AlignS: A Processing-In-Memory Accelerator for DNA Short Read Alignment Leveraging SOT-MRAM
Classified as a complex big data analytics problem, DNA short read alignment serves as a major sequential bottleneck to massive amounts of data generated by next-generation sequencing platforms. With Von-Neumann computing architectures struggling to address such computationally-expensive and memory-...
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| Published in: | Proceedings of the 56th Annual Design Automation Conference 2019 pp. 1 - 6 |
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| Format: | Conference Proceeding |
| Language: | English |
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01.06.2019
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| Abstract | Classified as a complex big data analytics problem, DNA short read alignment serves as a major sequential bottleneck to massive amounts of data generated by next-generation sequencing platforms. With Von-Neumann computing architectures struggling to address such computationally-expensive and memory-intensive task today, Processing-in-Memory (PIM) platforms are gaining growing interests. In this paper, an energy-efficient and parallel PIM accelerator (AlignS) is proposed to execute DNA short read alignment based on an optimized and hardware-friendly alignment algorithm. We first develop AlignS's platform that harnesses SOT-MRAM as computational memory and transforms it to a fundamental processing unit for short read alignment. Accordingly, we present a novel, customized, highly parallel read alignment algorithm that only seeks the proposed simple and parallel in-memory operations (i.e. comparisons and additions). AlignS is then optimized through a new correlated data partitioning and mapping methodology that allows local storage and processing of DNA sequence to fully exploit the algorithm-level's parallelism, and to accelerate both exact and inexact matches. The device-to-architecture co-simulation results show that AlignS improves the short read alignment throughput per Watt per mm 2 by ~12× compared to the ASIC accelerator. Compared to recent FM-index-based ReRAM platform, AlignS achieves 1.6× higher throughput per Watt. |
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| AbstractList | Classified as a complex big data analytics problem, DNA short read alignment serves as a major sequential bottleneck to massive amounts of data generated by next-generation sequencing platforms. With Von-Neumann computing architectures struggling to address such computationally-expensive and memory-intensive task today, Processing-in-Memory (PIM) platforms are gaining growing interests. In this paper, an energy-efficient and parallel PIM accelerator (AlignS) is proposed to execute DNA short read alignment based on an optimized and hardware-friendly alignment algorithm. We first develop AlignS's platform that harnesses SOT-MRAM as computational memory and transforms it to a fundamental processing unit for short read alignment. Accordingly, we present a novel, customized, highly parallel read alignment algorithm that only seeks the proposed simple and parallel in-memory operations (i.e. comparisons and additions). AlignS is then optimized through a new correlated data partitioning and mapping methodology that allows local storage and processing of DNA sequence to fully exploit the algorithm-level's parallelism, and to accelerate both exact and inexact matches. The device-to-architecture co-simulation results show that AlignS improves the short read alignment throughput per Watt per mm 2 by ~12× compared to the ASIC accelerator. Compared to recent FM-index-based ReRAM platform, AlignS achieves 1.6× higher throughput per Watt. |
| Author | Angizi, Shaahin Fan, Deliang Zhang, Wei Sun, Jiao |
| Author_xml | – sequence: 1 givenname: Shaahin surname: Angizi fullname: Angizi, Shaahin organization: Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, 32816 – sequence: 2 givenname: Jiao surname: Sun fullname: Sun, Jiao organization: Department of Computer Science, University of Central Florida, Orlando, FL, 32816 – sequence: 3 givenname: Wei surname: Zhang fullname: Zhang, Wei organization: Department of Computer Science, University of Central Florida, Orlando, FL, 32816 – sequence: 4 givenname: Deliang surname: Fan fullname: Fan, Deliang organization: Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, 32816 |
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| SubjectTerms | Bioinformatics Computer architecture DNA Genomics Magnetic tunneling Micromechanical devices Sequential analysis |
| Title | AlignS: A Processing-In-Memory Accelerator for DNA Short Read Alignment Leveraging SOT-MRAM |
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