Advances in computers Volume ninety-six, Dataflow processing Volume ninety-six, Dataflow processing /
Since its first volume in 1960, Advances in Computers has presented detailed coverage of innovations in computer hardware, software, theory, design, and applications. It has also provided contributors with a medium in which they can explore their subjects in greater depth and breadth than journal ar...
| Otros Autores: | , , , |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Waltham, Massachusetts :
Academic Press
2015.
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| Edición: | First edition |
| Colección: | Advances in computers,
96 |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009629568606719 |
Tabla de Contenidos:
- Front Cover; Dataflow Processing; Copyright; Contents; Preface; Chapter 1: An Overview of Selected Heterogeneous and Reconfigurable Architectures; 1. Introduction; 2. Problem Statement; 3. Existing Solutions and Their Criticism; 3.1. Presentation of Existing Solutions; 3.1.1. NVIDIA Fermi GPU; 3.1.2. AMD ATI; 3.1.3. Cell Broadband Engine Architecture; 3.1.4. ClearSpeed; 3.1.5. Maxeler Dataflow Engines; 3.1.6. SGI's Reconfigurable Application-Specific Computing; 3.1.7. Convey ́s Reconfigurable COP; 3.2. Classification of Presented Solutions; 4. Summary of Presented Solutions
- 4.1. Computation and Memory Capacity4.2. Programming Considerations; 5. Performance Comparison of Presented Solutions; 5.1. Analytical Comparison; 5.2. Experimental Comparison; 6. Conclusion; Acknowledgments; References; About the Author ; Chapter 2: Concurrency, Synchronization, and Speculation-The Dataflow Way; 1. Introduction; 2. Dataflow Concepts; 2.1. Dataflow Formalism; 2.2. Generalized Firing Semantic Sets (FSS); 2.3. Graphical Notations; 2.4. Concurrency; 2.5. Synchronization; 2.6. Speculation or Greedy Execution; 3. Dataflow Languages; 3.1. Dataflow Structures
- 3.1.1. Direct Access Method3.1.2. Indirect Access Method; 3.1.3. Dennis ́s Method; 3.1.4. I-Structures; 3.1.5. Hybrid Scheme; 3.2. Id: Irvine Dataflow Language; 3.3. VAL; 3.4. Streams and Iteration in a Single Assignment Language; 4. Historical Dataflow Architectures; 4.1. Dataflow Instructions; 4.1.1. Classical Architectures; 4.2. Static Dataflow Architectures; 4.3. Dynamic Dataflow Architectures; 4.4. Explicit Token Store; 4.5. Dataflow Limitations; 4.5.1. Localities and Memory Hierarchy; 4.5.2. Granularity of Computations; 4.5.3. Synchronous Execution; 4.5.4. Memory Ordering
- 4.6. Hybrid Dataflow/Controlflow Architectures4.6.1. Coarse-Grain Dataflow; 4.6.2. Complex Dataflow; 4.6.3. RISC Dataflow; 4.6.4. Threaded Dataflow; 5. Recent Dataflow Architectures; 5.1. Tera-op Reliable Intelligently Adaptive Processing System; 5.2. Data-Driven Workstation Network; 5.3. WaveScalar; 5.4. Teraflux; 5.5. Maxeler; 5.6. Codelet; 5.7. Recent Architectures Summary; 6. Case Study: Scheduled Dataflow; 6.1. Organization; 6.2. Instruction Format; 6.3. Execution Paradigm; 6.4. Architecture; 6.4.1. Synchronization Pipeline; 6.4.2. Execution Pipeline; 6.4.3. Scheduling Unit
- 6.5. Support for Thread-Level Speculation6.5.1. TLS Schema for SDF; 6.5.2. Speculation Extensions to SDF; 7. Conclusions; References; About the Author ; Chapter 3: Dataflow Computing in Extreme Performance Conditions; 1. Introduction; 2. Dataflow Computing; 3. Maxeler Multiscale DFEs; 4. Development Process; 4.1. Analysis; 4.2. Transformation; 4.3. Partitioning; 4.4. Implementation; 5. Programming with MaxCompiler; 6. Dataflow Clusters; 6.1. Power Efficient Computing; 6.2. Data Storage; 6.3. Interconnections; 6.4. Cluster-Level Management; 6.5. Reliability
- 7. Case Study: Meteorological Limited-Area Model
