{"title":"一个用于因子图应用程序的硬件生成器","authors":"James Demma, P. Athanas","doi":"10.1109/ReConFig.2014.7032490","DOIUrl":null,"url":null,"abstract":"A Factor Graph (FG-http://en.wikipedia.org/wiki/Factor_graph) is a structure used to And solutions to problems that can be represented as a Probabilistic Graphical Model (PGM). They consist of interconnected variable nodes and factor nodes, which iteratively compute and pass messages to each other. FG's can be applied to solve decoding of forward error correcting codes, Markov chains and Markov Random Fields, Kaiman Filtering, Fourier Transforms, and even some games such as Sudoku. In this paper, a framework is presented for rapid prototyping of hardware implementations of FG-based applications. The FG developer specifies aspects of the application, and the framework returns a design. A system of Python scripts and Verilog Hardware Description Language templates together are used to generate the HDL source code for the application. The generated designs are vendor/platform agnostic, but currently target the Xilinx Virtex-6-based ML605. The framework has so far been primarily applied to construct Low Density Parity Check (LDPC) decoders. The characteristics of a large basket of generated LDPC decoders, including contemporary 802.11η decoders, have been examined as a verification of the system and as a demonstration of its capabilities. As a further demonstration, the framework has been applied to construct a Sudoku solver.","PeriodicalId":137331,"journal":{"name":"2014 International Conference on ReConFigurable Computing and FPGAs (ReConFig14)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A hardware generator for factor graph applications\",\"authors\":\"James Demma, P. Athanas\",\"doi\":\"10.1109/ReConFig.2014.7032490\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A Factor Graph (FG-http://en.wikipedia.org/wiki/Factor_graph) is a structure used to And solutions to problems that can be represented as a Probabilistic Graphical Model (PGM). They consist of interconnected variable nodes and factor nodes, which iteratively compute and pass messages to each other. FG's can be applied to solve decoding of forward error correcting codes, Markov chains and Markov Random Fields, Kaiman Filtering, Fourier Transforms, and even some games such as Sudoku. In this paper, a framework is presented for rapid prototyping of hardware implementations of FG-based applications. The FG developer specifies aspects of the application, and the framework returns a design. A system of Python scripts and Verilog Hardware Description Language templates together are used to generate the HDL source code for the application. The generated designs are vendor/platform agnostic, but currently target the Xilinx Virtex-6-based ML605. The framework has so far been primarily applied to construct Low Density Parity Check (LDPC) decoders. The characteristics of a large basket of generated LDPC decoders, including contemporary 802.11η decoders, have been examined as a verification of the system and as a demonstration of its capabilities. As a further demonstration, the framework has been applied to construct a Sudoku solver.\",\"PeriodicalId\":137331,\"journal\":{\"name\":\"2014 International Conference on ReConFigurable Computing and FPGAs (ReConFig14)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on ReConFigurable Computing and FPGAs (ReConFig14)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ReConFig.2014.7032490\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on ReConFigurable Computing and FPGAs (ReConFig14)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ReConFig.2014.7032490","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A hardware generator for factor graph applications
A Factor Graph (FG-http://en.wikipedia.org/wiki/Factor_graph) is a structure used to And solutions to problems that can be represented as a Probabilistic Graphical Model (PGM). They consist of interconnected variable nodes and factor nodes, which iteratively compute and pass messages to each other. FG's can be applied to solve decoding of forward error correcting codes, Markov chains and Markov Random Fields, Kaiman Filtering, Fourier Transforms, and even some games such as Sudoku. In this paper, a framework is presented for rapid prototyping of hardware implementations of FG-based applications. The FG developer specifies aspects of the application, and the framework returns a design. A system of Python scripts and Verilog Hardware Description Language templates together are used to generate the HDL source code for the application. The generated designs are vendor/platform agnostic, but currently target the Xilinx Virtex-6-based ML605. The framework has so far been primarily applied to construct Low Density Parity Check (LDPC) decoders. The characteristics of a large basket of generated LDPC decoders, including contemporary 802.11η decoders, have been examined as a verification of the system and as a demonstration of its capabilities. As a further demonstration, the framework has been applied to construct a Sudoku solver.