Vector architectures have been traditionally applied to the supercomputing domain with many successful incarnations. The energy efficiency and high performance of vector processors, as well as their applicability in other emerging domains, encourage pursuing further research on vector architectures. However, there is a lack of appropriate tools to perform this research. This paper presents two tools for measuring and analyzing an application's suitability for vector microarchitectures. The first tool is VALib, a library that enables hand-crafted vectorization of applications and its main purpose is to collect data for detailed instruction level characterization and to generate input traces for the second tool. The second tool is SimpleVector, a fast trace-driven simulator that is used to estimate the execution time of a vectorized application on a candidate vector microarchitecture. The potential of the tools is demonstrated using six applications from emerging application domains such as speech and face recognition, video encoding, bioinformatics, machine learning and graph search. The results indicate that 63.2% to 91.1% of these contemporary applications are vectorizable. Then, over multiple use cases, we demonstrate that the tools can facilitate rapid evaluation of various vector architecture designs.

The research leading to these results has received funding from the European Research Council under the European Union's 7th FP (FP/2007-2013) / ERC GA n. 321253. It has been partially funded by the Spanish Government (TIN2012-34557).

Peer Reviewed