GCC Memcpy Optimization: Force a Direct Call Under -Os

How Did We Discover the Need to Override GCC Optimization in Firmware?

During a recent project for an industrial IoT provider, we were tasked with optimizing the firmware for a fleet of x86-64 edge computing gateways. These gateways processed high-throughput sensor telemetry. Because the devices had extremely constrained flash storage, our build pipelines compiled the entire firmware stack using the GCC -Os flag to optimize for binary size.

While profiling the data routing module, we realized that memory operations were consuming an unusually high number of CPU cycles. The ingestion engine was struggling to maintain throughput during peak sensor bursts. Upon disassembling the hot paths, we found that GCC, strictly adhering to the -Os directive, was inlining standard memcpy operations into rep movsb instructions.

While rep movsb uses very few bytes of instruction cache (achieving the goal of a smaller binary), it performed poorly on this specific microarchitecture for medium-sized memory copies. We needed the system to execute a direct call to the highly optimized, vectorized memcpy provided by our standard library, but we could not afford to drop the -Os flag globally. This challenge inspired the following deep dive into overriding compiler behaviors locally—a scenario that underscores why tech leaders must hire software developer teams capable of navigating the lowest levels of system architecture.

Why Does GCC Inline Memcpy Under Size Optimization?

To understand the root cause, we must look at how compilers interpret optimization directives. When you compile with -O2 or -O3, GCC prioritizes execution speed. It might unroll loops, auto-vectorize code or link against optimized built-in functions. However, when you use -Os, the primary mandate is minimizing the compiled binary size.

On x86-64 architectures, calling an external function requires setting up the Application Binary Interface (ABI). To call memcpy, the compiler must move variables into the rdi, rsi and rdx registers and then issue a call instruction. This sequence consumes significant byte space.

Conversely, the rep movsb instruction is highly compact. It relies on the rcx, rdi and rsi registers to perform byte-by-byte copying directly in hardware. By utilizing this built-in sequence, GCC saves instruction bytes, faithfully executing the -Os mandate. The architectural trade-off, however, is that for certain data sizes, the CPU microcode overhead for initiating rep movsb drastically degrades raw throughput.

What Performance Bottlenecks Occurred with REP MOVSB?

In our edge gateway architecture, the payload sizes varied consistently between 256 bytes and 1 kilobyte. The symptoms of our bottleneck surfaced during load testing:

• High CPU Utilization: The core handling telemetry packet parsing was pegging at 100%, causing queue backups in the networking layer.
• Microcode Startup Overhead: While modern x86 processors have optimized “Fast String” operations (ERMS – Enhanced REP MOVSB), the startup cost of the instruction for sub-kilobyte copies negated any hardware-level advantages.
• Cache Miss Amplification: The slower memory copy loops kept data in L1/L2 caches longer, causing evictions of other critical routing tables.

We verified through perf and objdump that replacing rep movsb with a direct call to an SSE/AVX optimized memcpy reduced the CPU time spent in that function by over 40%. The challenge was enforcing this without increasing the footprint of the rest of the binary.

How Did We Evaluate Local Overrides for GCC Builtins?

To fix the issue, we needed a strictly local solution. The engineering team explored several approaches. When enterprises hire C/C++ developers for system programming, evaluating these architectural trade-offs systematically is a critical requirement.

Could We Use Global Compiler Flags?

The most straightforward fix is passing -fno-builtin-memcpy to GCC. However, applying this globally meant the compiler would stop inlining memcpy everywhere in the project. This led to an unacceptable 12% increase in the overall firmware binary size, pushing us past our strict flash memory limits. The solution had to be isolated to a single C file or function.

Did a Volatile Function Pointer Work?

We attempted to obscure the function call from the compiler’s optimizer by casting memcpy through a volatile pointer:

void *(*volatile volatile_memcpy)(void *, const void *, size_t) = memcpy;
volatile_memcpy(dest, src, len);

While this successfully prevented the compiler from generating rep movsb, it introduced a new problem. It forced an indirect call (e.g., call *%rax). Indirect branches are harder for the CPU to predict, potentially causing branch prediction stalls. We specifically needed a direct call.

What About GCC Pragma Directives?

GCC supports localized optimization directives using pragmas:

#pragma GCC push_options
#pragma GCC optimize ("-fno-builtin-memcpy")
// our code
#pragma GCC pop_options

This approach was valid, but pragmas can sometimes behave inconsistently across different versions of GCC, especially older cross-compilation toolchains common in embedded environments. It also felt slightly heavy-handed for a single function call.

Could We Use an Assembly Alias?

The most elegant and localized solution involved tricking the compiler’s front-end while relying on the assembler to resolve the symbol correctly. By declaring a local prototype that maps to the memcpy assembly symbol, we could bypass GCC’s built-in recognition entirely.

How Do You Force a Direct Memcpy Call Locally in C?

After evaluating the trade-offs, we implemented the assembly alias technique. This approach guarantees a direct function call (call memcpy) without altering global compiler flags or relying on potentially brittle pragmas. It is an excellent pattern utilized by teams when they hire developers for performance-critical low-level engineering.

Here is the technical implementation we integrated into the telemetry router:

#include <stddef.h>
#include <stdint.h>
// 1. Declare a local function prototype that bypasses GCC's builtin detection
// but maps directly to the external 'memcpy' symbol in assembly.
void *direct_memcpy(void *dest, const void *src, size_t n) __asm__("memcpy");
void process_telemetry_payload(uint8_t *destination, const uint8_t *payload, size_t len) {
    // 2. The compiler sees 'direct_memcpy', so it does not apply builtin 
    // optimizations (like inlining to rep movsb). 
    // 3. The assembler links this directly to 'memcpy', generating a direct call.
    direct_memcpy(destination, payload, len);
}

Validation Steps:

We validated the resulting object file using objdump -d. Instead of the compact but slow inline string operations, the disassembly confirmed standard ABI preparation followed by a direct call <memcpy@plt>. Performance tests confirmed the CPU spikes were eliminated, restoring throughput entirely.

What Are the Key Takeaways for Systems Engineering Teams?

This issue highlights several core truths about systems architecture and compiler behaviors:

• Understand Your Compiler’s Mandate: Flags like -Os execute their primary goal ruthlessly. If you tell the compiler to prioritize size, it will sacrifice speed to do so.
• Profile Before Assuming: The assumption that “hardware instructions are faster” is frequently false. rep movsb is optimal for size, but only optimal for speed on very specific microarchitectures and payload sizes.
• Avoid Global Fixes for Local Problems: Applying -fno-builtin globally would have solved the CPU issue but broken our deployment constraints. Always strive to isolate overrides to the specific hot paths.
• Know the Toolchain Tooling: Techniques like assembly aliasing (__asm__("symbol")) empower developers to exert precise control over compilation without writing raw inline assembly blocks.
• Validate with Disassembly: High-level C code rarely tells the whole story. Teams must routinely inspect the generated machine code to verify that optimization assumptions hold true.

How Can Teams Balance Optimization and Performance?

When working at the boundaries of hardware capabilities, relying solely on default compiler flags can lead to unexpected system degradation. The ability to surgically bypass optimizations—such as forcing a direct call to memcpy over an inline expansion—requires deep knowledge of compiler toolchains, CPU instruction sets and binary analysis.

If your organization is building mission-critical embedded systems, edge infrastructure or high-throughput platforms, bringing in the right expertise is paramount. Whether you need to hire embedded engineers for performance tuning or augment your existing architecture teams, having developers who understand what happens after the code compiles is the difference between a functional system and a robust one. To learn more about how we structure highly capable engineering teams for our global clients, contact us.

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