S.: Mighty-morphing powerSIMD

In modern wireless devices, two broad classes of compute-intensive applications are common: those with high amounts of data-level parallelism, such as signal processing used in wireless baseband applications, and those that have little data-level parallelism, such as encryption. Wide single-instruction multiple-data (SIMD) pro-cessors have become popular for providing high performance, yet power efficient data engines for applications with abundant data parallelism. However, the non-data-parallel applications are rele-gated to a low-performance scalar datapath on these data engines while the SIMD resources are left idle. To accelerate both types of applications, we propose the design of a more flexible SIMD datapath called SIMD-Morph. In SIMD-Morph, code with data-level parallelism can be executed across the lanes in the traditional manner, but the lanes can be morphed into a feed-forward sub-graph accelerator to execute scalar applications more efficiently. The morphed SIMD lanes form an accelerator that exploits both instruction-level parallelism as well as operation chaining to im-prove the performance of scalar code by exploiting the available resources in the SIMD lanes. Experimental results show that the performance impact is a 2.6X improvement for purely non-SIMD applications and a 1.4X improvement for the non-SIMD-ized por-tions of applications with data parallelism