Literature DB >> 21603152

Computing Models for FPGA-Based Accelerators.

Martin C Herbordt1, Yongfeng Gu, Tom Vancourt, Josh Model, Bharat Sukhwani, Matt Chiu.   

Abstract

Field-programmable gate arrays are widely considered as accelerators for compute-intensive applications. A critical phase of FPGA application development is finding and mapping to the appropriate computing model. FPGA computing enables models with highly flexible fine-grained parallelism and associative operations such as broadcast and collective response. Several case studies demonstrate the effectiveness of using these computing models in developing FPGA applications for molecular modeling.

Entities:  

Year:  2008        PMID: 21603152      PMCID: PMC3096930          DOI: 10.1109/MCSE.2008.143

Source DB:  PubMed          Journal:  Comput Sci Eng        ISSN: 1521-9615            Impact factor:   2.080


  6 in total

1.  Multiple grid methods for classical molecular dynamics.

Authors:  Robert D Skeel; Ismail Tezcan; David J Hardy
Journal:  J Comput Chem       Date:  2002-04-30       Impact factor: 3.376

2.  Molecular surface recognition: determination of geometric fit between proteins and their ligands by correlation techniques.

Authors:  E Katchalski-Katzir; I Shariv; M Eisenstein; A A Friesem; C Aflalo; I A Vakser
Journal:  Proc Natl Acad Sci U S A       Date:  1992-03-15       Impact factor: 11.205

Review 3.  Docking and scoring in virtual screening for drug discovery: methods and applications.

Authors:  Douglas B Kitchen; Hélène Decornez; John R Furr; Jürgen Bajorath
Journal:  Nat Rev Drug Discov       Date:  2004-11       Impact factor: 84.694

4.  Simple but predictive protein models.

Authors:  Feng Ding; Nikolay V Dokholyan
Journal:  Trends Biotechnol       Date:  2005-09       Impact factor: 19.536

Review 5.  Studies of folding and misfolding using simplified models.

Authors:  Nikolay V Dokholyan
Journal:  Curr Opin Struct Biol       Date:  2006-01-18       Impact factor: 6.809

6.  Explicit Design of FPGA-Based Coprocessors for Short-Range Force Computations in Molecular Dynamics Simulations.

Authors:  Yongfeng Gu; Tom Vancourt; Martin C Herbordt
Journal:  Parallel Comput       Date:  2008-05       Impact factor: 0.986

  6 in total
  1 in total

1.  Fine-grained parallelization of fitness functions in bioinformatics optimization problems: gene selection for cancer classification and biclustering of gene expression data.

Authors:  Juan A Gomez-Pulido; Jose L Cerrada-Barrios; Sebastian Trinidad-Amado; Jose M Lanza-Gutierrez; Ramon A Fernandez-Diaz; Broderick Crawford; Ricardo Soto
Journal:  BMC Bioinformatics       Date:  2016-08-31       Impact factor: 3.169

  1 in total

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