Abstract
In this chapter we discuss the related work, where we present some of the ideas and implementations reported by other researchers working in areas closely related to this field. First we describe the various accelerator architectures and then, discuss FPGA based accelerators. We describe the FPGA architecture as well as the EDA tool flow followed while exploring HEBs in FPGAs. We discuss “bioinformatics” domain and the two important applications belonging to this domain. We show how these applications have benefited by FPGA-based acceleration.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ahmed, E., Rose, J.: The effect of LUT and cluster size on deep-submicron FPGA performance and density. IEEE Trans. Very Large Scale Integr. VLSI Syst. 12(3), 288–298 (2004)
Alpha-Data: Alpha-Data FPGA Boards. http://www.alpha-data.com/ (2015)
ALTERA: Altera dsps. http://www.altera.com/technology/dsp/dsp-index.jsp (2015)
Altera: Altera FPGAs. http://www.altera.com (2015)
ALTERA: Altera mrams. http://www.altera.com/technology/memory/embedded/mem-embedded.html (2015)
Altschul, S.F., Madden, T.L., Schffer, A.A., Zhang, J., Zhang, Z., Miller, W., Lipman, D.J.: Gapped blast and psiblast: a new generation of protein database search programs. Nucleic Acids Res. 25(17), 3389–3402 (1997)
Bajaj, C., Chowdhury, R., Siddavanahalli, V.: F2Dock: fast Fourier protein-protein docking. IEEE/ACM Trans. Comput. Biol. Bioinform. 8(1), 45–58 (2011)
Baker, M.: Next generation sequencing: adjusting to data overload. Nat. Methods 495–499 (2010)
Beauchamp, M.J., Hauck, S., Underwood, K.D., Hemmert, K.S.: Embedded floating-point units in FPGAs. In: ACM/SIGDA International Symposium on FPGAs (2006)
Bharat, S., Herbordt, M.C.: GPU acceleration of a production molecular docking code. In: GPGPU (2009)
Boisvert, S., Laviolette, F., Corbeil, J.: Simultaneous assembly of reads from a mix of high-throughput sequencing technologies. J. Comput. Biol. 17(11), 1519–1533 (2010)
Bradnam, K.R., Fass, J.N., Alexandrov, A., Baranay, P., et al.: Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species. GigaSci. 2(1) (2013)
Brown, S., Rose, J.: Architecture of FPGAs and CPLDs: a tutorial. IEEE Des. Test Comput. 13, 42–57 (1996)
Butler, J., MacCallum, I., Kleber, M., Shlyakhter, I.A., Belmonte, M.K., Lander, E.S., Nusbaum, C., Jaffe, D.B.: ALLPATHS: de novo assembly of whole-genome shotgun microreads. Genome Res. 18(5), 810–820 (2008)
CADENCE: Tensilica customizable processors. http://ip.cadence.com/ipportfolio/tensilica-ip (2015)
Che, S., Li, J., Sheaffer, J., Skadron, K., Lach, J.: Accelerating compute-intensive applications with gpus and fpgas. In: Symposium on Application Specific Processors, 2008. SASP 2008 (2008)
Chen, R., Li, L., Weng, Z.: ZDOCK: an initial-stage protein-docking algorithm. Proteins 52(1), 80–87 (2003)
Chen, Y., Souaiaia, T., Chen, T.: PerM: efficient mapping of short sequencing reads with periodic full sensitive spaced seeds. Bioinformatics 25(19), 2514–2521 (2009)
Chikhi, R.: Monument assembler. http://www.irisa.fr/symbiose/people/rchikhi/monument.html (2015)
Chikhi, R., Rizk, G.: Space-Efficient and Exact de Bruijn Graph Representation Based on a Bloom Filter. In: Raphael, B., Tang, J. (eds.) Algorithms in Bioinformatics. Lecture Notes in Computer Science, vol. 7534, pp. 236–248. Springer, Berlin Heidelberg (2012)
Chong, Y.J., Parameswaran, S.: Flexible multi-mode embedded floating-point unit for field programmable gate arrays. In: ACM/SIGDA International Symposium on FPGAs (2009)
Chung, E., Milder, P., Hoe, J., Mai, K.: Single-chip heterogeneous computing: does the future include custom logic, FPGAs, and GPGPUs? In: Annual IEEE/ACM International Symposium on Microarchitecture (MICRO) (2010)
Cohen, J.: Bioinformatics an introduction for computer scientists. ACM Comput. Surv. 36, 122–158 (2004)
Cohen, J.: Computer science and bioinformatics. Commun. ACM 48, 72–78 (2005)
Convey Computer: Convey GraphConstructor. http://www.conveycomputer.com (2015)
David, Ritchie, W., Ritchie, D.: Hex 6.0 user manual protein docking using spherical polar fourier correlations
Devadoss, R., Paul, K., Balakrishnan, M.: p-qca: a tiled programmable fabric architecture using molecular quantum-dot cellular automata. J. Emerg. Technol. Comput. Syst. 7(3), 13:1–13:20 (2011)
El-Ghazawi, T., George, A.D., Gonzalez, I., Lam, H., Merchant, S., Saha, P., Smith, M., Stitt, G., Alam, N., El-Araby, E., Holland, B., Reardon, C.: Exploration of a Research Roadmap for Application Development and Execution on Field-Programmable Gate Array (FPGA)-Based Systems. Technical Report, Defense Technical Information Center (2008)
Fernandez, E., Najjar, W., Harris, E., Lonardi, S.: Exploration of short reads genome mapping in hardware. In: International Conference on FPL, pp. 360–363 (2010)
Fujinaga, M., Chernaia, M.M., Tarasova, N.I., Mosimann, S.C., James, M.N.: Crystal structure of human pepsin and its complex with pepstatin. Protein Sci. 4 (1995)
Gabb, H.A., Jackson, R.M., Sternberg, M.J.E.: Modelling protein docking using shape complementarity, electrostatics and biochemical information. J. Mol. Biol. 272 (1997)
Gac, N., Mancini, S., Desvignes, M., Houzet, D.: High speed 3D tomography on CPU, GPU, and FPGA. EURASIP J. Embed. Syst. 2008, 5:1–5:12 (2008)
Gaisler: LEON processors. http://www.gaisler.com/index.php/products/processors/ (2015)
Gao, H., Yang, Y., Ma, X., Dong, G.: Analysis of the effect of LUT size on FPGA area and delay using theoretical derivations. In: Sixth International Symposium on Quality of Electronic Design, 2005. ISQED 2005, pp. 370–374 (2005)
Grozea, C., Bankovic, Z., Laskov, P.: Facing the multicore-challenge. chap. FPGA vs. Multi-core CPUs vs. GPUs: Hands-on Experience with a Sorting Application, pp. 105–117. Springer-Verlag, Berlin, Heidelberg (2010)
Halperin, I., Ma, B., Wolfson, H., Nussinov, R.: Principles of docking: an overview of search algorithms and a guide to scoring functions. Proteins Struct., Funct., Bioinf. 47(4), 409–443 (2002)
Hauck, S., DeHon, A.: Reconfigurable Computing: The Theory and Practice of FPGA-Based Computation. Morgan Kaufmann, Systems on Silicon (2007)
Herbordt, M.C., VanCourt, T., Gu, Y., Sukhwani, B., Conti, A., Model, J., DiSabello, D.: Achieving high performance with FPGA-based computing. Computer 40(3), 50–57 (2007)
Hernandez, D., François, P., Farinelli, L., Østerås, M., Schrenzel, J.: De novo bacterial genome sequencing: millions of very short reads assembled on a desktop computer. Genome Res. 18 (2008)
Hert, D.G., Fredlake, C.P., Barron, A.E.: Advantages and limitations of next-generation sequencing technologies: a comparison of electrophoresis and non-electrophoresis methods. Electrophoresis 29(23), 4618–4626 (2008)
Homer, N., Merriman, B., Nelson, S.F.: BFAST: an alignment tool for large scale genome resequencing. PLoS ONE 4 (2009)
Inc., D.: Digilent FPGA Boards. https://www.digilentinc.com/ (2015)
ITRS: The International Technology Roadmap for Semiconductors. http://www.itrs.net (2015)
Jamieson, P., Rose, J.: Enhancing the area efficiency of fpgas with hard circuits using shadow clusters. IEEE Trans. VLSI Syst. 18(12), 1696–1709 (2010)
Jenwitheesuk, E., Horst, J.A., Rivas, K.L., Voorhis, W.C.V., Samudrala, R.: Novel paradigms for drug discovery: computational multitarget screening. Trends Pharmacol. Sci. 29(2), 62–71 (2008)
Kapre, N., DeHon, A.: Performance comparison of single-precision SPICE model-evaluation on FPGA, GPU, cell, and multi-core processors. In: International Conference on Field Programmable Logic and Applications, 2009. FPL 2009, pp. 65–72 (2009)
Kitchen, D.B., Decornez, H., Furr, J.R., Bajorath, J.: Docking and scoring in virtual screening for drug discovery: methods and applications. Nat. Rev. Drug Discov. 3(11), 935–949 (2004)
Knodel, O., Preusser, T., Spallek, R.: Next-generation massively parallel short-read mapping on FPGAs. In: IEEE International Conference on ASAP, pp. 195–201 (2011)
Kozakov, D., Brenke, R., Comeau, S.R., Vajda, S.: PIPER: an FFT-based protein docking program with pairwise potentials. Proteins (2006)
Kuon, I., Rose, J.: Measuring the gap between FPGAs and ASICs. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 26(2), 203–215 (2007)
Kuon, I., Rose, J.: Area and delay trade-offs in the circuit and architecture design of FPGAs. In: Proceedings of the 16th International ACM/SIGDA Symposium on Field Programmable Gate Arrays. FPGA ’08, pp. 149–158. ACM, New York, NY, USA (2008)
Kuon, I., Tessier, R., Rose, J.: FPGA architecture: survey and challenges. Found. Trends Electron. Des. Autom. 2, 135–253 (2008)
Langmead, B., Trapnell, C., Pop, M., Salzberg, S.: Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10 (2009)
Li, H., Ruan, J., Durbin, R.: Mapping short DNA sequencing reads and calling variants using mapping quality scores. Genome Res. 18(11), 1851–1858 (2008)
Li, R., Li, Y., Kristiansen, K., Wang, J.: SOAP: short oligonucleotide alignment program. Bioinformatics 24(5), 713–714 (2008)
Liu, Y., Schmidt, B., Maskell, D.: Parallelized short read assembly of large genomes using De Bruijn graphs. BMC Bioinf. 12(1), 354–363 (2011)
Luo, R., Liu, B., Xie, Y., Li, Z., Huang, W., Yuan, J., He, G., Chen, Y., Pan, Q., Liu, Y., Tang, J., Wu, G., Zhang, H., Shi, Y., Liu, Y., Yu, C., Wang, B., Lu, Y., Han, C., Cheung, D.W., Yiu, S.M., Peng, S., Xiaoqian, Z., Liu, G., Liao, X., Li, Y., Yang, H., Wang, J., Lam, T.W., Wang, J.: SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience 1(1), 18 (2012)
Mardis, E.R.: Next generation DNA sequencing methods. Ann. Rev. Genomics Hum. Genet. 9, 387–402 (2008)
McCollum, J.M., Peterson, G.D., Cox, C.D., Simpson, M.L.: Accelerating gene regulatory network modeling using grid-based simulation. Simulation 80(4–5), 231–241 (2004)
McInnes, C.: Virtual screening strategies in drug discovery. Curr. Opin. Chem. Biol. 11(5), 494–502 (2007)
Miller, J.R., Koren, S., Sutton, G.: Assembly algorithms for next-generation sequencing data. Genomics 95(6), 315–327 (2010)
Morris, G.M., Huey, R., Lindstrom, W., Sanner, M.F., Belew, R.K., Goodsell, D.S., Olson, A.J.: J. Comput. Chem
Movahedi, N., Forouzmand, E., Chitsaz, H.: De novo co-assembly of bacterial genomes from multiple single cells. In: 2012 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 1–5 (2012)
Myers, E.W., Sutton, G.G., Delcher, A.L., Dew, I.M., Fasulo, D.P., et al.: A whole-genome assembly of Drosophila. Science 287(5461), 2196–2204 (2000)
Nagarajan, N., Pop, M.: Sequence assembly demystified. In: Nature Reviews Genetics, pp. 157–167 (2013)
Ngai, T., Rose, J., Wilton, S.J.E.: An sram-programmable field-configurable memory. In: Proceedings of the IEEE Custom Integrated Circuits Conference, 1995, pp. 499–502 (1995)
NVIDIA: Nvidia GPGPU. http://www.nvidia.com (2015)
Olson, C., Kim, M., Clauson, C., Kogon, B., Ebeling, C., Hauck, S., Ruzzo, W.: Hardware acceleration of short read mapping. In: IEEE Symposium on FCCM, pp. 161–168 (2012)
Parandeh-Afshar, H., Verma, A., Brisk, P., Ienne, P.: Improving fpga performance for carry-save arithmetic. IEEE Trans. Very Large Scale Integ. VLSI Syst. 18(4), 578–590 (2010)
Patel, S., Hwu, W.W.: Guest editors’ introduction: accelerator architectures. IEEE Micro 28(4), 4–12 (2008)
Pothineni, N., Kumar, A., Paul, K.: Exhaustive enumeration of legal custom instructions for extensible processors. In: VLSID ’08: Proceedings of the 21st International Conference on VLSI Design, pp. 261–266. IEEE Computer Society, Washington, DC, USA (2008)
QuickLogic: QuickLogic FPGAs. http://www.quicklogic.com/ (2015)
Ritchie, D.W., Venkatraman, V.: Ultra-fast FFT protein docking on graphics processors. Bioinformatics 26(19), 2398–2405 (2010)
Rizk, G., Lavenier, D.: Gassst: global alignment short sequence search tool. Bioinformatics 26(20), 2534–2540 (2010)
Rose, J., Gamal, A.E., Member, S., Sangiovanni-vincentelli, A.: Architecture of field-programmable gate arrays: the effect of logic block functionality on area efficiency. Proc. IEEE 25, 1217–1225 (1990)
Sequencing, R.: 454 Sequencing. http://www.454.com/products/analysis-software/ (2015)
Simpson, J., Wong, K., Jackman, S., Schein, J., Jones, S., Birol, I.: ABySS: a parallel assembler for short read sequence data. Genome Res. 19, 1117 (2009)
Singh, D.P., Czajkowski, T.S., Ling, A.C.: Harnessing the power of fpgas using altera’s opencl compiler. In: Hutchings, B.L., Betz, V. (eds.) FPGA, pp. 5–6. ACM (2013)
Smith, A.D., Xuan, Z., Zhang, M.Q.: Using quality scores and longer reads improves accuracy of solexa read mapping. BMC Bioinf. 9, 128 (2008)
Smith, T., Waterman, M.S.: Identification of common molecular subsequences. J. Mol. Biol. 147(3), 195–197 (1981)
Sternberg, M.J.E., Aloy, P., Gabb, H.A., Jackson, R.M., Moont, G., Querol, E., Aviles, F.X.: A computational system for modeling flexible protein-protein and protein-DNA docking. In: Proceedings of the 6th International Conference on Intelligent Systems for Molecular Biology, pp. 183–192 (1998)
Stone, J., Gohara, D., Shi, G.: Opencl: a parallel programming standard for heterogeneous computing systems. Comput. Sci. Eng. 12(3), 66–73 (2010)
Tabula: Tabula FPGAs. http://www.tabula.com/ (2015)
Tang, W., Wang, W., Duan, B., Zhang, C., Tan, G., Zhang, P., Sun, N.: Accelerating millions of short reads mapping on a heterogeneous architecture with fpga accelerator. Annual IEEE Symposium on Field-Programmable Custom Computing Machines, 0, pp. 184–187 (2012)
Venkatesh, G., Sampson, J., Goulding, N., Garcia, S., Bryksin, V., Lugo-Martinez, J., Swanson, S., Taylor, M.B.: Conservation cores: reducing the energy of mature computations. SIGARCH Comput. Archit. News 38(1), 205–218 (2010)
Wilton, S.J.E.: Embedded memory in fpgas: recent research results. In: 1999 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, pp. 292–296 (1999)
Wilton, S.J.E., Rose, J., Vranesic, Z.: The memory/logic interface in fpgas with large embedded memory arrays. IEEE Trans. Very Large Scale Integr. VLSI Syst. 7(1), 80–91 (1999)
Wilton, S.J.E., Rose, J., Vranesic, Z.G.: Architecture of centralized field-configurable memory. In: Proceedings of the 1995 ACM Third International Symposium on Field-programmable Gate Arrays. FPGA ’95, pp. 97–103. ACM, New York, NY, USA (1995)
XILINX: Xilinx brams (2015)
XILINX: Xilinx core generator. http://www.xilinx.com/tools/coregen.htm (2015)
XILINX: Xilinx dsps. http://www.xilinx.com/products/technology/dsp/ (2015)
Xilinx: Xilinx FPGAs, ISE. http://www.xilinx.com (2015)
XtremeData: XtremeData FPGA Boards. http://www.xtremedata.com/ (2015)
Zerbino, D.R., Birney, E.: Velvet: algorithms for de novo short read assembly using De Bruijn graphs. Genome Res. 18(5), 821–829 (2008)
Zhang, W., Jha, N.K., Shang, L.: A hybrid nano/cmos dynamically reconfigurable system—part i: Architecture. J. Emerg. Technol. Comput. Syst. 5(4), 16:1–16:30 (2009)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media Singapore
About this chapter
Cite this chapter
Varma, B.S.C., Paul, K., Balakrishnan, M. (2016). Related Work. In: Architecture Exploration of FPGA Based Accelerators for BioInformatics Applications. Springer Series in Advanced Microelectronics, vol 55. Springer, Singapore. https://doi.org/10.1007/978-981-10-0591-6_2
Download citation
DOI: https://doi.org/10.1007/978-981-10-0591-6_2
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-0589-3
Online ISBN: 978-981-10-0591-6
eBook Packages: EngineeringEngineering (R0)