Exploiting the AltiVec Unit for Commercial Applications

The introduction of the PowerPC 970 JS20 blade server opens opportunities for vectorizing commercial applications using the integrated AltiVec unit. We examined the vectorization of applications from diverse fields such as XML parsing, UTF-8 encoding, life sciences, string manipulations, and sorting. We obtained performance speedups (over optimized scalar code) for string comparisons (2-3), XML delimiter lookup (1.5-5), and UTF-8 conversion (2-4). The focus of this paper is on the process rather than on the results. Vectorizing commercial applications vastly differs from vectorizing graphic and image processing applications. In addition to the results achieved, we describe the pitfalls encountered, the advantages and disadvantages of the AltiVec unit, and what is missing in its current implementation. Sorting presents an interesting example. Vectorizing the quicksort algorithm was not successful due to low parallelism and misaligned data accesses. Vectorization of the combsort algorithm was very successful, with speedups of 5.0, until the data spilled from the L2 cache. Combining both approaches, by first partitioning the input using quicksort and then continuing with combsort, yielded speedups of over 2.0. This research led to several patent disclosures, many algorithmic enhancements, and an insight into the correct integration of software with the AltiVec unit. The wealth of information collected during this study is being conveyed to the auto-vectorization teams of the relevant compilers.