An Automated Approach for Estimating the Memory Footprint of Non-Linear Data Objects

Please always quote using this URN: urn:nbn:de:0297-zib-42224
  • Current programming models for heterogeneous devices with disjoint physical memory spaces require explicit allocation of device memory and explicit data transfers. While it is quite easy to manually implement these operations for linear data objects like arrays, this task becomes more difficult for non-linear objects, e.g. linked lists or multiple inherited classes. The difficulties arise due to dynamic memory requirements at run-time and the dependencies between data structures. In this paper we present a novel method to build a graph-based static data type description which is used to create code for injectable functions that automatically determine the memory footprint of data objects at run-time. Our approach is extensible to implement automatically generated optimized data transfers across physical memory spaces.

Download full text files

Export metadata

  • Export Bibtex
Metadaten
Author:Sebastian Dreßler, Thomas Steinke
Document Type:ZIB-Report
Tag:dynamic analysis; memory footprint; non-linear objects; static analysis
CCS-Classification:E. Data
Date of first Publication:2013/08/30
Series (Serial Number):ZIB-Report (13-46)
ISSN:1438-0064
Published in:Appeared in: Euro-Par 2013: Parallel Processing Workshops. Lecture Notes in Computer Science 8374. 2014, pp. 249-258
DOI:http://dx.doi.org/10.1007/978-3-642-54420-0_25
Licence (German):License LogoCreative Commons - Namensnennung-Nicht kommerziell-Keine Bearbeitung

$Rev: 13581 $