Stack Memory VS Heap Memory

What and where are the stack and heap?

The stack is the memory set aside as scratch space for a thread of execution. When a function is called, a block is reserved on the top of the stack for local variables and some bookkeeping data. When that function returns, the block becomes unused and can be used the next time a function is called. The stack is always reserved in a LIFO (last in first out) order; the most recently reserved block is always the next block to be freed. This makes it really simple to keep track of the stack; freeing a block from the stack is nothing more than adjusting one pointer.

The heap is memory set aside for dynamic allocation. Unlike the stack, there's no enforced pattern to the allocation and deallocation of blocks from the heap; you can allocate a block at any time and free it at any time. This makes it much more complex to keep track of which parts of the heap are allocated or free at any given time; there are many custom heap allocators available to tune heap performance for different usage patterns.

Each thread gets a stack, while there's typically only one heap for the application (although it isn't uncommon to have multiple heaps for different types of allocation).

To answer your questions directly:

To what extent are they controlled by the OS or language runtime?

The OS allocates the stack for each system-level thread when the thread is created. Typically the OS is called by the language runtime to allocate the heap for the application.

What is their scope?

The stack is attached to a thread, so when the thread exits the stack is reclaimed. The heap is typically allocated at application startup by the runtime, and is reclaimed when the application (technically process) exits.

What determines the size of each of them?

The size of the stack is set when a thread is created. The size of the heap is set on application startup, but can grow as space is needed (the allocator requests more memory from the operating system).

What makes one faster?

The stack is faster because the access pattern makes it trivial to allocate and deallocate memory from it (a pointer/integer is simply incremented or decremented), while the heap has much more complex bookkeeping involved in an allocation or deallocation. Also, each byte in the stack tends to be reused very frequently which means it tends to be mapped to the processor's cache, making it very fast. Another performance hit for the heap is that the heap, being mostly a global resource, typically has to be multi-threading safe, i.e. each allocation and deallocation needs to be - typically - synchronized with "all" other heap accesses in the program.

A clear demonstration:


_{Image source: vikashazrati.wordpress.com}

Is accessing data in the heap faster than from the stack?

Is accessing data in the heap faster than from the stack?

Not inherently... on every architecture I've ever worked on, all the process "memory" can be expected to operate at the same set of speeds, based on which level of CPU cache / RAM / swap file is holding the current data, and any hardware-level synchronisation delays that operations on that memory may trigger to make it visible to other processes, incorporate other processes'/CPU (core)'s changes etc..

The OS (which is responsible for page faulting / swapping), and the hardware (CPU) trapping on accesses to not-yet-accessed or swapped-out pages, would not even be tracking which pages are "global" vs "stack" vs "heap"... a memory page is a memory page.

While the global vs stack vs heap usage to which memory is put is unknown to the OS and hardware, and all are backed by the same type of memory with the same performance characteristics, there are other subtle considerations (described in detail after this list):

• allocation - time the program spends "allocating" and "deallocating" memory, including occasional sbrk (or similar) virtual address allocation as the heap usage grows
• access - differences in the CPU instructions used by the program to access globals vs stack vs heap, and extra indirection via a runtime pointer when using heap-based data,
• layout - certain data structures ("containers" / "collections") are more cache-friendly (hence faster), while general purpose implementations of some require heap allocations and may be less cache friendly.

Allocation and deallocation

For global data (including C++ namespace data members), the virtual address will typically be calculated and hardcoded at compile time (possibly in absolute terms, or as an offset from a segment register; occasionally it may need tweaking as the process is loaded by the OS).

For stack-based data, the stack-pointer-register-relative address can also be calculated and hardcoded at compile time. Then the stack-pointer-register may be adjusted by the total size of function arguments, local variables, return addresses and saved CPU registers as the function is entered and returns (i.e. at runtime). Adding more stack-based variables will just change the total size used to adjust the stack-pointer-register, rather than having an increasingly detrimental effect.

Both of the above are effectively free of runtime allocation/deallocation overhead, while heap based overheads are very real and may be significant for some applications...

For heap-based data, a runtime heap allocation library must consult and update its internal data structures to track which parts of the block(s) aka pool(s) of heap memory it manages are associated with specific pointers the library has provided to the application, until the application frees or deletes the memory. If there is insufficient virtual address space for heap memory, it may need to call an OS function like sbrk to request more memory (Linux may also call mmap to create backing memory for large memory requests, then unmap that memory on free/delete).

Access

Because the absolute virtual address, or a segment- or stack-pointer-register-relative address can be calculated at compile time for global and stack based data, runtime access is very fast.

With heap hosted data, the program has to access the data via a runtime-determined pointer holding the virtual memory address on the heap, sometimes with an offset from the pointer to a specific data member applied at runtime. That may take a little longer on some architectures.

For the heap access, both the pointer and the heap memory must be in registers for the data to be accessible (so there's more demand on CPU caches, and at scale - more cache misses/faulting overheads).

Note: these costs are often insignificant - not even worth a look or second thought unless you're writing something where latency or throughput are enormously important.

Layout

If successive lines of your source code list global variables, they'll be arranged in adjacent memory locations (albeit with possible padding for alignment purposes). The same is true for stack-based variables listed in the same function. This is great: if you have X bytes of data, you might well find that - for N-byte cache lines - they're packed nicely into memory that can be accessed using X/N or X/N + 1 cache lines. It's quite likely that the other nearby stack content - function arguments, return addresses etc. will be needed by your program around the same time, so the caching is very efficient.

When you use heap based memory, successive calls to the heap allocation library can easily return pointers to memory in different cache lines, especially if the allocation size differs a fair bit (e.g. a three byte allocation followed by a 13 byte allocation) or if there's already been a lot of allocation and deallocation (causing "fragmentation"). This means when you go to access a bunch of small heap-allocated memory, at worst you may need to fault in as many cache lines (in addition to needing to load the memory containing your pointers to the heap). The heap-allocated memory won't share cache lines with your stack-allocated data - no synergies there.

Additionally, the C++ Standard Library doesn't provide more complex data structures - like linked lists, balanced binary trees or hash tables - designed for use in stack-based memory. So, when using the stack programmers tend to do what they can with arrays, which are contiguous in memory, even if it means a little brute-force searching. The cache-efficiency may well make this better overall than heap based data containers where the elements are spread across more cache lines. Of course, stack usage doesn't scale to large numbers of elements, and - without at least a backup option of using heap - creates programs that stop working if given more data to process than expected.

Discussion of your example program

In your example you're contrasting a global variable with a function-local (stack/automatic) variable... there's no heap involved. Heap memory comes from new or malloc/realloc. For heap memory, the performance issue worth noting is that the application itself is keeping track of how much memory is in use at which addresses - the records of all that take some time to update as pointers to memory are handed out by new/malloc/realloc, and some more time to update as the pointers are deleted or freed.

For global variables, the allocation of memory may effectively be done at compile time, while for stack based variables there's normally a stack pointer that's incremented by the compile-time-calculated sum of the sizes of local variables (and some housekeeping data) each time a function is called. So, when main() is called there may be some time to modify the stack pointer, but it's probably just being modified by a different amount rather than not modified if there's no buffer and modified if there is, so there's no difference in runtime performance at all.

Note

I omit some boring and largely irrelevant details above. For example, some CPUs use "windows" of registers to save the state of one function as they enter a call to another function; some function state will be saved in registers rather than on the stack; some function arguments will be passed in registers rather than on the stack; not all Operating Systems use virtual addressing; some non-PC-grade hardware may have more complex memory architecture with different implications....

What's the difference between Stack Memory and Heap Memory?

stack and heap in general

Each Thread has a Stack.

Whenever a function is called, parameters and some pointers are pushed to the stack(the stack grows with that)

Whenever a local variable is created, it will also be allocated on the stack.

When the livecycle of a variable ends or a function returns, all those things will be poped from the stack that will therefore shrink.

The heap is a part in memory that is shared by all threads of a process.

Space can be allocated on the heap using malloc and has to be freed with free when it is not used anymore to prevent memory leaks.

As the heap can e.g. be used by other threads, it will not be freed automatically.

Stack and heap in java

In java, primitive local variables will be allocated on the stack. If you call a method and pass a primitive type to it, java will copy the content of the variable(call by value) and pass that copy to the method.

Whenever you create an object with new, it will be allocated on the heap and a reference to that object is stored like a primitive type.

If you pass an object (reference) to a method, the reference will be copied and the method will therefore modify the same object(call by reference).

The JVM will detect if an object is not used and free it automatically(garbage collection).

a stack vs the stack and a heap vs the heap

"The stack" and "the heap" are memory lumps used in a specific way by a program or operating system. For example, the call stack can hold data pertaining to function calls and the heap is a region of memory specifically used for dynamically allocating space.

Contrast these with stack and heap data structures.

A stack can be thought of as an array where the last element in will be the first element out. Operations on this are called push and pop.

A heap is a data structure that represents a special type of graph where each node's value is greater than that of the node's children.

On a side note, keep in mind that "the stack" or "the heap" or any of the stack/heap data structures are unique to any given programming language but are simply concepts in the field of computer science.

What is more efficient stack memory or heap?

Stack is usually more efficient speed-wise, and simple to implement!

I tend to agree with Michael from Joel on Software site, who says,

It is more efficient to use the stack
when it is possible.

When you allocate from the heap, the
heap manager has to go through what is
sometimes a relatively complex
procedure, to find a free chunk of
memory. Sometimes it has to look
around a little bit to find something
of the right size.

This is not normally a terrible amount
of overhead, but it is definitely more
complex work compared to how the stack
functions. When you use memory from
the stack, the compiler is able to
immediately claim a chunk of memory
from the stack to use. It's
fundamentally a more simple procedure.

However, the size of the stack is
limited, so you shouldn't use it for
very large things, if you need
something that is greater than
something like 4k or so, then you
should always grab that from the heap
instead.

Another benefit of using the stack is
that it is automatically cleaned up
when the current function exits, you
don't have to worry about cleaning it
yourself. You have to be much more
careful with heap allocations to make
sure that they are cleaned up. Using
smart pointers that handle
automatically deleting heap
allocations can help a lot with this.

I sort of hate it when I see code that
does stuff like allocates 2 integers
from the heap because the programmer
needed a pointer to 2 integers and
when they see a pointer they just
automatically assume that they need to
use the heap. I tend to see this with
less experienced coders somewhat -
this is the type of thing that you
should use the stack for and just have
an array of 2 integers declared on the
stack.

Quoted from a really good discussion at Joel on Software site:

stack versus heap: more efficiency?

Java stack and heap memory management

Where are the methods of s stored?

They are stored in the String class object; it is an object loaded by a ClassLoader object when String is first referenced in the program. All the implementations of the JVM that existed when I read about this last never deallocated the memory for a class object once it was loaded. It's on the heap.

Had I created another object of MemoryClass inside myMethod, would JVM allocate memory for the same methods again inside the stack memory?

No, methods and data for objects is kept separately, specifically because the JVM never needs more than one copy of the methods.

Would JVM free the memory allocated to myMethod as soon as it's execution is completed, if so, how would it manage the situation mentioned in question 2(only applicable if JVM allocates memory multiple times to the same method).

No. Java doesn't generally "immediately free memory" of things stored on the heap. It would make things run too slowly. It only frees memory when the garbage collector runs, and it does that only when its algorithm for running the garbage collector decides it is time.

What would have been the case, if I had only declared s and did not initialize it, would JVM still allocate memory to all the methods of java.lang.String class,if so,why?

This depends on the JVM implementation, I think, and maybe the compiler. If you declare a variable and never use it, it is quite possible (and common) for the compiler to notice that there is no use for it and to not put it into the class file. If it isn't in the class file, it is never referenced, and therefore it and its methods are not loaded, etc. If the compiler puts it in anyway but it is never referenced, then the ClassLoader wouldn't have any reason to load it, but I'm a little vague on whether it would get loaded or not. Might depend on the JVM implementation; does it load things because there are variables of the class or only when they are referenced? How many ClassLoader algorithms can dance on the head of a 4-digit PIN?

I encourage you to read about the JVM and ClassLoaders and such; you will gain so much more by reading an explanation of how it works rather than poking at it with examples you can think up.

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