{"title":"用数据流引擎加速分子力学中感应偶极子的计算","authors":"F. Pratas, D. Oriato, O. Pell, R. Mata, L. Sousa","doi":"10.1109/FCCM.2013.34","DOIUrl":null,"url":null,"abstract":"In Molecular Mechanics simulations, the treatment of electrostatics is the most computational intensive task. Modern force fields, such as the AMOEBA, which include explicit polarization effects, are particularly computationally demanding. We propose a static dataflow architecture for accelerating polarizable force fields. Results, obtained with Maxeler's MaxCompiler, show a speed-up factor of about 14x on a Maxeler 1U MaxNode, when compared to a 12-core CPU node while using half of the dataflow engine capacity. Projections for a full chip implementation indicate that speed-up results of up to 29x per node can be reached. Moreover, our implementation on the Maxeler system shows improvements between 2.5x and 4x compared to NVIDIA Fermibased GPUs. The current work shows the potential of dataflow engines in accelerating this field of applications.","PeriodicalId":269887,"journal":{"name":"2013 IEEE 21st Annual International Symposium on Field-Programmable Custom Computing Machines","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Accelerating the Computation of Induced Dipoles for Molecular Mechanics with Dataflow Engines\",\"authors\":\"F. Pratas, D. Oriato, O. Pell, R. Mata, L. Sousa\",\"doi\":\"10.1109/FCCM.2013.34\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In Molecular Mechanics simulations, the treatment of electrostatics is the most computational intensive task. Modern force fields, such as the AMOEBA, which include explicit polarization effects, are particularly computationally demanding. We propose a static dataflow architecture for accelerating polarizable force fields. Results, obtained with Maxeler's MaxCompiler, show a speed-up factor of about 14x on a Maxeler 1U MaxNode, when compared to a 12-core CPU node while using half of the dataflow engine capacity. Projections for a full chip implementation indicate that speed-up results of up to 29x per node can be reached. Moreover, our implementation on the Maxeler system shows improvements between 2.5x and 4x compared to NVIDIA Fermibased GPUs. The current work shows the potential of dataflow engines in accelerating this field of applications.\",\"PeriodicalId\":269887,\"journal\":{\"name\":\"2013 IEEE 21st Annual International Symposium on Field-Programmable Custom Computing Machines\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE 21st Annual International Symposium on Field-Programmable Custom Computing Machines\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FCCM.2013.34\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 21st Annual International Symposium on Field-Programmable Custom Computing Machines","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FCCM.2013.34","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Accelerating the Computation of Induced Dipoles for Molecular Mechanics with Dataflow Engines
In Molecular Mechanics simulations, the treatment of electrostatics is the most computational intensive task. Modern force fields, such as the AMOEBA, which include explicit polarization effects, are particularly computationally demanding. We propose a static dataflow architecture for accelerating polarizable force fields. Results, obtained with Maxeler's MaxCompiler, show a speed-up factor of about 14x on a Maxeler 1U MaxNode, when compared to a 12-core CPU node while using half of the dataflow engine capacity. Projections for a full chip implementation indicate that speed-up results of up to 29x per node can be reached. Moreover, our implementation on the Maxeler system shows improvements between 2.5x and 4x compared to NVIDIA Fermibased GPUs. The current work shows the potential of dataflow engines in accelerating this field of applications.