Beating the L1 cache with value speculation (2021)
7 days ago
- #Branch Prediction
- #CPU Optimization
- #Performance Tuning
- Value speculation leverages the branch predictor to guess values, removing data dependencies and increasing CPU instruction parallelism.
- The bottleneck in processing linked lists is often due to L1 cache hits introducing unwanted data dependencies, not misses.
- A trick to improve performance involves guessing the next node in a contiguous memory block and correcting if wrong, exploiting branch prediction.
- Modern CPUs use branch prediction and caching to execute instructions in parallel, but dependencies can limit this parallelism.
- Performance improvements vary with dataset size, showing significant gains when data fits entirely in CPU caches.
- Compiler optimizations can undo human-introduced performance tricks, requiring careful coding to preserve them.
- Manual assembly optimization can further improve performance by reducing the number of instructions per loop iteration.
- The final optimized function achieves near-peak performance by minimizing cache dependency and maximizing instruction-level parallelism.