack, not on heap
Not managed by garbage collector
For reference types
When you new
When you load data into a variable, object, property, ...
Hidden allocations!
Boxing!
Put an int in a box
Take an int out of a box
Lambda’s/closures
Allocate compiler-generated
DisplayClass to capture state
Params arrays
And more!
int i = 42;
// boxing - wraps the value type in an "object box"
// (allocating a System.Object)
object o = i;
// unboxing - unpacking the "object box" into an int again
// (CPU effort to unwrap)
int j = (int)o;
How to find them?
Past experience
Intermediate Language (IL)
Profiler
“Heap allocations viewer”
ReSharper Heap Allocations Viewer plugin
Roslyn’s Heap Allocation Analyzer
Don’t do premature optimization – measure!
Hidden allocations
DEMO
https://github.com/maartenba/memory-demos
ReSharper Heap Allocations Viewer plugin
Roslyn’s Heap Allocation Analyzer
Don’t optimize what
should not be
optimized.
Measure!
We know when allocations are done...
...but perhaps these don’t matter.
Measure!
How frequently are we allocating?
How frequently are we collecting?
What generation do we end up on?
Are our allocations introducing pauses?
www.jetbrains.com/dotmemory (and www.jetbrains.com/dottrace)
Always Be Measuring
DEMO
https://github.com/maartenba/memory-demos
Object pools / object re-use
If it make sense, re-use objects
Fewer allocations, fewer objects for the GC to scan
Fewer memory traffic that can trigger a full GC
Object pooling - object pool pattern
Create a pool of objects that can be cleaned and re-used
https://www.codeproject.com/articles/20848/c-object-pooling
“Optimize ASP.NET Core” - https://github.com/aspnet/AspLabs/issues/3
Garbage Collector & Allocations
GC is optimized for high memory traffic in short-lived objects
Use that knowledge! Don’t fear allocations!
Don’t optimize what should not be optimized…
GC is the concept that makes .NET / C# tick – use it!
Know when allocations happen
GC is awesome
Gen2 collection that stop the world not so much…
Measure!
Strings
Strings are objects
.NET tries to make them look like a value type, but they are a reference type
Read-only collection of char
Length property
A bunch of operator overloading
Allocated on the managed heap
var a = new string('-', 25);
var b = a.Substring(5);
var c = httpClient.GetStringAsync("http://blog.maartenballiauw.be");
String literals
Are all strings on the heap? Are all strings duplicated?
var a = "Hello, World!";
var b = "Hello, World!";
Console.WriteLine(a == b);
Console.WriteLine(Object.ReferenceEquals(a, b));
Prints true twice. So “Hello World” only in memory once?
Portable Executable (PE)
#UserStrings
DEMO
https://github.com/maartenba/memory-demos
String literals in #US
Compile-time optimization
Store literals only once in PE header metadata stream ECMA-335 standard, section II.24.2.4
Reference literals (IL: ldstr)
var a = Console.ReadLine();
var b = Console.ReadLine();
Console.WriteLine(a == b);
Console.WriteLine(Object.ReferenceEquals(a, b));
String duplicates
Any .NET application has them (System.Globalization duplicates quite a few)
Are they bad?
.NET GC is fast for short-lived objects, so meh.
Don’t waste memory with string duplicates on gen2
(but: it’s okay to have strings there)
String interning
Store (and read) strings from the intern pool
Simply call String.Intern when “allocating” or reading the string
Scans intern pool and returns reference
var url = "http://blog.maartenballiauw.be";
var stringList = new List<string>();
for (int i = 0; i < 1000000; i++)
{
stringList.Add(string.Intern(url + "/"));
}
String interning caveats
Why are not all strings interned by default?
CPU vs. memory
Not on the heap but on intern pool
No GC on intern pool – all strings in memory for AppDomain lifetime!
Rule of thumb
Lot of long-lived, few unique -> interning good
Lot of long-lived, many unique -> no benefit, memory growth
Lot of short-lived -> trust the GC
Measure!
Exploring the heap
for fun and profit
How would you do it...
Build a managed type system, store in memory, CPU/memory friendly
Probably:
Store type info (what’s in there, what’s the offset of fieldN, …)
Store field data (just data)
Store method pointers (“who you gonna call?”)
Inheritance information
Stuff on the Stack
Stuff on the Managed Heap
(scroll down for more...)
.NET memory is like a database
Pointer to an “instance”
Instance
Pointer to Runtime Type Information (RTTI)
Field values (which can be pointers in turn)
RunTime Type Information
Interface addresses
Instance method addresses
Static method addresses
…
Theory is nice...
Microsoft.Diagnostics.Runtime (ClrMD)
“ClrMD is a set of advanced APIs for programmatically inspecting a crash dump of
a .NET program much in the same way that the SOS Debugging Extensions (SOS)
do. This allows you to write automated crash analysis for your applications as well
as automate many common debugger tasks. In addition to reading crash dumps
ClrMD also allows supports attaching to live processes.”
“LINQ-to-heap”
Maarten’s definition
ClrMD
DEMO
https://github.com/maartenba/memory-demos
But... Why?
Programmatic insight into memory space of a running project
Unit test critical paths and assert behavior (did we clean up what we expected?)
Capture memory issues in running applications
Other options in this space
dotMemory Unit (JetBrains)
Benchmark.NET
Conclusion
Conclusion
Garbage Collector (GC) optimized for high memory traffic + short-lived objects
Don’t fear allocations! But beware of gen2 “stop the world”
String interning when lot of long-lived, few unique
Don’t optimize what should not be optimized…
Measure!
Using a profiler/memory analysis tool
ClrMD to automate inspections
dotMemory Unit, Benchmark.NET, … to profile unit tests
Blog series: https://blog.maartenballiauw.be
.NET Internals: stack
memory management
Nikolay Balakin
16:05 – Track 2
Thank you!
http://blog.maartenballiauw.be
@maartenballiauw

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.NET Fest 2018. Maarten Balliauw. Let’s refresh our memory! Memory management in .NET

  • 1. Let’s refresh our memory! Memory management in .NET Maarten Balliauw @maartenballiauw
  • 2. .NET runtime Manages execution of programs Just-in-time compilation: Intermediate Language (IL) ->machine code Type safety Exception handling Security Thread management Memory management Garbage collection (GC)
  • 4. Memory management and GC “Virtually unlimited memory for our applications” Big chunk of memory pre-allocated Runtime manages allocation in that chunk Garbage Collector (GC) reclaims unused memory, making it available again
  • 5. .NET memory management 101 Memory allocation Objects allocated in “managed heap” (big chunk of memory) Allocating memory is fast, it’s just adding a pointer Some unmanaged memory is also consumed (not GC-ed) .NET CLR, Dynamic libraries, Graphics buffer, … Memory release or “Garbage Collection” (GC) Generations Large Object Heap
  • 6. .NET memory management 101 Memory allocation Memory release or “Garbage Collection” (GC) GC releases objects no longer in use by examining application roots GC builds a graph of all the objects that are reachable from these roots Object unreachable? Remove object, release memory, compact heap Takes time to scan all objects! Generations Large Object Heap
  • 7. .NET memory management 101 Memory allocation Memory release or “Garbage Collection” (GC) Generations Large Object Heap Generation 0 Generation 1 Generation 2 Short-lived objects (e.g. Local variables) In-between objects Long-lived objects (e.g. App’s main form)
  • 8. .NET memory management 101 Memory allocation Memory release or “Garbage Collection” (GC) Generations Large Object Heap (LOH) Special segment for large objects (>85KB) Collected only during full garbage collection Not compacted (by default) -> fragmentation! Fragmentation can cause OutOfMemoryException
  • 9. The .NET garbage collector When does it run? Vague… But usually: Out of memory condition – when the system fails to allocate or re-allocate memory After some significant allocation – if X memory is allocated since previous GC Failure of allocating some native resources – internal to .NET Profiler – when triggered from profiler API Forced – when calling methods on System.GC Application moves to background GC is not guaranteed to run http://blogs.msdn.com/b/oldnewthing/archive/2010/08/09/10047586.aspx http://blogs.msdn.com/b/abhinaba/archive/2008/04/29/when-does-the-net-compact-framework-garbage-collector-run.aspx
  • 10. The .NET garbage collector Runs very often for gen0 Short-lived objects, few references, fast to clean Local variable Web request/response Higher generation Usually more references, slower to clean GC pauses the running application to do its thing Usually short, except when not… Background GC (enabled by default) Concurrent with application threads May still introduce short locks/pauses, usually just for one thread
  • 11. Helping the GC, avoid pauses Optimize allocations (use struct when it makes sense, Span<T>, object pooling) Don’t allocate at all Make use of IDisposable / using statement Clean up references, giving the GC an easy job Weak references Allow the GC to collect these objects, no need for checks Finalizers Beware! Moved to finalizer queue -> always gen++
  • 14. When is memory allocated? Not for value types (int, bool, struct, decimal, enum, float, byte, long, …) Allocated on stack, not on heap Not managed by garbage collector For reference types When you new When you load data into a variable, object, property, ...
  • 15. Hidden allocations! Boxing! Put an int in a box Take an int out of a box Lambda’s/closures Allocate compiler-generated DisplayClass to capture state Params arrays And more! int i = 42; // boxing - wraps the value type in an "object box" // (allocating a System.Object) object o = i; // unboxing - unpacking the "object box" into an int again // (CPU effort to unwrap) int j = (int)o;
  • 16. How to find them? Past experience Intermediate Language (IL) Profiler “Heap allocations viewer” ReSharper Heap Allocations Viewer plugin Roslyn’s Heap Allocation Analyzer Don’t do premature optimization – measure!
  • 17. Hidden allocations DEMO https://github.com/maartenba/memory-demos ReSharper Heap Allocations Viewer plugin Roslyn’s Heap Allocation Analyzer
  • 18. Don’t optimize what should not be optimized.
  • 19. Measure! We know when allocations are done... ...but perhaps these don’t matter. Measure! How frequently are we allocating? How frequently are we collecting? What generation do we end up on? Are our allocations introducing pauses? www.jetbrains.com/dotmemory (and www.jetbrains.com/dottrace)
  • 21. Object pools / object re-use If it make sense, re-use objects Fewer allocations, fewer objects for the GC to scan Fewer memory traffic that can trigger a full GC Object pooling - object pool pattern Create a pool of objects that can be cleaned and re-used https://www.codeproject.com/articles/20848/c-object-pooling “Optimize ASP.NET Core” - https://github.com/aspnet/AspLabs/issues/3
  • 22. Garbage Collector & Allocations GC is optimized for high memory traffic in short-lived objects Use that knowledge! Don’t fear allocations! Don’t optimize what should not be optimized… GC is the concept that makes .NET / C# tick – use it! Know when allocations happen GC is awesome Gen2 collection that stop the world not so much… Measure!
  • 24. Strings are objects .NET tries to make them look like a value type, but they are a reference type Read-only collection of char Length property A bunch of operator overloading Allocated on the managed heap var a = new string('-', 25); var b = a.Substring(5); var c = httpClient.GetStringAsync("http://blog.maartenballiauw.be");
  • 25. String literals Are all strings on the heap? Are all strings duplicated? var a = "Hello, World!"; var b = "Hello, World!"; Console.WriteLine(a == b); Console.WriteLine(Object.ReferenceEquals(a, b)); Prints true twice. So “Hello World” only in memory once?
  • 27. String literals in #US Compile-time optimization Store literals only once in PE header metadata stream ECMA-335 standard, section II.24.2.4 Reference literals (IL: ldstr) var a = Console.ReadLine(); var b = Console.ReadLine(); Console.WriteLine(a == b); Console.WriteLine(Object.ReferenceEquals(a, b));
  • 28. String duplicates Any .NET application has them (System.Globalization duplicates quite a few) Are they bad? .NET GC is fast for short-lived objects, so meh. Don’t waste memory with string duplicates on gen2 (but: it’s okay to have strings there)
  • 29. String interning Store (and read) strings from the intern pool Simply call String.Intern when “allocating” or reading the string Scans intern pool and returns reference var url = "http://blog.maartenballiauw.be"; var stringList = new List<string>(); for (int i = 0; i < 1000000; i++) { stringList.Add(string.Intern(url + "/")); }
  • 30. String interning caveats Why are not all strings interned by default? CPU vs. memory Not on the heap but on intern pool No GC on intern pool – all strings in memory for AppDomain lifetime! Rule of thumb Lot of long-lived, few unique -> interning good Lot of long-lived, many unique -> no benefit, memory growth Lot of short-lived -> trust the GC Measure!
  • 31. Exploring the heap for fun and profit
  • 32. How would you do it... Build a managed type system, store in memory, CPU/memory friendly Probably: Store type info (what’s in there, what’s the offset of fieldN, …) Store field data (just data) Store method pointers (“who you gonna call?”) Inheritance information
  • 33. Stuff on the Stack
  • 34. Stuff on the Managed Heap (scroll down for more...)
  • 35. .NET memory is like a database Pointer to an “instance” Instance Pointer to Runtime Type Information (RTTI) Field values (which can be pointers in turn) RunTime Type Information Interface addresses Instance method addresses Static method addresses …
  • 36. Theory is nice... Microsoft.Diagnostics.Runtime (ClrMD) “ClrMD is a set of advanced APIs for programmatically inspecting a crash dump of a .NET program much in the same way that the SOS Debugging Extensions (SOS) do. This allows you to write automated crash analysis for your applications as well as automate many common debugger tasks. In addition to reading crash dumps ClrMD also allows supports attaching to live processes.” “LINQ-to-heap” Maarten’s definition
  • 38. But... Why? Programmatic insight into memory space of a running project Unit test critical paths and assert behavior (did we clean up what we expected?) Capture memory issues in running applications Other options in this space dotMemory Unit (JetBrains) Benchmark.NET
  • 40. Conclusion Garbage Collector (GC) optimized for high memory traffic + short-lived objects Don’t fear allocations! But beware of gen2 “stop the world” String interning when lot of long-lived, few unique Don’t optimize what should not be optimized… Measure! Using a profiler/memory analysis tool ClrMD to automate inspections dotMemory Unit, Benchmark.NET, … to profile unit tests Blog series: https://blog.maartenballiauw.be
  • 41. .NET Internals: stack memory management Nikolay Balakin 16:05 – Track 2