Understanding std::hardware_destructive_interference_size and std::hardware_constructive_interference_size
Introduction
In C 17, the addition of std::hardware_destructive_interference_size and std::hardware_constructive_interference_size provides a portable way to optimize memory access and avoid performance pitfalls.
Relationship to L1 Cache Line Size
These constants are typically related to the L1 cache line size, which is the minimum unit of data that is transferred between the CPU and cache. By aligning and organizing data structures according to these sizes, we can avoid conflicts and improve performance.
Use Cases
Challenges with Static Constants
These constants are defined as static constexpr, which means they are evaluated at compile time. However, this introduces a challenge: the computed values may not align perfectly with the cache line size of the target machine at runtime.
Workarounds
To address this, we can define our own constant values based on known system characteristics if available. Alternatively, we can use platform-specific hints or libraries that detect the cache line size dynamically.
Example
The following code shows a simple example that demonstrates how these constants can be used:
#include <iostream> using namespace std; int main() { // Assuming hardware_destructive_interference_size and hardware_constructive_interference_size are defined int x1[hardware_destructive_interference_size]; // Avoid false sharing int x2[hardware_destructive_interference_size / 2]; // Potential false sharing int y1[hardware_constructive_interference_size]; // Promote true sharing pair<int, int> y2; // Potential true sharing // Use these arrays to store data and observe the performance difference due to alignment issues return 0; }
Conclusion
std::hardware_destructive_interference_size and std::hardware_constructive_interference_size provide a valuable tool for optimizing memory access and avoiding cache line conflicts. However, it is important to be aware of the challenges associated with static constants and consider appropriate workarounds to ensure optimal performance on different platforms.
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