How Can SIMD Instructions Optimize Parallel Prefix Sum on Intel CPUs?

SIMD-Based Parallel Prefix Sum on Intel CPUs

Introduction

Prefix sum algorithms are essential for various data processing and parallel computing applications, and performance optimization is crucial. This article explores a highly efficient parallel prefix sum implementation leveraging Intel CPUs' SIMD (Single Instruction Multiple Data) capabilities.

The SIMD Approach

The traditional prefix sum algorithm involves iteratively adding elements in an array. To accelerate this process, we leverage SSE (Streaming SIMD Extensions) SIMD instructions to perform parallel addition of vectorized elements.

Two-Phase Algorithm with SIMD Optimization

The proposed algorithm consists of two phases:

• Phase 1:

  • Split the array into chunks and assign them to multiple threads.
  • Each thread performs parallel prefix sum on its chunk using SSE.
  • The total sum for each chunk is stored.

• Phase 2:

  • Again, use multiple threads.
  • Each thread iterates over its assigned chunk and adds the corresponding total sum from Phase 1 to each element.
  • The final prefix sum is obtained.

CUDA Implementation

The provided code demonstrates the implementation of this algorithm using OpenMP and SSE intrinsics. It includes two functions: scan_SSE() for SIMD prefix sum on 4-element vectors and scan_omp_SSEp2_SSEp1_chunk() for the overall parallel prefix sum.

Performance Enhancement with Caching Considerations

For large array sizes, caching can significantly impact performance. To mitigate this, the algorithm incorporates a chunk-based approach, where the prefix sum within each chunk is performed serially while the overall process remains parallel. This keeps data within the CPU cache, enhancing speed.

Conclusion

The SIMD-based parallel prefix sum algorithm presented in this article provides a highly optimized implementation for Intel CPUs. Its two-phase approach with SIMD optimization and caching considerations ensure efficient prefix sum computation for large datasets.

The above is the detailed content of How Can SIMD Instructions Optimize Parallel Prefix Sum on Intel CPUs?. For more information, please follow other related articles on the PHP Chinese website!