NDLI: The unified accelerator architecture for RNA secondary structure prediction on FPGA

Content Provider	Springer Nature Link
Author	Xia, Fei Dou, Yong Jin, Guoqing
Copyright Year	2011
Abstract	In the field of RNA secondary structure prediction, MFE, SCFG and the homologous comparative sequence analysis are three kinds of classical computation analysis approaches. However, the parallel efficiency of many implementations on general-purpose computers are greatly limited by complicated data dependency and tight synchronization. Additionally, large scale parallel computers are too expensive to be used easily for many research institutes. Recently, FPGA chips provide a new approach to accelerate those algorithms by exploiting fine-grained custom design. We propose a unified parallelism schemes and logic circuit architecture for three classical algorithms—Zuker, RNAalifold and CYK, based on a systolic-like master-slave PE (Processing Element) array for fine-grained hardware implementation on FPGA. We partition tasks by columns and assign them to PEs for load balance. We exploit data reuse schemes to reduce the need to load matrix from external memory. The experimental results show a factor of 12–14× speedup over the three software versions running on a PC platform with AMD Phenom 9650 Quad CPU. The computational power of our prototype is comparable to a PC cluster consisting of 20 Intel-Xeon CPUs for RNA secondary structure prediction; however, the power consumption is only about 10% of the latter.
Starting Page	826
Ending Page	855
Page Count	30
File Format	PDF
ISSN	09208542
Journal	The Journal of Supercomputing
Volume Number	61
Issue Number	3
e-ISSN	15730484
Language	English
Publisher	Springer US
Publisher Date	2011-10-14
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Bioinformatics RNA secondary structure prediction Fine-grained parallelism FPGA Hardware accelerator Computer Science Programming Languages, Compilers, Interpreters Processor Architectures
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Information Systems Hardware and Architecture Software

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