A3 Methods for Efficient Resource Utilization in Machine Learning Algorithms
- Prof. Dr. Jörg Rahnenführer
- Prof. Dr. Peter Marwedel
This subproject builds a bridge between learning algorithms and resource efficiency.
Statistical learning algorithms are optimized with respect to resource requirements and methods for the calculation of resource utilization
for different compiler strategies are developed. For the first time, the level of compilation of R programs is connected with the level of algorithms and model choice in order to decrease resource requirements. The potential gain in resource efficiency will be evaluated for these new approaches.
Publications
- [1] Alexa, A.:
topGO: Enrichment analysis for Gene Ontology. http://www.
bioconductor.org/packages/release/bioc/html/topGO.html, 2009.
- [2] Alexa, A., J. Rahnenführer und T. Lengauer:
Improved scoring
of functional groups from gene expression data by decorrelating GO graph
structure. Bioinformatics, 22(13):1600–1607, Jul 2006.
- [3] ArtistDesign Consortium:
ArtistDesign home page.
http://www.artist-embedded.org, 2010.
- [4] Beerenwinkel, N., J. Rahnenführer, M. Däumer, D. Hoffmann,
R. Kaiser, J. Selbig und T. Lengauer:
Learning multiple evolutionary
pathways from cross-sectional data. J Comput Biol, 12(6):584–598, 2005.
- [5] Bogojeska, J., A. Alexa, A. Altmann, T. Lengauer und J. Rahnenführer:
Rtreemix: an R package for estimating evolutionary pathways
and genetic progression scores. Bioinformatics, 24(20):2391–2392,
Oct 2008.
- [6] Bogojeska, J., T. Lengauer und J. Rahnenführer:
Stability analysis
of mixtures of mutagenetic trees. BMC Bioinformatics, 9:165, 2008.
- [7] Falk, H., P. Lokuciejewski und H. Theiling:
Design of a WCETAware
C Compiler. In: 4th IEEE Workshop on Embedded Systems for
Real-Time Multimedia (ESTIMedia), S. 121–126, Seoul/Korea, Okt. 2006.
- [8] Falk, H. und M. Schwarzer:
Loop Nest Splitting for WCETOptimization
and Predictability Improvement. In: 4th IEEE Workshop on
Embedded Systems for Real-Time Multimedia (ESTIMedia), S. 115–120,
Seoul/Korea, Oct 2006.
- [9] Falk, H., J. Wagner und A. Schaefer:
Use of a Bit-true Data Flow
Analysis for Processor-Specific Source Code Optimization. In: 4th IEEE
Workshop on Embedded Systems for Real-Time Multimedia (ESTIMedia),
S. 133–138, Seoul/Korea, Oct 2006.
- [10] ICD e.V.:
ICD-C home page. http://www.icd.de/es, 2009.
- [11] Lohr, M., P. Godoy, J. G. Hengstler, J. Rahnenführer und
M. Grzegorczyk:
Extracting differential regulatory sub-networks from
genome-wide microarray expression data. In: Proceedings of the Seventh
International Workshop on Computational Systems Biology (WCSB
2010), Luxembourg, June 2010.
- [12] Lokuciejewski, P., F. Gedikli, P. Marwedel und K. Morik:
Automatic
WCET Reduction by Machine Learning Based Heuristics for Function
Inlining. In: Proceedings of the 3rd Workshop on Statistical and Machine
Learning Approaches to ARchitectures and CompilaTion (SMART),
S. 1–15, Paphos / Cyprus, Jan. 2009.
- [13] Marwedel, P.:
1st Workshop on Mapping of Applications to MPSoCs.
http://www.artist-embedded.org/artist/-map2mpsoc-2008-.html, 2008.
- [14] Marwedel, P.:
2nd Workshop on Mapping of Applications to MPSoCs.
http://www.artist-embedded.org/artist/-map2mpsoc-2009-.html, 2009.
- [15] Marwedel, P. und G. Goossens (Hrsg.):
Code Generation for Embedded
Processors. Kluwer Academic Publishers, 1995.
- [16] Mnemee Consortium:
Mnemee home page. http://www.mnemee.org,
2010.
- [17] Plazar, S., P. Lokuciejewski und P. Marwedel:
A Retargetable
Framework for Multi-objective WCET-aware High-level Compiler Optimizations.
In: Proceedings of The 29th IEEE Real-Time Systems Symposium
(RTSS) WiP, S. 49–52, Barcelona / Spain, Dec 2008.
- [18] Plazar, S., P. Marwedel und J. Rahnenführer:
Optimizing Execution
Runtimes of R Programs. In: Book of Abstracts of ISBIS-2010
(International Symposium on Business and Industrial Statistics), Portorose,
Slovenia, Jul 2010.
- [19] Podwojski, K., A. Fritsch, D. C. Chamrad, W. Paul, B. Sitek,
K. Stühler, P. Mutzel, C. Stephan, H. E. Meyer, W. Urfer,
K. Ickstadt und J. Rahnenführer:
Retention time alignment algorithms
for LC/MS data must consider non-linear shifts. Bioinformatics,
25(6):758–764, Mar 2009.
- [20] Predator Consortium:
Predator home page. http://www.predatorproject.
eu, 2009.
- [21] Rahnenführer, J., N. Beerenwinkel, W. A. Schulz, C. Hartmann,
A. von Deimling, B. Wullich und T. Lengauer:
Estimating
cancer survival and clinical outcome based on genetic tumor progression
scores. Bioinformatics, 21(10):2438–2446, May 2005.
- [22] Rahnenführer, J. und D. Bozinov:
Hybrid clustering for microarray
image analysis combining intensity and shape features. BMC Bioinformatics,
5:47, Apr 2004.
- [23] Rahnenführer, J., F. S. Domingues, J. Maydt und T. Lengauer:
Calculating the statistical significance of changes in pathway activity from
gene expression data. Stat Appl Genet Mol Biol, 3:Article16, 2004.
- [24] Steinke, S., M. Knauer, L. Wehmeyer und P. Marwedel:
An Accurate
and Fine Grain Instruction-Level Energy Model Supporting Software
Optimizations. Proc. of the International Workshop on Power and Timing
Modeling, Optimization and Simulation (PATMOS), 2001.
- [25] Steinke, S., L. Wehmeyer, B.-S. Lee und P. Marwedel:
Assigning
Program and Data Objects to Scratchpad for Energy Reduction. Design,
Automation and Test in Europe (DATE), S. 409–417, 2002.
- [26] Verma, M. und P. Marwedel:
Advanced Memory Optimization Techniques
for Low-Power Embedded Processors. Springer, 2007. ISBN-13-
978-1-4020-5897-4 (e-book).
- [27] Wehmeyer, L. und P. Marwedel:
Fast, Efficient and Predictable Memory
Accesses. Springer, 2006.
- [28] Whalley, D.:
4th Workshop on Statistical and Machine learning approaches
to ARchitecture and compilaTion (SMART’10). http://ctuning.org/
workshop-smart10, 2009.
- [29] Yin, J., N. Beerenwinkel, J. Rahnenführer und T. Lengauer:
Model selection for mixtures of mutagenetic trees. Stat Appl Genet Mol
Biol, 5:Article17, 2006.
Publications (State of the Art)
