@inproceedings{Wal2015,Author = {Jörg Walter and Wolfgang Nebel},Title = {Energy-Aware Mapping and Scheduling of Large-Scale Macro Data-Flow Applications},Year = {2015},Month = {01},Booktitle = {1st International Workshop on Investigating Dataflow in Embedded Computing Architecture (IDEA 2018)},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.}}@COMMENT{Bibtex file generated on }