Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  describes a high-level library (The Nearest Neighbor Tool, NNT) that has been used to parallelize operational ather prediction models. NNT is part of the Scalable Modeling System (SMS), developed at the Forecast Systems Laboratory (FSL). Programs written in NNT rely on SMS's run-time system and port beten a wide range of computing platforms, performing ll in multiprocessor systems.  show, using examples from operational ather models, how large Fortran 77 codes can be parallelized using NNT.  compare the ease of programmability of NNT and High Performance Fortran (HPF).  also discuss optimizations like data movement overlap (in interprocessor communication and I/O operations), and the minimization of data exchanges through the use of redundant computations.  show that although HPF provides a simpler programming interface, NNT allows for program optimizations that increase performance considerably and still keeps a simple user interface. These optimizations have proven essential to run ather prediction models in real time, and HPF compilers should incorporate them in order to meet operational demands. Throughout the paper,  present performance results of ather models running on a network of workstations, the Intel Paragon, and the SGI Challenge. Finally,  study the cost of programming global address space architectures with NNT's local address space paradigm.
['Bernardo Rodriguez', 'Leslie Hart', 'Tom Henderson']
I am writing a research paper on a idea Parallelizing Operational Weather Forecast Models for Portable and Fast Execution
[{"from": "human", "value": "I am writing a research paper on a idea Parallelizing Operational Weather Forecast Models for Portable and Fast Execution"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  describes a high-level library (The Nearest Neighbor Tool, NNT) that has been used to parallelize operational ather prediction models. NNT is part of the Scalable Modeling System (SMS), developed at the Forecast Systems Laboratory (FSL). Programs written in NNT rely on SMS's run-time system and port beten a wide range of computing platforms, performing ll in multiprocessor systems.  show, using examples from operational ather models, how large Fortran 77 codes can be parallelized using NNT.  compare the ease of programmability of NNT and High Performance Fortran (HPF).  also discuss optimizations like data movement overlap (in interprocessor communication and I/O operations), and the minimization of data exchanges through the use of redundant computations.  show that although HPF provides a simpler programming interface, NNT allows for program optimizations that increase performance considerably and still keeps a simple user interface. These optimizations have proven essential to run ather prediction models in real time, and HPF compilers should incorporate them in order to meet operational demands. Throughout the paper,  present performance results of ather models running on a network of workstations, the Intel Paragon, and the SGI Challenge. Finally,  study the cost of programming global address space architectures with NNT's local address space paradigm."}]