I love almost every topic in Computer Science and Software Engineering, but the part I probably love the most is Low-Level Programming. It's fascinating to study, experiment, and understand what happens at the edge between software and hardware. Sometimes, this knowledge helps you debug and solve problems, even in high-level application programming. One example is the Stack Memory. Understanding how it works—especially when working close to the hardware—is crucial to avoiding and debugging problems.
In this article, I’ll discuss how frequent function calls in a program can create overhead and degrade performance. This content assumes you already have some knowledge about stack and heap memory, as well as CPU registers, to follow the explanation.
What is a Stack Frame?
Imagine you just executed a program on your computer. Your operating system calls the scheduler, which reserves memory for your program and gets it ready for the CPU to process its instructions. This reserved memory is where your program allocates stack memory. In most systems, the default maximum stack size per thread is 8 MB.
If you’re using a Linux or Unix system, you can check this value with the following command:
ulimit -s
The stack memory is used to save the parameters passed to your program, allocate memory for local variables, and store the program’s execution context. One of the main differences between stack memory and heap memory is that the stack is much faster. Since the memory for the stack is reserved by the OS at the start of execution, you don’t need to call the OS every time you allocate something. Instead, your code simply updates the memory address pointed to by the top of the stack and continues execution. This makes the stack ideal for small, short-lived data like local variables, while larger or longer-lived data is allocated in the heap via system calls to the OS.
During program execution, many functions may be called. For example, imagine the following code snippet:
#include <stdio.h>
int sum(int a, int b) {
return a + b;
}
int main() {
int a = 1, b = 3;
int result;
result = sum(a, b);
printf("%d\n", result);
return 0;
}
When you call the sum
function, the CPU must switch the execution context from the main
function to sum
. To do this, the CPU spends cycles preparing to execute the new instructions. Specifically, it must:
- Save the current values of CPU registers in the stack memory.
- Save the memory address of the next instruction (to resume
main
aftersum
returns). - Change the Program Counter (PC) to point to the first instruction of
sum
. - Store the function arguments (depending on the calling convention, this might involve placing them in registers or the stack).
This collection of saved data is called a Stack Frame. Each time a function is called, a new stack frame is created, and when the function finishes, the reverse process occurs, restoring the previous execution context.
Impact on Performance
As described earlier, calling and returning from functions introduces CPU overhead. This becomes more noticeable in scenarios like loops with frequent function calls or deep recursion, where managing the stack frames becomes a significant portion of the workload.
For critical performance scenarios, such as embedded software or game development, C provides tools to minimize this overhead. For instance, you can use macros or the inline
keyword to reduce function call overhead. Here’s an example:
static inline int sum(int a, int b) {
return a + b;
}
Alternatively, you can use a macro:
#define SUM(a, b) ((a) + (b))
While both options avoid the overhead of creating stack frames, inline functions are preferred because they provide type safety, unlike macros, which can introduce subtle bugs (e.g., multiple evaluations of arguments).
It’s important to note that modern compilers are highly optimized and often perform function inlining automatically, especially with optimization flags like -O2
or -O3
. Explicit use of inline
or macros is usually unnecessary unless you’re working in specific contexts like embedded systems, where every cycle counts.
Practical Insights
To illustrate what happens under the hood, you can examine the assembly generated by a simple function call to the sum
function provided at the start of this article. Using objdump
or gdb
, you can see how the CPU manages registers and the stack:
0000000000001149 <sum>:
1149: f3 0f 1e fa endbr64 # Indirect branch protection (may vary by system)
114d: 55 push %rbp # Save base pointer
114e: 48 89 e5 mov %rsp,%rbp # Set new base pointer
1151: 89 7d fc mov %edi,-0x4(%rbp) # Save first argument (a) on the stack
1154: 89 75 f8 mov %esi,-0x8(%rbp) # Save second argument (b) on the stack
1157: 8b 55 fc mov -0x4(%rbp),%edx # Load first argument (a) from the stack
115a: 8b 45 f8 mov -0x8(%rbp),%eax # Load second argument (b) from the stack
115d: 01 d0 add %edx,%eax # Add the two arguments
115f: 5d pop %rbp # Restore base pointer
1160: c3 ret # Return to the caller
Here, you see instructions for setting up and tearing down the stack frame (push
, mov
, pop
) and the actual computation (add
). Each function call adds a similar sequence, contributing to overhead.
When Optimization Matters
CPUs today are capable of performing trillions of operations per second, and in most cases, the performance impact of function calls is negligible. However, in some fields—like embedded systems or computationally intensive applications—these optimizations can be critical. Embedded processors, for instance, often have limited performance and memory, making stack management more expensive. Similarly, optimizing function calls can reduce latency in real-time systems or speed up mathematical computations in resource-intensive simulations.
That said, this article isn’t advocating for sacrificing code readability for performance. Instead, it aims to shed light on what happens under the hood when a program runs.
Top comments (1)
Congrats!!! I loved this content
I am starting to dive into low level programming.
Thank you for your post