Name
Abstract | ||
|---|---|---|
Sequence alignment is a core component of many biological applications. As the advancement in sequencing technologies produces a tremendous amount of data on an hourly basis, this alignment is becoming the critical bottleneck in bioinformatics analysis. Even though large clusters and highly-parallel processing nodes can carry out sequence alignment, in addition to the exacerbated power consumption, they cannot afford to concurrently process the massive amount of data generated by sequencing machines. In this paper, we propose a novel processing in-memory (PIM) architecture suited for DNA sequence alignment, called RAPID. We revise the state-of-the-art alignment algorithm to make it compatible with in-memory parallel computations, and process DNA data completely inside memory without requiring additional processing units. The main advantage of RAPID over the other alignment accelerators is a dramatic reduction in internal data movement while maintaining a remarkable degree of parallelism provided by PIM. The proposed architecture is also highly scalable, facilitating precise alignment of lengthy sequences. We evaluated the efficiency of the proposed architecture by aligning chromosome sequences from human and chimpanzee genomes. The results show that RAPID is at least 2× faster and 7× more power efficient than BioSEAL, the best DNA sequence alignment accelerator. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ISLPED.2019.8824830 | 2019 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED) |
Keywords | Field | DocType |
ReRAM processing in-memory architecture,sequencing technologies,sequencing machines,in-memory parallel computations,process DNA data,DNA sequence alignment accelerator,RAPID,data movement,chromosome sequences,bioinformatics,parallel processing nodes,chimpanzee genomes,human genomes,parallelism | Sequence alignment,Bottleneck,Degree of parallelism,Computer science,Parallel computing,Real-time computing,Memory architecture,Scalability,Computation,Resistive random-access memory,Power consumption | Conference |
ISBN | Citations | PageRank |
978-1-7281-2955-6 | 6 | 0.42 |
References | Authors | |
17 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Saransh Gupta | 1 | 101 | 11.58 |
| Mohsen Imani | 2 | 341 | 48.13 |
| Behnam Khaleghi | 3 | 91 | 13.49 |
| Venkatesh Kumar | 4 | 6 | 0.42 |
| Tajana Simunic | 5 | 3198 | 266.23 |