NDLI: 3D-stacked many-core architecture for biological sequence analysis problems

Content Provider	IEEE Xplore Digital Library
Author	Pei Liu Hemani, A. Paul, K.
Copyright Year	2015
Description	Author affiliation: Dept. of Electron. Syst., KTH R. Inst. of Technol., Stockholm, Sweden (Pei Liu; Hemani, A.) \|\| Dept. of Comput. Sci. & Eng., Indian Inst. of Technol., New Delhi, New Delhi, India (Paul, K.)
Abstract	Sequence analysis plays critical role in bioinformatics, and most applications of which have compute intensive kernels consuming over 70% of total execution time. By exploiting the compute intensive execution stages of popular sequence analysis applications, we present and evaluate a VLSI architecture with a focus on those that target at biological sequences directly, including pairwise alignment, multiple sequence alignment, database search, and short read sequence mappings. Based on coarse grained reconfigurable array (CGRA) we propose the use of many-core and 3D-stacked technologies to gain further improvement over memory subsystem, which gives another order of magnitude speedup from high bandwidth and low access latency. We analyze our approach in terms of its throughput and efficiency for different application mappings. Initial experimental results are evaluated from a stripped down implementation in a commodity FPGA, and then we scale the results to estimate the performance of our architecture with 9 layers of 68 mm2 stacked wafers in 45-nm process. We demonstrate numerous estimated speedups better than any existed hardware accelerators for at least 39 times for the entire range of applications and datasets of interest. In comparison, the alternative FPGA based accelerators deliver only improvement for single application, while GPGPUs perform not well enough on accelerating program kernel with random memory access and integer addition/comparison operations.
Starting Page	211
Ending Page	220
File Size	1560381
Page Count	10
File Format	PDF
ISBN	9781467373111
DOI	10.1109/SAMOS.2015.7363678
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-19
Publisher Place	Greece
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sequences Computational modeling Biology Application specific integrated circuits Databases Accelerator architectures Computer architecture Reconfigurable architectures Bioinformatics Kernel Three-dimensional integrated circuits Computational biology Coprocessors
Content Type	Text
Resource Type	Article

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