# Adapting the GACT-X Aligner to Accelerate Minimap2 in an FPGA Cloud Instance
## 5 Conclusions  
This work has proposed a hybrid software-hardware implementation to accelerate Minimap2's extending step on a cloud FPGA design. The limitations in the face of the challenges in implementing memory-based and communication-intensive algorithms on cloud FPGAs have been identified. The hardware aligner GACT-X was adapted to substitute for Minimap2's SK software long-read alignment algorithm and was integrated into the Minimap2 assembler. In order to have reliable and robust benchmarking, three different read datasets (one simulated and two real) were used and validated through Minimap2's execution and profiling. The results have shown that varied long-read patterns were available as input, in addition to certifying that the extending step consists of a bottleneck in Minimap2 data processing. GACT-X was hosted on an AWS f1.2 xlarge instance FPGA cloud for a series of tests with the three datasets. The tests have aimed to optimize the implementation under the long-read alignment environment for increased performance. The tests have shown 4000 bases as the best tile length to be adopted. The results with this GACT-X stand-aloneversion have shown that GACT-X can be up to 1.91\(\times\) faster than SK from Minimap2, including the data transfer time with the FPGA's DRAM. The GACT-X implementation was also compared to Minimap2's ksw function, which performs the SK algorithm. GACT-X's alignment accuracy was close to Minimap2's in two datasets, and worse than Minimap2's on one real dataset that also presented a high rate of unmapped reads. GACT-X was fully integrated into Minimap2 in an f1.2 xlarge instance and executed on combinations with one to two FPGA kernels and one to eight software threads. The results were presented regarding the processing speed and acceleration in comparison to those of Minimap2 in software. The integrated system achieved the highest speed-up of 1.41\(\times\) over Minimap2's software performance. The data transfer delays were measured and, for multiple concurrent threads and two kernels, a dispute for the PCIe channel was reported in the observations. GACT-X's performance in AWS was consistent with what was reported in earlier works on FPGA clouds regarding communication-intensive applications. Additionally, the results on data transfer delays with GACT-X allowed for the identification of bottlenecks in the tile processing, revealing new hardware design strategies for further acceleration in future work. These actions, added to the previously proposed hardware acceleration for the chaining step, may lead to a sturdy FPGA cloud Minimap2. Conceptualization, C.T., R.W.A. and J.C.W. ; methodology, C.T. and J.C.W. ; software, C.T. and R.W.A. ; validation, J.C.W. and F.J.F. ; formal analysis, C.T. and R.W.A. ; investigation, C.T. and R.W.A. ; resources, C.T. and J.C.W. ; data curation, C.T. and R.W.A. ; writing--original draft preparation, C.T. and J.C.W. ; writing--review and editing, C.T., J.C.W. and F.J.F. ; visualization, C.T. ; supervision, J.C.W. and F.J.F. ; project administration, J.C.W. and F.J.F. ; funding acquisition, C.T., J.C.W. and F.J.F. All authors have read and agreed to the published version of the manuscript. This research was partially supported by the National Council for Scientific and Technological Development with grant number 133892/2020-4. The APC was disbursed by the Coordination of Superior Level Staff Improvement and by the University of Sao Paulo. Patient consent was waived due to their data being collected from public repositories. Publicly available datasets were analyzed in this study. These data can be found here: [33; 34; 36; 38]. The original programs used in this study can be found here: [42; 44]. The adapted code presented in this study is available at [46]. The authors express their gratitude to [PERSON] from the Institute of Biomedical Sciences at University of Sao Paulo for granting access to the Bioinformatics Seal server used in this work. The authors declare no conflict of interest.