@inproceedingsWal2015, Author = {Walter, Jörg and Nebel, Wolfgang}, Title = {Energy-Aware Mapping and Scheduling of Large-Scale Macro Data-Flow Applications}, Year = {2015}, Month = {1}, Booktitle = {1st International Workshop on Investigating Dataflow in Embedded Computing Architecture}, type = {inproceedings}, note = {Predicting the performance of parallel programs for large-scale parallel platforms is difficult due to the disparity between development system and target platform. Additionally, energy efficiency is becoming a universal concern, and platforms move toward}, Abstract = {Predicting the performance of parallel programs for large-scale parallel platforms is difficult due to the disparity between development system and target platform. Additionally, energy efficiency is becoming a universal concern, and platforms move towards highly heterogeneous systems containing GPUs, FPGAs, and other unconventional processing elements.In this paper we propose a static macro data-flow mapping and scheduling tool that is able to handle large parallel applications targeting heterogeneous platforms. It optimizes overall run time and energy consumption at the same time with a user-configurable cost function, allowing a selectable trade-off between both properties.} @COMMENTBibtex file generated on