Developing Data Redistribution Algorithms
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Purpose[edit | edit source]
- Developing Communication Models that can represent the characteristics about each communication link and its bandwidth.
- Developing Data Redistribution Algorithms using AI techniques.
- Verifying Algorithms by using NOC SystemC Simulators.
Idea Sketch[edit | edit source]
- Idea.1.A (pdf)
Communication Patterns and Models[edit | edit source]
Parallel Prefix Sum[edit | edit source]
FFT[edit | edit source]
Redistribution Algorithms using a Generalized Circulant Matrix[edit | edit source]
Applying Sudoku Problems to Data Redistribution[edit | edit source]
Sudoku Codes in Haskell[edit | edit source]
from [ Haskell_programming_in_plain_view ]
- Sudoku Background (pdf)
- Bird's Implementation
Sudoku Codes in Prolog[edit | edit source]
Finding relationship with other algorithms[edit | edit source]
FFT Algorithms using a Tensor Product[edit | edit source]
FFT Algorithms using a Mixed Radix[edit | edit source]
Background[edit | edit source]
- Y. Ishikawa : "Efficient Collective Operations for Clusters in Long-and-Fast Networks"
- R. V. de Geijn : "Collective Communications on Architectures that Support Simultaneous Communications over Multiple Links"
- R. Rabenseifner : "Optimization of Collective Communication Operations in MPICH"
- NoC Simulator
- - NIRGAM (SystemC)- University of Southampton, 2007
- - OCCN (SystemC) - ST Microelectronics, 2005
- - TOPAZ (C++) - University of Cantabria, 2012
- - HNoCs (OMNeT++) - Technion, 2011
- MPI+NOC Literature to be surveyed.
- Y. W. Lim : "Efficient algorithms for block-cyclic redistribution of arrays", 1999
- Circulant Matrix based redistribution (pdf)
go to [ Electrical_&_Computer_Engineering_Studies ]
* Idea.2.A (pdf) moved to CORDIC Hardware Implementations