an integrated simdization framework using virtual vectors
Automatic simdization for multimedia extensions faces several new challenges that are not present in traditional vectorization. Some of the new issues are due to the more restrictive SIMD architectures designed for multimedia extensions. Among them are alignment constraints, lack of memory gather and scatter support, and the short and fixed-length nature of SIMD vectors. Since these constraints affect some very basic components of a program, a compiler must not only provide solid solutions to individual issues, but also take an integrated approach to address these constraints in combination.In this paper, we propose a simdization framework that addresses several orthogonal aspects of simdization, such as alignment handling, simdization of loops with mixed data lengths, and SIMD parallelism extraction from different program scopes (from basic blocks to inner loops). The novelty of this framework is its ability to facilitate interactions between different techniques based on the simple intermediate representation of virtual vectors. Measurements on a PPC970 with a VMX SIMD unit indicate speedup factors of up to 8.11 for numerical/video/communication kernels and speedup factors of up to 2.16 for benchmarks, when automatic simdization is turned on.
integrability virtualization vectorization multimedia extensibility challenge architecture aligning constraint memorialized support affect component compilation addressing combinational paper aspect data parallel extraction novelty interaction representation measurement speedup factor video communication kernel benchmark  framework 