Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/891
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dc.contributor.authorMilutinoviee, Veljko ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:23:09Z-
dc.date.available2020-05-17T08:23:09Z-
dc.date.issued2017en_US
dc.identifier.isbn9783319661285 ; (electronic bk.) ;en_US
dc.identifier.isbn3319661280 ; (electronic bk.) ;en_US
dc.identifier.isbn9783319661278 ;en_US
dc.identifier.isbn3319661272 ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/891-
dc.descriptionOhio Library and Information Network ;en_US
dc.descriptionAvailable to OhioLINK libraries ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionPrint version: ; 3319661272 ; 9783319661278 ; (OCoLC)994791101 ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractThis informative text/reference highlights the potential of DataFlow computing in research requiring high speeds, low power requirements, and high precision, while also benefiting from a reduction in the size of the equipment. The cutting-edge research and implementation case studies provided in this book will help the reader to develop their practical understanding of the advantages and unique features of this methodology. This work serves as a companion title to DataFlow Supercomputing Essentials: Algorithms, Applications and Implementations, which reviews the key algorithms in this area, and provides useful examples. Topics and features: Reviews the library of tools, applications, and source code available to support DataFlow programming Discusses the enhancements to DataFlow computing yielded by small hardware changes, different compilation techniques, debugging, and optimizing tools Examines when a DataFlow architecture is best applied, and for which types of calculation Describes how converting applications to a DataFlow representation can result in an acceleration in performance, while reducing the power consumption Explains how to implement a DataFlow application on Maxeler hardware architecture, with links to a video tutorial series available online This enlightening volume will be of great interest to all researchers investigating supercomputing in general, and DataFlow computing in particular. Advanced undergraduate and graduate students involved in courses on Data Mining, Microprocessor Systems, and VLSI Systems, will also find the book to be a helpful reference ;en_US
dc.description.statementofresponsibilityVeljko Milutinovic... [et al.]en_US
dc.description.tableofcontentsPreface; Dataflow Taxonomy; Maxeler; Research Issues; Application Issues; Conclusion; Contents; Part I Research; 1 Maxeler AppGallery Revisited; 1.1 Introduction; 1.2 Maxeler AppGallery; 1.2.1 Data Analytics Category; 1.2.1.1 Sequential Monte Carlo; 1.2.1.2 Real-Time VaR Monitoring; 1.2.1.3 Boosted Decision Tree Classifier; 1.2.1.4 Heston Option Pricer; 1.2.2 Engineering Category; 1.2.2.1 Motion Estimation; 1.2.2.2 Real-time 4k Ultra HD Video; 1.2.2.3 Gzip Compression ;en_US
dc.description.tableofcontents1.2.3 Low Latency Transaction Processing Category1.2.3.1 HFTDemo; 1.2.4 Networking Category; 1.2.4.1 High-Speed Packet Capture; 1.2.4.2 Packet Pusher; 1.2.4.3 Low-Latency HTTP Web Server; 1.2.5 Science Category; 1.2.5.1 Reverse Time Migration; 1.2.5.2 Network Sorting; 1.2.5.3 Localization Microscopy; 1.2.6 Security Category; 1.2.6.1 Fully Homomorphic Encryption; References; 2 Discrepancy Reduction Between the Topology of Dataflow Graph and the Topology of FPGA Structure; 2.1 Introduction; 2.2 Dataflow Graph ;en_US
dc.description.tableofcontents2.3 Getting to Accelerated Application: Maxeler Way2.4 Simulation Debugging; 2.4.1 Simulation Watches; 2.4.2 Simulation printf; 2.5 Hardware Debugging; 2.5.1 DFE printf; 2.6 Advanced Debugging; 2.6.1 Introduction; 2.6.2 Kernel Halted on Input; 2.6.3 Kernel Halted on Output; 2.6.4 Stream Status Blocks; 2.6.5 Deadlock; 2.6.5.1 Deadlock Due To: Kernel Has Scheduled an Input Before an Output; 2.6.5.2 Deadlock Due to: FIFO Ends Up Full; 2.7 Effects of Inconsistency Between Simulation and Hardware; 2.7.1 Uninitialized Elements ;en_US
dc.description.tableofcontents2.7.2 Race Condition2.8 Embedded DFE Optimizations; 2.8.1 Kernel Optimizations; 2.8.1.1 Holistic Optimization; 2.8.1.2 Push-Pop Optimizations; 2.8.1.3 Placement Constraints; 2.8.1.4 Input Registering; 2.8.1.5 Per-Stream Optimizations; 2.8.2 Manager Optimizations; 2.8.2.1 LMem Clock Frequency; 2.8.2.2 Stream Clock Frequency; 2.9 Global DFE Optimization Practices: Getting Maximum Performance; 2.9.1 Introduction; 2.9.2 Dataflow Computing Strategy; 2.9.3 Fitting Procedure; 2.9.3.1 Techniques to Fit Designs Onto DFE ;en_US
dc.description.tableofcontents2.9.4 How to Make it Fite2.9.4.1 Stage 1: DFE Logic Utilization >100%: Macro-optimization; 2.9.4.2 Stage 2: DFE Logic Utilization >80% and <100%, Micro-optimizations; 2.9.4.3 Stage 3: DFE Logic Utilization <80%, Frequency Optimization; 2.9.5 Optimizing Memory Bound Applications: Data Size; 2.9.5.1 Differences in Memory Controllers of Different Cards; 2.9.5.2 Data-Specific Compression; 2.9.5.3 Data Encoding; 2.9.5.4 Reorganization of the Order of Computations; 2.9.6 Optimizing Compute Performance: Clock Frequency ;en_US
dc.format.extent1 online resource ;en_US
dc.format.extentIncludes bibliographical references and index ;en_US
dc.publisherSpringer,en_US
dc.relation.ispartofseriesComputer communications and networks ;en_US
dc.relation.ispartofseriesComputer communications and networks ;en_US
dc.relation.haspart9783319661285.pdfen_US
dc.subjectSupercomputers ;en_US
dc.subjectHigh performance computing ;en_US
dc.titleDataFlow supercomputing essentials :en_US
dc.title.alternativeresearch, development and education /en_US
dc.typeBooken_US
dc.publisher.placeCham :en_US
dc.classification.lcQA76.5 ;en_US
Appears in Collections:مهندسی فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9783319661285.pdf3.81 MBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMilutinoviee, Veljko ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:23:09Z-
dc.date.available2020-05-17T08:23:09Z-
dc.date.issued2017en_US
dc.identifier.isbn9783319661285 ; (electronic bk.) ;en_US
dc.identifier.isbn3319661280 ; (electronic bk.) ;en_US
dc.identifier.isbn9783319661278 ;en_US
dc.identifier.isbn3319661272 ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/891-
dc.descriptionOhio Library and Information Network ;en_US
dc.descriptionAvailable to OhioLINK libraries ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionPrint version: ; 3319661272 ; 9783319661278 ; (OCoLC)994791101 ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractThis informative text/reference highlights the potential of DataFlow computing in research requiring high speeds, low power requirements, and high precision, while also benefiting from a reduction in the size of the equipment. The cutting-edge research and implementation case studies provided in this book will help the reader to develop their practical understanding of the advantages and unique features of this methodology. This work serves as a companion title to DataFlow Supercomputing Essentials: Algorithms, Applications and Implementations, which reviews the key algorithms in this area, and provides useful examples. Topics and features: Reviews the library of tools, applications, and source code available to support DataFlow programming Discusses the enhancements to DataFlow computing yielded by small hardware changes, different compilation techniques, debugging, and optimizing tools Examines when a DataFlow architecture is best applied, and for which types of calculation Describes how converting applications to a DataFlow representation can result in an acceleration in performance, while reducing the power consumption Explains how to implement a DataFlow application on Maxeler hardware architecture, with links to a video tutorial series available online This enlightening volume will be of great interest to all researchers investigating supercomputing in general, and DataFlow computing in particular. Advanced undergraduate and graduate students involved in courses on Data Mining, Microprocessor Systems, and VLSI Systems, will also find the book to be a helpful reference ;en_US
dc.description.statementofresponsibilityVeljko Milutinovic... [et al.]en_US
dc.description.tableofcontentsPreface; Dataflow Taxonomy; Maxeler; Research Issues; Application Issues; Conclusion; Contents; Part I Research; 1 Maxeler AppGallery Revisited; 1.1 Introduction; 1.2 Maxeler AppGallery; 1.2.1 Data Analytics Category; 1.2.1.1 Sequential Monte Carlo; 1.2.1.2 Real-Time VaR Monitoring; 1.2.1.3 Boosted Decision Tree Classifier; 1.2.1.4 Heston Option Pricer; 1.2.2 Engineering Category; 1.2.2.1 Motion Estimation; 1.2.2.2 Real-time 4k Ultra HD Video; 1.2.2.3 Gzip Compression ;en_US
dc.description.tableofcontents1.2.3 Low Latency Transaction Processing Category1.2.3.1 HFTDemo; 1.2.4 Networking Category; 1.2.4.1 High-Speed Packet Capture; 1.2.4.2 Packet Pusher; 1.2.4.3 Low-Latency HTTP Web Server; 1.2.5 Science Category; 1.2.5.1 Reverse Time Migration; 1.2.5.2 Network Sorting; 1.2.5.3 Localization Microscopy; 1.2.6 Security Category; 1.2.6.1 Fully Homomorphic Encryption; References; 2 Discrepancy Reduction Between the Topology of Dataflow Graph and the Topology of FPGA Structure; 2.1 Introduction; 2.2 Dataflow Graph ;en_US
dc.description.tableofcontents2.3 Getting to Accelerated Application: Maxeler Way2.4 Simulation Debugging; 2.4.1 Simulation Watches; 2.4.2 Simulation printf; 2.5 Hardware Debugging; 2.5.1 DFE printf; 2.6 Advanced Debugging; 2.6.1 Introduction; 2.6.2 Kernel Halted on Input; 2.6.3 Kernel Halted on Output; 2.6.4 Stream Status Blocks; 2.6.5 Deadlock; 2.6.5.1 Deadlock Due To: Kernel Has Scheduled an Input Before an Output; 2.6.5.2 Deadlock Due to: FIFO Ends Up Full; 2.7 Effects of Inconsistency Between Simulation and Hardware; 2.7.1 Uninitialized Elements ;en_US
dc.description.tableofcontents2.7.2 Race Condition2.8 Embedded DFE Optimizations; 2.8.1 Kernel Optimizations; 2.8.1.1 Holistic Optimization; 2.8.1.2 Push-Pop Optimizations; 2.8.1.3 Placement Constraints; 2.8.1.4 Input Registering; 2.8.1.5 Per-Stream Optimizations; 2.8.2 Manager Optimizations; 2.8.2.1 LMem Clock Frequency; 2.8.2.2 Stream Clock Frequency; 2.9 Global DFE Optimization Practices: Getting Maximum Performance; 2.9.1 Introduction; 2.9.2 Dataflow Computing Strategy; 2.9.3 Fitting Procedure; 2.9.3.1 Techniques to Fit Designs Onto DFE ;en_US
dc.description.tableofcontents2.9.4 How to Make it Fite2.9.4.1 Stage 1: DFE Logic Utilization >100%: Macro-optimization; 2.9.4.2 Stage 2: DFE Logic Utilization >80% and <100%, Micro-optimizations; 2.9.4.3 Stage 3: DFE Logic Utilization <80%, Frequency Optimization; 2.9.5 Optimizing Memory Bound Applications: Data Size; 2.9.5.1 Differences in Memory Controllers of Different Cards; 2.9.5.2 Data-Specific Compression; 2.9.5.3 Data Encoding; 2.9.5.4 Reorganization of the Order of Computations; 2.9.6 Optimizing Compute Performance: Clock Frequency ;en_US
dc.format.extent1 online resource ;en_US
dc.format.extentIncludes bibliographical references and index ;en_US
dc.publisherSpringer,en_US
dc.relation.ispartofseriesComputer communications and networks ;en_US
dc.relation.ispartofseriesComputer communications and networks ;en_US
dc.relation.haspart9783319661285.pdfen_US
dc.subjectSupercomputers ;en_US
dc.subjectHigh performance computing ;en_US
dc.titleDataFlow supercomputing essentials :en_US
dc.title.alternativeresearch, development and education /en_US
dc.typeBooken_US
dc.publisher.placeCham :en_US
dc.classification.lcQA76.5 ;en_US
Appears in Collections:مهندسی فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9783319661285.pdf3.81 MBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMilutinoviee, Veljko ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:23:09Z-
dc.date.available2020-05-17T08:23:09Z-
dc.date.issued2017en_US
dc.identifier.isbn9783319661285 ; (electronic bk.) ;en_US
dc.identifier.isbn3319661280 ; (electronic bk.) ;en_US
dc.identifier.isbn9783319661278 ;en_US
dc.identifier.isbn3319661272 ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/891-
dc.descriptionOhio Library and Information Network ;en_US
dc.descriptionAvailable to OhioLINK libraries ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionPrint version: ; 3319661272 ; 9783319661278 ; (OCoLC)994791101 ;en_US
dc.descriptionen_US
dc.descriptionen_US
dc.description.abstractThis informative text/reference highlights the potential of DataFlow computing in research requiring high speeds, low power requirements, and high precision, while also benefiting from a reduction in the size of the equipment. The cutting-edge research and implementation case studies provided in this book will help the reader to develop their practical understanding of the advantages and unique features of this methodology. This work serves as a companion title to DataFlow Supercomputing Essentials: Algorithms, Applications and Implementations, which reviews the key algorithms in this area, and provides useful examples. Topics and features: Reviews the library of tools, applications, and source code available to support DataFlow programming Discusses the enhancements to DataFlow computing yielded by small hardware changes, different compilation techniques, debugging, and optimizing tools Examines when a DataFlow architecture is best applied, and for which types of calculation Describes how converting applications to a DataFlow representation can result in an acceleration in performance, while reducing the power consumption Explains how to implement a DataFlow application on Maxeler hardware architecture, with links to a video tutorial series available online This enlightening volume will be of great interest to all researchers investigating supercomputing in general, and DataFlow computing in particular. Advanced undergraduate and graduate students involved in courses on Data Mining, Microprocessor Systems, and VLSI Systems, will also find the book to be a helpful reference ;en_US
dc.description.statementofresponsibilityVeljko Milutinovic... [et al.]en_US
dc.description.tableofcontentsPreface; Dataflow Taxonomy; Maxeler; Research Issues; Application Issues; Conclusion; Contents; Part I Research; 1 Maxeler AppGallery Revisited; 1.1 Introduction; 1.2 Maxeler AppGallery; 1.2.1 Data Analytics Category; 1.2.1.1 Sequential Monte Carlo; 1.2.1.2 Real-Time VaR Monitoring; 1.2.1.3 Boosted Decision Tree Classifier; 1.2.1.4 Heston Option Pricer; 1.2.2 Engineering Category; 1.2.2.1 Motion Estimation; 1.2.2.2 Real-time 4k Ultra HD Video; 1.2.2.3 Gzip Compression ;en_US
dc.description.tableofcontents1.2.3 Low Latency Transaction Processing Category1.2.3.1 HFTDemo; 1.2.4 Networking Category; 1.2.4.1 High-Speed Packet Capture; 1.2.4.2 Packet Pusher; 1.2.4.3 Low-Latency HTTP Web Server; 1.2.5 Science Category; 1.2.5.1 Reverse Time Migration; 1.2.5.2 Network Sorting; 1.2.5.3 Localization Microscopy; 1.2.6 Security Category; 1.2.6.1 Fully Homomorphic Encryption; References; 2 Discrepancy Reduction Between the Topology of Dataflow Graph and the Topology of FPGA Structure; 2.1 Introduction; 2.2 Dataflow Graph ;en_US
dc.description.tableofcontents2.3 Getting to Accelerated Application: Maxeler Way2.4 Simulation Debugging; 2.4.1 Simulation Watches; 2.4.2 Simulation printf; 2.5 Hardware Debugging; 2.5.1 DFE printf; 2.6 Advanced Debugging; 2.6.1 Introduction; 2.6.2 Kernel Halted on Input; 2.6.3 Kernel Halted on Output; 2.6.4 Stream Status Blocks; 2.6.5 Deadlock; 2.6.5.1 Deadlock Due To: Kernel Has Scheduled an Input Before an Output; 2.6.5.2 Deadlock Due to: FIFO Ends Up Full; 2.7 Effects of Inconsistency Between Simulation and Hardware; 2.7.1 Uninitialized Elements ;en_US
dc.description.tableofcontents2.7.2 Race Condition2.8 Embedded DFE Optimizations; 2.8.1 Kernel Optimizations; 2.8.1.1 Holistic Optimization; 2.8.1.2 Push-Pop Optimizations; 2.8.1.3 Placement Constraints; 2.8.1.4 Input Registering; 2.8.1.5 Per-Stream Optimizations; 2.8.2 Manager Optimizations; 2.8.2.1 LMem Clock Frequency; 2.8.2.2 Stream Clock Frequency; 2.9 Global DFE Optimization Practices: Getting Maximum Performance; 2.9.1 Introduction; 2.9.2 Dataflow Computing Strategy; 2.9.3 Fitting Procedure; 2.9.3.1 Techniques to Fit Designs Onto DFE ;en_US
dc.description.tableofcontents2.9.4 How to Make it Fite2.9.4.1 Stage 1: DFE Logic Utilization >100%: Macro-optimization; 2.9.4.2 Stage 2: DFE Logic Utilization >80% and <100%, Micro-optimizations; 2.9.4.3 Stage 3: DFE Logic Utilization <80%, Frequency Optimization; 2.9.5 Optimizing Memory Bound Applications: Data Size; 2.9.5.1 Differences in Memory Controllers of Different Cards; 2.9.5.2 Data-Specific Compression; 2.9.5.3 Data Encoding; 2.9.5.4 Reorganization of the Order of Computations; 2.9.6 Optimizing Compute Performance: Clock Frequency ;en_US
dc.format.extent1 online resource ;en_US
dc.format.extentIncludes bibliographical references and index ;en_US
dc.publisherSpringer,en_US
dc.relation.ispartofseriesComputer communications and networks ;en_US
dc.relation.ispartofseriesComputer communications and networks ;en_US
dc.relation.haspart9783319661285.pdfen_US
dc.subjectSupercomputers ;en_US
dc.subjectHigh performance computing ;en_US
dc.titleDataFlow supercomputing essentials :en_US
dc.title.alternativeresearch, development and education /en_US
dc.typeBooken_US
dc.publisher.placeCham :en_US
dc.classification.lcQA76.5 ;en_US
Appears in Collections:مهندسی فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9783319661285.pdf3.81 MBAdobe PDFThumbnail
Preview File