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Lift: a Functional Approach to Generating High Performance GPU Code using Rewrite RulesToomas RemmelgMichel SteuwerChristophe DubachThe 4th South of England Regional Programming Language Seminar 27th
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Lift a functional data-parallel is a method used to enable data processing tasks to be performed in parallel, making the evaluation of functions over collections of data more efficient and streamlined.
Individuals or organizations that are involved in data-intensive applications or those utilizing data-parallel computing frameworks may be required to file lift a functional data-parallel.
To fill out lift a functional data-parallel, users should provide details regarding their data processing tasks, specify the functions to be applied, and outline the data structures used for parallel execution.
The purpose of lift a functional data-parallel is to enhance the performance of data processing by utilizing parallel execution, thereby improving the speed and efficiency of computations over large datasets.
Information to be reported includes the type of data being processed, the functional operations applied, computational resources utilized, and the performance metrics of the parallel execution.
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