I am working on a graphic design, vector drawing application that needs to render the data in every frame when there is a change. The issue is, that if the user is moving nodes, there will be changes during every single frame. This is not an issue with a tiny amount of data and is a major slowdown when there is anything more than a minor amount of data.
The reason is that in order to render I preform calculations and store data inside arrays. Then when the function responsible for the computation is done, the GC simply discards the data and next time the function is called, we create new arrays and new data.
In C++ I would probably allocate space in the memory and write to that space(over and over). I would probably improve performance that way. In languages that us GC I cannot allocate space that way. I have to do an ugly hack where I define an array as a class member and then write to that array from the function over and over although that array is only used in that one function and is not used by other methods of the class.
My questions is, what is the best way to reuse memory space in a language that uses GC?
Object pooling would be the major one, see here:
Gotoandplay Tutorial
Also
10 Top Tips around GC
I would also suggest you read through Grant's explanation of the garbage collection system in the Flash Player, it's quite unique, and understanding how Flash handles data is quite important to data intensive scripts.
This presentation
Related
I am making racing game in Libgdx.My game apk size is 9.92 mb and I am using four texture packer of total size is 9.92 Mb. My game is running on desktop but its run on android device very slow. What is reason behind it?
There are few loopholes which we neglect while programming.
Desktop processors are way more powerful so the game may run smoothly on Desktop but may slow on mobile Device.
Here are some key notes which you should follow for optimum game flow:
No I/O operations in render method.
Avoid creating Objects in Render Method.
Objects must be reused (for instance if your game have 1000 platforms but on current screen you can display only 3, than instead of making 1000 objects make 5 or 6 and reuse them). You can use Pool class provided by LibGdx for object pooling.
Try to load only those assets which are necessary to show on current screen.
Try to check your logcat if the Garbage collector is called. If so than try to use finalize method of object class to find which class object are collected as garbage and try to improve on it.
Good luck.
I've got some additional tips for improving performance:
Try to minimize texture bindings (or generally bindings when you're making a 3D game for example) in you render loop. Use texture atlases and try to use one texture after binding as often as possible, before binding another texture unit.
Don't display things that are not in the frustum/viewport. Calculate first if the drawn object can even be seen by the active camera or not. If it's not seen, just don't load it onto your GPU when rendering!
Don't use spritebatch.begin() or spritebatch.end() too often in the render loop, because every time you begin/end it, it's flushed and loaded onto the GPU for rendering its stuff.
Do NOT load assets while rendering, except you're doing it once in another thread.
The latest versions of libgdx also provide a GLProfiler where you can measure how many draw calls, texture bindings, vertices, etc. you have per frame. I'd strongly recommend this since there always can be situations where you would not expect an overhead of memory/computational usage.
Use libgdx Poolable (interface) objects and Pool for pooling objects and minimizing the time for object creation, since the creation of objects might cause tiny but noticable stutterings in your game-render loop
By the way, without any additional information, no one's going to give you a good or precise answer. If you think it's not worth it to write enough text or information for your question, why should it be worth it to answer it?
To really understand why your game is running slow you need to profile your application.
There are free tools avaiable for this.
On Desktop you can use VisualVM.
On Android you can use Android Monitor.
With profiling you will find excatly which methods are taking up the most time.
A likely cause of slowdowns is texture binding. Do you switch between different pages of packed textures often? Try to draw everything from one page before switching to another page.
The answer is likely a little more that just "Computer fast; phone slow". Rather, it's important to note that your computer Java VM is likely Oracles very nicely optimized JVM while your phone's Java VM is likely Dalvik, which, to say nothing else of its performance, does not have the same optimizations for object creation and management.
As others have said, libGDX provides a Pool class for just this reason. Take a look here: https://github.com/libgdx/libgdx/wiki/Memory-management
One very important thing in LibGDX is that you should make sure that sometimes loading assets from the memory cannot go in the render() method. Make sure that you are loading the assets in the right times and they are not coming in the render method.
Another very important thing is that try to calculate your math and make it independent of the render in the sense that your next frame should not wait for calculations to happen...!
These are the major 2 things i encountered when I was making the Snake game Tutorial.
Thanks,
Abhijeet.
One thing I have found, is that drawing is laggy. This means that if you are drawing offscreen items, then it uses a lot of useless resources. If you just check if they are onscreen before drawing, then your performance improves by a lot surprisingly.
Points to ponder (From personal experience)
DO NOT keep calling a function,in render method, that updates something like time,score on HUD (Make these updates only when required eg when score increases ONLY then update score etc)
Make calls IF specific (Make updations on certain condition, not all the time)
eg. Calling/updating in render method at 60FPS - means you update time 60 times a sec when it just needs to be updated once per sec )
These points will effect hugely on performance (thumbs up)
You need to check the your Image size of the game.If your image size are more than decrease the size of images by using the following link "http://tinypng.org/".
It will be help you.
Which garbage collection algorithms can recognize garbage objects as soon as they become garbage?
The only thing which comes to my mind is reference counting with an added cycle-search every time a reference count is decremented to a non-zero value.
Are there any other interesting collection algorithms which can achieve that? (Note that I'm asking out of curiosity only; I'm aware that all such collectors would probably be incredibly inefficient)
Though not being a garbage collection algorithm, escape analysis allows reasoning about life-time of objects. So, if efficiency is a concern and objects should be collected not in all but in "obvious" cases, it can be handy. The basic idea is to perform static analysis of the program (at compile time or at load time if compiled for a VM) and to figure out if a newly created object may escape a routine it is created in (hence the name of the analysis). If the object is not passed anywhere else, not stored in global memory, not returned from the given routine, etc., it can be released before returning from this routine or even earlier, at the place of its last use.
The objects that do not live longer than the associated method call can be allocated on the stack rather than in the heap so they can be removed from the garbage collection cycle at compile time thus lowering pressure on the general GC.
Such a mechanism would be called "heap management", not garbage collection.
By definition, garbage collection is decoupled from heap management. This is because in some environments/applications it is more efficient to skip doing a "free" operation and keeping track of what is in use. Instead, every once in a while, just ago around and gather all the unreferenced nodes and put them back on the free list.
== Addendum ==
I am being downvoted for attempting to correct the terminology of heap management with garbage collection. The Wikipedia article agrees with my usage, and what I learned at university, even though that was several decades ago. Languages such as Lisp and Snobol invented the need for garbage collection. Languages such as C don't provide such a heavy duty runtime environment; instead the rely on the programmer to manage cleanup of unused bits of memory and resources.
On collection, the garbage collector copies all live objects into another memory space, thus discarding all garbage objects in the process. A forward pointer to the copied object in new space is installed into the 'old' version of an object to ensure the collector updates all remaining references to the object correctly and doesn't erroneously copy the same object twice.
This obviously works quite well for stop-the-world-collectors. However, since pause times are long with stop-the-world, nowadays most garbage collectors allow the mutator threads to run concurrently with the collector, only stopping the mutators for a short time to do the initial stack scan.
So how can the collector ensure that the 'old' version of an object is not accessed by the mutator while/after copying it? I imagine the mutators could check for the forward pointer with some sort of read barrier, however this seems to costly to me since variables are read so often.
The Loaded Value Barrier implemented in Azul's Generational Pauseless Garbage Collector is an example of a solution to this problem. You can read about it in the article The Azul Garbage Collector posted on InfoQ in early 2011.
You pretty much need to use a read barrier or a write barrier. You're apparently already aware of read barriers so I won't try to get into them.
Writer barriers work because as long as you prevent writes from happening, you simply don't care whether somebody accesses the old or the new copy of the data. You set the write barrier, copy the data, and then start adjusting pointers. After the copy is made, you don't really care whether somebody reads the old or the new copy of the data, because the write barrier ensures they're identical. Once you're done adjusting pointers, everything will be working with the new data, so you revoke the write barrier.
There has been some work done with using page protection bits to mark an area of memory as read-only to create a write-barrier on fairly standard hardware. At least the last time I looked into it, however, this was still pretty much at a proof of concept stage -- working, but too slow to be very practical.
Disclaimer: this is related to java's Shenandoah GC only.
Your reasons are absolutely spot on for Shenandoah! Some details here for example.
In the not so long ago days, Shenandoah had write and read barriers for all primitive and reference types. The read barrier was actually just a single indirection via the forwarding pointer as you assume. Since they are so much more compared to writes (which was a much more complicated barrier), these read barriers were more expensive (cumulative time-wise) vs the write ones. This had to do with the sole fact that these are so darn many.
But, things have changed in jdk-13, when a Load Reference barrier was implemented. Thus only loads have a barrier, write happen the usual way. If you think about it, this makes perfect sense, in order to write to an Object field, you need to read that object first, as such if your barrier preserves the "to-space invariant", you will always read from the most recent and correct copy of the object; without the need to use a read barrier with a forwarding pointer.
So the problem I am having has not actually happened yet. I am planning out some code for a game I am currently working on and I know that I am going to be needing to conserve memory usage as much as possible from step one. My question is, if I have for example, 500k objects that will need to constantly be constructed and deconstructed. Would is save me any memory to have the functions those classes are going to use as function pointers.e.g. without function pointers class MyClass{public:void Update();void Draw();...}e.g. with function pointersclass MyClass{public:void * Update;void * Draw;...}Would this save me any memory or would any new creation of MyClass just access the same functions that were defined for the rest of them? If it does save me any memory would it be enough to be worthwhile?
Assuming those are not virtual functions, you'd use more memory with function pointers.
The first example
There is no allocation (beyond the base amount required to make new return unique pointers, or your additional implementation that you ... ellipsized).
Non-virtual member functions are basically static functions taking a this pointer.
The advantage is that your objects are really simple, and you'll have only one place to look to find the corresponding code.
The disadvantage is that you lose some flexibility, and have to cram all your code into single update/draw functions. This will be hard to manage for anything but a tiny game.
The second example
You allocate 2x pointers per object instance. Pointers are usually 4x to 8x bytes each (depending on your target platform and your compiler).
The advantage you gain a lot of flexibility of being able to change the function you're pointing to at runtime, and can have a multitude of functions that implement it - thus supporting (but not guaranteeing) better code organization.
The disadvantage is that it will be harder to tell which function each instance will point to when you're debugging your application, or when you're simply reading through the code.
Other options
Using function pointers this specific way (instance data members) usually makes more sense in plain C, and less sense in C++.
If you want those functions to be bound at runtime, you may want to make them virtual instead. The cost is compiler/implementation dependent, but I believe it is (usually) going to be one v-table pointer per object instance.
Plus you can take full advantage of virtual function syntax to make your functions based on type, rather than whatever you bound them to. It will be easier to debug than the function pointer option, since you can simply look at the derived type to figure out what function a particular instance points to.
You also won't have to initialize those function pointers - the C++ type system would do the equivalent initialization automatically (by building the v-table, and initializing each instance's v-table pointer).
See: http://www.parashift.com/c++-faq-lite/virtual-functions.html
I was thinking about garbage collection on the way home, and I began wondering, why does the garbage collector totally freeze execution of a program? Personally I would have designed it to block any threads which try to allocate a new object, but threads which were running would be left alone.
I can't imagine any situation where this would be a problem compared to how a garbage collector currently works.
I was thinking about garbage collection on the way home, and I began wondering, why does the garbage collector totally freeze execution of a program?
There is a trade-off between latency and throughput in GC design. You can either process heap-allocated blocks individually ("incremental") or you can batch them up and process them all at the same time ("stop the world"). Fully incremental collection never totally freezes a program and it has very low latency but it also has very poor throughput. Stop the world garbage collectors have the worst possible latency (freezing the program for seconds or even minutes at a time) but near-optimal throughput.
All of the major production GCs today provide a middle ground, typically with generational collection with the per-thread nursery generations collected in batches and incremental or concurrent collection of the shared old generation. Thus, only nursery collections incur pauses and nursery size is bounded so pause times are kept low, e.g. 10-100ms in .NET with the workstation GC.
For a simple GC algorithm that never pauses, see Baker's Treadmill. For more information on garbage collection I highly recommend the Memory Management Reference and the Garbage Collection Handbook.
There is a lot of misinformation in the other answers here. Jon Skeet wrote some source code and started discussing it from the point of view of garbage collection. You need to be very careful doing this because there is little correspondence between source code and what the GC sees. The compiler does instruction block rearrangements, register allocation, promotion and so on, all of which affect what is visible to the GC at run time. In particular, scope in source code is not carried through to compiled code and is typically replaced with the related concept of liveness. Jon also wrote that you must pause in order to get the global roots. That is not strictly true although it is the most efficient way to get the global roots and the resulting pause is almost always tiny (sub-millisecond) because you're just copying less than a kB of stack from each thread.
Powerlord wrote that moving collectors must block reads and, therefore, all threads that read. This is also not true. The simplest counter example is immutable data: referential transparency means you can read from any copy safely.
Kico wrote that pauses are required to determine reachability. This is also not true. See Dijkstra's research about "on-the-fly" collectors and any recent real-time GC such as Stacatto.
Jerry Coffin wrote the best answer but moving isn't the reason GCs pause. There are GCs that don't move but do pause (e.g. HLVM's) and those that do move but don't pause (e.g. Stacatto).
Modern garbage collectors (in .NET and Java, anyway) don't actually "stop the world" - they do all kinds of clever things to collect concurrently.
However, you might want to consider a situation like this:
object x = null;
object y = new object();
...
x = y;
y = null;
Now, suppose the GC looks at x, then the lines below the ... run, and then the GC looks at y - it won't have seen any live objects... but the object should still be live.
Basically there needs to be a certain amount of pausing in order to get a consistent set of references. Then there's compaction, reference reassignment etc. However, it isn't nearly as bad as it used to be in terms of requiring everything to be stopped for the whole of the GC cycle. It does, however, get painful to think about :)
In addition to what Kico Lobo said, Garbage Collectors can also move things around in memory.
Therefore, they don't just have to block threads that write to memory, but also threads that read from memory.
Which is every thread.
Most GCs stop execution because objects can move in memory during a collection cycle (at least with most reasonably recent designs). That means either reading or writing almost any object at the wrong time can cause a problem.
There are collectors that have been designed around the idea of just blocking reads (or writes) to the specific parts of memory being modified at a given time, so as long as execution only uses objects that aren't (currently) being moved around, it can proceed unhindered. The problem is that most typical hardware doesn't provide efficient support for this, so even though they work in principle, they're fairly inefficient in practice. There has been at least one attempt at adapting that type of algorithm to use the write protection available in a typical paging unit, but I'm not aware of its having been used for much other than research and experimentation.
The primary alternative is to make the collector incremental -- i.e. have it do only a small amount of work at a time, so even though other execution gets stopped, it only has to stop for a little while at any given time.
With multi-core machines becoming so common, however, I'd expect to see more work put into garbage collection algorithms that can run in parallel with other execution. Up until recently, the primary emphasis was on minimizing the total time/effort spent on garbage collection. The growing number of cores available is likely to (often) mean that doing more total work in garbage collection may be easily justified, if doing so allows the mainstream of the code to run with fewer hindrances.
Edit: You might want to read Paul Wilson's Survey of Uniprocessor Garbage Collection Techniques. This isn't definitive (especially any more, given its age), but it's at least a reasonable starting point.
Because that's the only way it can assure that the refereces it is going to clean are not been used by anyone else.
If it didn´t freezed the execution, it could not assure that.