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@MastersThesis{Hall2010,
  author    = {Adam Hall},
  title     = {Short-Read DNA Sequence Alignment with Custom Designed FPGA-based Hardware},
  school    = {THE FACULTY OF GRADUATE STUDIES (Bioinformatics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)},
  year      = {2010},
  month     = {November},
  abstract  = {The alignment of short DNA read sequencing data to a human reference genome sequence has become a standard step in the analysis pipeline for short DNA read sequence data. As the rate at which short read DNA sequence data is being produced doubles every 5 months, analysis of this data in a computationally efficient way is becoming increasingly important. We demonstrate how we can exploit the ``embarrassingly parallel'' property of short read sequence alignment in custom-designed hardware in FPGA’s. Hardware is chosen, a system is designed, and this system is implemented. My FPGA-based hit finder was demonstrated to produce correct hit results. The performance of this single FPGA implementation was demonstrated to be 71,000 seed hits found per hour on a human genome sized reference sequence. The implementation was demonstrated to produce identical results to the hit finder stage of the MAQ aligner. We demonstrate that the price/performance of this sliding-window FPGA aligner (approximately ~355 seeds/hr/$) compares favorably to the price/performance of sliding-window software aligners (approximately ~67.5 seeds/hr/$ for MAQ). However, software aligners which are based on the superior Burrows-Wheeler alignment algorithm still have a significant price/performance advantage over the FPGA-based approach (approximately ~7,200 seeds/hr/$). We predict that as chips continue to increase in size due to Moore’s Law and computation is performed in high-density cloud-computing datacenters the FPGA-based approach will become preferable to current software aligners.},
  file      = {2010_Hall_masterthesis.pdf:by-author/H/Hall/2010_Hall_masterthesis.pdf:PDF},
  keywords  = {FPGA, NGS, new generation sequenceing, custom hardware, Verilog, VHDL, sequence alignment},
  owner     = {saulius},
  timestamp = {2016.10.03},
  url       = {https://open.library.ubc.ca/cIRcle/collections/ubctheses/24/items/1.0071441},
}

@Manuscript{Khan2012,
  author    = {M. A. Khan and M. Chiu and M. A. Herbordt},
  title     = {{FPGA}-accelerated molecular dynamics},
  year      = {2012},
  keywords  = {CS, FPGA, molecular dynamics},
  url       = {http://www.bu.edu/caadlab/Khan13.pdf},
  file      = {:by-author/K/Khan/2012_Khan.pdf:PDF},
  owner     = {saulius},
  timestamp = {2020.02.07},
}

@Presentation{Chiu2010,
  author    = {Matt Chiu and Martin Herbordt},
  title     = {Towards production {FPGA}‐accelerated molecular dynamics: progress and challenge},
  year      = {2010},
  file      = {:by-author/C/Chiu/2010_Chiu.pdf:PDF},
  keywords  = {CS, molecular dynamics, FPGA},
  owner     = {saulius},
  timestamp = {2020.02.07},
  url       = {http://www.ncsa.illinois.edu/Conferences/HPRCTA10/presentations/chiu.pdf},
}

@Article{Schaffner2018,
  author      = {Michael Schaffner and Luca Benini},
  title       = {On the feasibility of {FPGA} acceleration of molecular dynamics simulations},
  journal     = {ArXiv},
  year        = {2018},
  pages       = {180804201},
  abstract    = {Classical molecular dynamics (MD) simulations are important tools in life and material sciences since they allow studying chemical and biological processes in detail. However, the inherent scalability problem of particle-particle interactions and the sequential dependency of subsequent time steps render MD computationally intensive and difficult to scale. To this end, specialized FPGA-based accelerators have been repeatedly proposed to ameliorate this problem. However, to date none of the leading MD simulation packages fully support FPGA acceleration and a direct comparison of GPU versus FPGA accelerated codes has remained elusive so far. With this report, we aim at clarifying this issue by comparing measured application performance on GPU-dense compute nodes with performance and cost estimates of a FPGA-based single- node system. Our results show that an FPGA-based system can indeed outperform a similarly configured GPU-based system, but the overall application-level speedup remains in the order of 2x due to software overheads on the host. Considering the price for GPU and FPGA solutions, we observe that GPU-based solutions provide the better cost/performance tradeoff, and hence pure FPGA-based solutions are likely not going to be commercially viable. However, we also note that scaled multi-node systems could potentially benefit from a hybrid composition, where GPUs are used for compute intensive parts and FPGAs for latency and communication sensitive tasks.},
  date        = {2018-08-08},
  eprint      = {http://arxiv.org/abs/1808.04201v1},
  eprintclass = {cs.DC},
  eprinttype  = {arXiv},
  file        = {:by-author/S/Schaffner/2018_Schaffner_180804201.pdf:PDF},
  keywords    = {CS, FPGA, molecular dynamics},
  owner       = {saulius},
  timestamp   = {2020.02.07},
  url         = {https://arxiv.org/pdf/1808.04201.pdf},
}

@Presentation{Yang2019,
  author    = {Chen Yang and Tong Geng and Tianqi Wang and Charles Lin and Jiayi Sheng and Vipin Sachdeva and Woody Sherman and Martin Herbordt},
  title     = {Molecular dynamics range-limited force evaluation optimized for {FPGA}},
  year      = {2019},
  file      = {:by-author/Y/Yang/2019_Yang.pdf:PDF},
  keywords  = {CS, FPGA, molecular dynamics},
  owner     = {saulius},
  timestamp = {2020.02.07},
  url       = {https://asap2019.csl.cornell.edu/presentations/48_Yang.pdf},
}

@Manuscript{Yang2019a,
  author    = {Chen Yang and Tong Geng and Tianqi Wang and Charles Lin and Jiayi Sheng and Vipin Sachdeva and Woody Sherman and Martin Herbordt},
  title     = {Molecular dynamics range-limited force evaluation optimized for {FPGA}s},
  year      = {2019},
  keywords  = {CS, FPGA, molecular dynamics},
  url       = {http://www.bu.edu/caadlab/ASAP19b.pdf},
  file      = {:by-author/Y/Yang/2019_Yang_a.pdf:PDF},
  owner     = {saulius},
  timestamp = {2020.02.07},
}

@Article{Yang2019b,
  author      = {Chen Yang and Tong Geng and Tianqi Wang and Rushi Patel and Qingqing Xiong and Ahmed Sanaullah and Jiayi Sheng and Charles Lin and Vipin Sachdeva and Woody Sherman and Martin C. Herbordt},
  title       = {Fully integrated on-{FPGA} molecular dynamics simulations},
  journal     = {ArXiv},
  year        = {2019},
  pages       = {190505359},
  abstract    = {The implementation of Molecular Dynamics (MD) on FPGAs has received substantial attention. Previous work, however, has consisted of either proof-of-concept implementations of components, usually the range-limited force; full systems, but with much of the work shared by the host CPU; or prototype demonstrations, e.g., using OpenCL, that neither implement a whole system nor have competitive performance. In this paper, we present what we believe to be the first full-scale FPGA-based simulation engine, and show that its performance is competitive with a GPU (running Amber in an industrial production environment). The system features on-chip particle data storage and management, short- and long-range force evaluation, as well as bonded forces, motion update, and particle migration. Other contributions of this work include exploring numerous architectural trade-offs and analysis on various mappings schemes among particles/cells and the various on-chip compute units. The potential impact is that this system promises to be the basis for long timescale Molecular Dynamics with a commodity cluster.},
  date        = {2019-05-14},
  eprint      = {http://arxiv.org/abs/1905.05359v1},
  eprintclass = {cs.DC},
  eprinttype  = {arXiv},
  file        = {:by-author/Y/Yang/2019_Yang_190505359.pdf:PDF},
  keywords    = {CS, FPGA, molecular dynamics},
  owner       = {saulius},
  timestamp   = {2020.02.07},
  url         = {https://arxiv.org/pdf/1905.05359.pdf},
}

@InProceedings{Waidyasooriya2016,
  author    = {Hasitha Muthumala Waidyasooriya and Masanori Hariyama and Kota Kasahara},
  title     = {Architecture of an {FPGA} accelerator for molecular dynamics simulation using {OpenCL}},
  booktitle = {2016 {IEEE}/{ACIS} 15th International Conference on Computer and Information Science ({ICIS})},
  year      = {2016},
  pages     = {7550743},
  month     = {jun},
  publisher = {{IEEE}},
  doi       = {10.1109/icis.2016.7550743},
  file      = {:by-author/W/Waidyasooriya/2016_Waidyasooriya_7550743.pdf:PDF},
  keywords  = {CS, FPGA, molecular dynamics},
  owner     = {saulius},
  timestamp = {2020.02.07},
}