Performance analysis of the Kahan-enhanced scalar product on current multi- and manycore processors

SUMMARY We investigate the performance characteristics of a numerically enhanced scalar product (dot) kernel loop that uses the Kahan algorithm to compensate for numerical errors, and describe efficient SIMD-vectorized implementations on recent multi-and manycore processors. Using low-level instruction analysis and the execution-cache-memory (ECM) performance model we pinpoint the relevant performance bottlenecks for single-core and thread-parallel execution, and predict performance and saturation behavior. We show that the Kahan-enhanced scalar product comes at almost no additional cost compared to the naive (non-Kahan) scalar product if appropriate low-level optimizations, notably SIMD vectorization and unrolling, are applied. The ECM model is extended appropriately to accommodate not only modern Intel multicore chips but also the Intel Xeon Phi " Knights Corner " coprocessor and an IBM POWER8 CPU. This allows us to discuss the impact of processor features on the performance across four modern architectures that are relevant for high performance computing.