GemStone is a suite of five software tools that, together, identify and evaluate the sources of error in gem5 models against a reference hardware (HW) platform by utilising statistical and machine learning approaches. Independently, the tools serve many purposes:
An interactive results visualiser dynamically creates detailed graphs and tables of the results when the results files are drag-and-dropped into the webpage – click on the links under ‘View Existing Results’ to see examples.
More details of our methodology can be found in the following publications:
M J. Walker, S. Diestelhorst, S. Bischoff, G. V. Merrett and B. Al-Hashimi Hardware-Validated CPU Performance and Energy Modelling in IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), April 2018.
For more information, and to download the tool, visit www.gemstone.ecs.soton.ac.uk.