@misc{DresslerSteinke2013, author = {Dreßler, Sebastian and Steinke, Thomas}, title = {Automated Analysis of Complex Data Objects}, series = {28th International Supercomputing Conference, ISC 2013, Leipzig, Germany, June 16-20, 2013}, journal = {28th International Supercomputing Conference, ISC 2013, Leipzig, Germany, June 16-20, 2013}, year = {2013}, language = {en} } @article{GrunzkeBreuersGesingetal.2013, author = {Grunzke, Richard and Breuers, Sebastian and Gesing, Sandra and Herres-Pawlis, Sonja and Kruse, Martin and Blunk, Dirk and de la Garza, Luis and Packschies, Lars and Sch{\"a}fer, Patrick and Sch{\"a}rfe, Charlotta and Schlemmer, Tobias and Steinke, Thomas and Schuller, Bernd and M{\"u}ller-Pfefferkorn, Ralph and J{\"a}kel, Ren{\´e} and Nagel, Wolfgang and Atkinson, Malcolm and Kr{\"u}ger, Jens}, title = {Standards-based metadata management for molecular simulations}, series = {Concurrency and Computation: Practice and Experience}, journal = {Concurrency and Computation: Practice and Experience}, doi = {10.1002/cpe.3116}, year = {2013}, language = {en} } @inproceedings{WendeSteinke, author = {Wende, Florian and Steinke, Thomas}, title = {Swendsen-Wang Multi-Cluster Algorithm for the 2D/3D Ising Model on Xeon Phi and GPU}, series = {Proceeding SC '13 Proceedings of SC13: International Conference for High Performance Computing, Networking, Storage and Analysis Article No. 83 ACM New York, NY, USA, 2013}, booktitle = {Proceeding SC '13 Proceedings of SC13: International Conference for High Performance Computing, Networking, Storage and Analysis Article No. 83 ACM New York, NY, USA, 2013}, doi = {http://dx.doi.org/10.1145/2503210.2503254}, language = {en} } @misc{DresslerSteinke, author = {Dreßler, Sebastian and Steinke, Thomas}, title = {An Automated Approach for Estimating the Memory Footprint of Non-Linear Data Objects}, issn = {1438-0064}, doi = {10.1007/978-3-642-54420-0_25}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-42224}, abstract = {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.}, language = {en} } @misc{WendeSteinke, author = {Wende, Florian and Steinke, Thomas}, title = {Swendsen-Wang Multi-Cluster Algorithm for the 2D/3D Ising Model on Xeon Phi and GPU}, issn = {1438-0064}, doi = {10.1145/2503210.2503254}, url = {http://nbn-resolving.de/urn:nbn:de:0297-zib-42187}, abstract = {Simulations of the critical Ising model by means of local update algorithms suffer from critical slowing down. One way to partially compensate for the influence of this phenomenon on the runtime of simulations is using increasingly faster and parallel computer hardware. Another approach is using algorithms that do not suffer from critical slowing down, such as cluster algorithms. This paper reports on the Swendsen-Wang multi-cluster algorithm on Intel Xeon Phi coprocessor 5110P, Nvidia Tesla M2090 GPU, and x86 multi-core CPU. We present shared memory versions of the said algorithm for the simulation of the two- and three-dimensional Ising model. We use a combination of local cluster search and global label reduction by means of atomic hardware primitives. Further, we describe an MPI version of the algorithm on Xeon Phi and CPU, respectively. Significant performance improvements over known im plementations of the Swendsen-Wang algorithm are demonstrated.}, language = {en} }