Nowadays, parallel applications are used every day in high performance computing, scientific computing and also in everyday tasks due to the pervasiveness of multi-core architectures. However, several implementation challenges have so far stifled the integration of parallel applications and automatic precision tuning. First of all, tuning a parallel application introduces difficulties in the detection of the region of code that must be affected by the optimization. Moreover, additional challenges arise in handling shared variables and accumulators. In this work we address such challenges by introducing OpenMP parallel programming support to the TAFFO precision tuning framework. With our approach we achieve speedups up to 750% with respect to the same parallel application without precision tuning.

Precision Tuning in Parallel Applications

Gabriele Magnani;Lev Denisov;Daniele Cattaneo;Giovanni Agosta
2022-01-01

Abstract

Nowadays, parallel applications are used every day in high performance computing, scientific computing and also in everyday tasks due to the pervasiveness of multi-core architectures. However, several implementation challenges have so far stifled the integration of parallel applications and automatic precision tuning. First of all, tuning a parallel application introduces difficulties in the detection of the region of code that must be affected by the optimization. Moreover, additional challenges arise in handling shared variables and accumulators. In this work we address such challenges by introducing OpenMP parallel programming support to the TAFFO precision tuning framework. With our approach we achieve speedups up to 750% with respect to the same parallel application without precision tuning.
2022
13th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 11th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2022)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1217631
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