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) processors 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 relegated 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 datalevel parallelism can be executed across the lanes in the traditional manner, but the lanes can be morphed into a feed-forward subgraph 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 improve 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 portions of applications with data parallelism.  Categories and Subject Descriptors Design, Performance Operation chaining, SIMD processing, Data-level parallelism, Instruction-level Parallelism Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.
The SIMD-Morph REF architecture uses transition modes to exploit both DLP and ILP.
Mighty-morphing power-SIMD
CASES '10
Computer Science