The evaluation of small degree polynomials is critical for the computation of elementary functions. It has been extensively studied and is well documented. In this article, we evaluate existing methods for polynomial evaluation on superscalar architecture. In addition, we have completed this work with a factorization method, which is surprisingly neglected in the literature. This work focuses on out-of-order Intel processors, amongst others, of which computational units are available. Moreover, we applied our work on the elementary function e x that requires, in the current implementation, an evaluation of a polynomial of degree 10 for a satisfying precision and performance. Our results show that the factorization scheme is the fastest in benchmarks, and that latency and throughput are intrinsically dependent on each other on superscalar architecture.

中文翻译：

---

超标量架构的多项式评估，应用于初等函数 ex

小次多项式的评估对于基本函数的计算至关重要。它已被广泛研究并有据可查。在本文中，我们评估了现有的超标量架构多项式评估方法。此外，我们使用因式分解方法完成了这项工作，这在文献中令人惊讶地被忽略了。这项工作的重点是无序的英特尔处理器，其中计算单元可用。此外，我们将我们的工作应用于基本函数e X 在当前的实现中，这需要对 10 次多项式进行评估，以获得令人满意的精度和性能。我们的结果表明，分解方案是基准测试中最快的，并且延迟和吞吐量在超标量架构上本质上是相互依赖的。