SAIS-OPT: On the characterization and optimization of the SA-IS algorithm for suffix array construction

Abstract

Abstract-The suffix array and Burrows-Wheeler Transform are critical index structures in next generation sequence analysis. The construction of such index structures for mammalian-sized genomes can take thousands of seconds (i.e. tens of minutes). Its construction is complicated by computational overheads that coming from irregular or complex memory-access patterns. This paper rigorously characterizes the execution profile of the SA-IS algorithm in order to guide its optimization. The resulting optimized SA-IS, which we refer to as sais-opt, outperforms previous implementations of SA-IS as well as "best in practice" algorithms, when applied to large DNA strings.

Block-Split Array Coding Algorithm for Long-Stream Data Compression

“…As mentioned above, Com-Zip also keeps up with the optimal algorithms of the 3 classes, but each time we cannot focus on too many points. In [6], we have compared the time complexities of traditional BWT, BWT with SA-IS [11], BWT with GSACA [12], and CZ-BWT, which are current BWT studies.…”

Fast Algorithm of Truncated Burrows-Wheeler Transform Coding for Data Compression of Sensors

“…SA-IS requires special ending symbol for the block and recursive reduction to a shorter string [2,13], which are more complex than CZ-BWT. SA-IS needs to scan the BWT block for more than 3 times, while according to Algorithm 1, CZ-BWT encoding just scan the block twice in phases 1 and 2.…”

“…Quite a few recent advancements of BWT algorithms are driven by the rapid development of genome information technologies [2,3,13,18], and there are many DNA softwares using BWT, including DNA compression, alignment, sequencing, and indexing. Due to the difference between the DNA and common data charsets, we cannot proceed direct experiments to compare a DNA software such as BWA (Burrows-Wheeler aligner) with a universal compression software such as ComZip or bzip2, but we can analyze their BWT algorithms to investigate their advantages and shortcomings.…”

“…Considering the large BWT block for the big data, the memory requirement of the SA construction is many times of the block. Meanwhile, if we try to design a hardware BWT filter for the sensors, we will meet the complexity of the algorithms such as the recursive computation in SA-IS [13]. GSACA is nonrecursive, but currently, it is slower than SA-IS, and its memory consumption is quite large [14], which are weaknesses for the limited computing resources of the sensors.…”

“…Among them, SA-IS is currently the best algorithm in the speed. Moreover, the further optimization of SA-IS algorithm is studied [13], and the first linear nonrecursive algorithm named GSACA is a new approach for the future [14].…”