stdalign


1. Byte-packing structures

struct PackedStruct {
  _Alignas(1) char byte1;
  _Alignas(2) short byte2;
  _Alignas(4) int byte3;
};

This ensures that byte1 is aligned on a 1-byte boundary, byte2 on a 2-byte boundary, and byte3 on a 4-byte boundary, optimizing memory access performance.

2. Hardware alignment requirements

#define SIMD_ALIGNMENT 16

struct SIMDVector {
  _Alignas(SIMD_ALIGNMENT) float vec[4];
};

This ensures that when accessing the vec array, the SIMD instructions are executed efficiently, without causing cache misses or performance penalties.

3. Alignment for performance-critical code

_Alignas(64) char *ptr = malloc(1024);

Aligning memory allocations on a 64-byte boundary can improve performance for memory-intensive operations, such as vector computations or high-speed data transfers.

4. Cross-platform alignment

This ensures that the array arr is aligned on a 16-byte boundary, regardless of the compiler or platform, providing consistent performance.

5. Custom alignment

This aligns the value variable on a boundary that matches the alignment of the long long double data type, ensuring efficient access.

6. Unaligned memory access mitigation

This example copies data from an unaligned memory location to an aligned buffer, allowing efficient access to the data later.

7. Cache-friendly data structures

This aligns the data array on a 64-byte boundary, optimizing cache performance by ensuring that the entire array fits within a single cache line.

8. Vector data alignment

Aligning the vector vec on a 64-byte boundary allows efficient vector operations, such as SIMD calculations or matrix transformations.

9. Multithreaded data sharing

Aligning the shared_var atomic variable on a 64-byte boundary ensures consistent cache behavior across multiple threads, reducing synchronization overhead.

10. SIMD vector optimization

This example aligns the vec array and the pointer vec_ptr on a 16-byte boundary, enabling efficient SIMD operations, such as vector loads and stores.

11. Hardware-specific alignment requirements

This ensures that the array arr is aligned on the appropriate boundary, as specified by the ARM or non-ARM hardware architecture.

12. Aligning function arguments

Aligning the function argument arr on a 16-byte boundary optimizes its passing to the function, reducing the overhead of parameter copying.

13. Structure padding removal

Aligning the s member of AlignedStruct on a boundary that matches the size of the ptr pointer removes unnecessary padding, reducing memory consumption.

14. Memory allocation hints

This allocates memory aligned on a 16-byte boundary, optimizing its use for alignment-sensitive operations.

15. Data parallel operations

The aligned clause ensures that the loop iterations are executed on aligned memory, improving performance for data parallel operations.

16. DMA transfers

Aligning the buf buffer on a 64-byte boundary optimizes Direct Memory Access (DMA) transfers, reducing the overhead of data alignment during data movement.

17. Packed SIMD data

Aligning the packed_data variable on a 32-byte boundary optimizes operations using SSE intrinsics, such as vector additions and multiplications.

18. Memory mapping

This maps memory aligned on the system page size, typically 4096 bytes, optimizing performance for memory-intensive operations.

19. Cache-aware data structures

Aligning the data pointer on a 64-byte boundary optimizes cache performance by ensuring that the data structure fits within a single cache line.

20. Accelerating computations

Aligning the arr array on a 64-byte boundary improves the efficiency of vectorized and parallelized computations, reducing execution time.

21. Efficient pointer arithmetic

Aligning the ptr pointer on a 4-byte boundary ensures that pointer increment and decrement operations align with the underlying data type.

22. Optimized data access

Aligning the arr array on a 16-byte boundary optimizes data access by ensuring that individual elements are accessed on the appropriate alignment boundaries.

23. Reducing memory fragmentation

Aligning the arr array on a 256-byte boundary reduces memory fragmentation by allocating larger chunks of aligned memory, minimizing the overhead of managing small memory blocks.

24. Improved performance for virtualized environments

Aligning the buf buffer on a 4096-byte boundary improves performance in virtualized environments by matching the page size, reducing the overhead of page table translations.

25. Aligning structures in packed memory regions

Aligning the members of PackedStruct on a 16-byte boundary ensures efficient access when the structure is packed into a contiguous memory region.

26. Aligning data for streaming operations

Aligning the data array on a 32-byte boundary optimizes streaming operations, such as network I/O or multimedia data processing, by matching the alignment of streaming buffers.

27. Multi-threading performance optimization

Aligning the shared_value atomic variable on a 32-byte boundary improves performance in multi-threaded environments by reducing the overhead of atomic operations.

28. Aligning matrices for efficient operations

Aligning the matrix array on a 64-byte boundary optimizes linear algebra operations, such as matrix multiplication, by reducing the overhead of accessing individual matrix elements.

29. Reducing cache misses for data structures

Aligning the arr and data members of CacheOptimisedStruct on a 64-byte boundary reduces cache misses when accessing the members together, improving performance.

30. Aligning function pointers

Aligning the function pointer on a 16-byte boundary ensures efficient function calls when passing aligned arguments.

31. Aligning data for efficient vectorization

Aligning the arr array on a 64-byte boundary enables efficient vectorization of operations on the array, improving performance.

32. Ensuring memory alignment for critical sections

Aligning the lock variable on a 16-byte boundary ensures efficient access in critical sections, reducing contention and improving synchronization performance.

33. Optimizing memory access for large data structures