Christopher Hagedorn

Name at Birth: Christopher Schmidt

Research Assistant, PhD Candidate

Phone:	+49 (331) 5509 - 1317
Fax:	+49 (331) 97992 - 579
E-Mail:	christopher.hagedorn@hpi.de
Room:	Hasso-Plattner-Villa, V 2.01

Research

Parallel Execution Strategies for Causal Structure Learning on GPUs

Learning causal relationships from observational data is insightful for researchers in multiple domains. For example, in genetic research, gene regulatory networks can be derived from gene expression data. Real world gene expression datasets are often high-dimensional, resulting in long execution times prohibiting the application of constraint-based Causal Structure Learning (CSL) algorithms in practice.
As part of our research on Data-Driven Causal Inference we investigate the adaptation of existing CSL algorithms to utilize parallel processing capabilities of modern hardware in order to speed-up execution. This fosters the application of CSL in real-world settings, both in industry and in research. On multi-core CPUs, we introduce dynamic load-balancing for parallel execution of CSL algorithms to avoid situations of under- or overutilization of compute resources to effectively reduce runtimes.
In recent years, GPUs have advanced to become a source for massive parallel processing. By utilizing the thousands of parallel processing units and shared memory in GPUs, we achieve a runtime improvement by up to two orders of magnitude for multivariate normal distributed data.
In a next step, we will generalize our GPU-accelerated algorithm to fit different data distributions. For this purpose, we develop a definition of tasks for parallel execution independent of the current data distribution. Such tasks support fine-grained parallelism, e.g., to speed-up processing of raw observational data during conditional independence tests.

Teaching Activities

Winter Term 2020/21

Master's Project: A Benchmark Suite for Causal Inference or “How to model a complex world?”

Summer Term 2020

Winter Term 2019/20

Summer Term 2019

Winter Term 2018/19

Summer Term 2018

Winter Term 2017/2018

Summer Term 2017

Winter Term 2016/2017

Publications

Huegle, J., Hagedorn, C., Uflacker, M.: Unterstützte Fehlerbehebung durch kausales Strukturwissen in Überwachungssystemen der Automobilfertigung. In: Götz, S., Linsbauer, L., Schaefer, I., and Wortmann, A. (eds.) Software Engineering 2021 Satellite Events, Lecture Notes in Informatics (LNI). Gesellschaft für Informatik, Bonn (2021).
[ BibTeX ] [ URL ]

@inproceedings{huegle2021untersttzte, address = {Bonn}, author = {Huegle, Johannes and Hagedorn, Christopher and Uflacker, Matthias}, booktitle = {Software Engineering 2021 Satellite Events, Lecture Notes in Informatics (LNI)}, editor = {Götz, Sebastian and Linsbauer, Lukas and Schaefer, Ina and Wortmann, Andreas}, keywords = {Causal_Structure_Learning}, publisher = {Gesellschaft für Informatik}, title = {Unterstützte Fehlerbehebung durch kausales Strukturwissen in Überwachungssystemen der Automobilfertigung}, year = 2021 }
Huegle, J., Hagedorn, C., Uflacker, M.: How Causal Structural Knowledge Adds Decision-Support in Monitoring of Automotive Body Shop Assembly Lines. In: Bessiere, C. (ed.) Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI-20. p. 5246--5248. International Joint Conferences on Artificial Intelligence Organization (2020).
[ BibTeX ] [ URL ] [ DOI ]

@inproceedings{huegle2020causal, author = {Huegle, Johannes and Hagedorn, Christopher and Uflacker, Matthias}, booktitle = {Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, {IJCAI-20}}, editor = {Bessiere, Christian}, keywords = {causal_inference}, note = {Demos}, pages = {5246–5248}, publisher = {International Joint Conferences on Artificial Intelligence Organization}, title = {How Causal Structural Knowledge Adds Decision-Support in Monitoring of Automotive Body Shop Assembly Lines}, year = 2020 }
Schmidt, C., Huegle, J.: Towards a GPU-Accelerated Causal Inference.HPI Future SOC Lab - Proceedings 2017. pp. 187-194 (2020).
[ BibTeX ] [ DOI ]

@inproceedings{schmidt2020towards, author = {Schmidt, Christopher and Huegle, Johannes}, booktitle = {HPI Future SOC Lab - Proceedings 2017}, keywords = {gpu_acceleration causal_inference}, pages = {187-194}, title = {Towards a GPU-Accelerated Causal Inference}, year = 2020 }
Schmidt, C., Huegle, J., Horschig, S., Uflacker, M.: Out-of-Core GPU-Accelerated Causal Structure Learning.Algorithms and Architectures for Parallel Processing. ICA3PP 2019. p. 89--104. Springer International Publishing (2020).
[ BibTeX ] [ URL ] [ Download ]

@inproceedings{schmidt2020outofcore, author = {Schmidt, Christopher and Huegle, Johannes and Horschig, Siegfried and Uflacker, Matthias}, booktitle = {Algorithms and Architectures for Parallel Processing. ICA3PP 2019}, keywords = {gpu_acceleration causal_inference}, pages = {89–104}, publisher = {Springer International Publishing}, title = {Out-of-Core GPU-Accelerated Causal Structure Learning}, year = 2020 }
Schmidt, C., Huegle, J., Bode, P., Uflacker, M.: Load-Balanced Parallel Constraint-Based Causal Structure Learning on Multi-Core Systems for High-Dimensional Data.SIGKDD Workshop on Causal Discovery. p. 59--77 (2019).
[ BibTeX ] [ URL ]

@inproceedings{schmidt2019loadbalanced, author = {Schmidt, Christopher and Huegle, Johannes and Bode, Philipp and Uflacker, Matthias}, booktitle = {SIGKDD Workshop on Causal Discovery}, keywords = {causal_inference}, pages = {59–77}, series = {Proceedings of Machine Learning Research}, title = {Load-Balanced Parallel Constraint-Based Causal Structure Learning on Multi-Core Systems for High-Dimensional Data}, volume = 104, year = 2019 }
Schmidt, C., Uflacker, M.: Workload-Driven Data Placement for GPU-Accelerated Database Management Systems.Datenbanksysteme für Business, Technologie und Web BTW 2019, 18. Fachtagung des GI-Fachbereichs ,,Datenbanken und Informationssysteme" (DBIS), 4.-8. März 2019, Rostock, Germany, Workshopband (2019).
[ BibTeX ] [ URL ] [ DOI ]

@inproceedings{schmidt2019workloaddriven, author = {Schmidt, Christopher and Uflacker, Matthias}, booktitle = {Datenbanksysteme für Business, Technologie und Web BTW 2019, 18. Fachtagung des GI-Fachbereichs ,,Datenbanken und Informationssysteme" (DBIS), 4.-8. März 2019, Rostock, Germany, Workshopband}, keywords = {in-memory_database gpu_acceleration}, title = {Workload-Driven Data Placement for GPU-Accelerated Database Management Systems}, year = 2019 }
Schmidt, C., Huegle, J., Uflacker, M.: Order-independent constraint-based causal structure learning for gaussian distribution models using GPUs.SSDBM '18 Proceedings of the 30th International Conference on Scientific and Statistical Database Management. p. 19:1--19:10. ACM, New York, NY, USA (2018).
[ BibTeX ] [ URL ] [ DOI ] [ Download ]

@inproceedings{schmidt2018orderindependent, address = {New York, NY, USA}, author = {Schmidt, Christopher and Huegle, Johannes and Uflacker, Matthias}, booktitle = {SSDBM '18 Proceedings of the 30th International Conference on Scientific and Statistical Database Management}, keywords = {gpu_acceleration causal_inference}, pages = {19:1–19:10}, publisher = {ACM}, series = {SSDBM '18}, title = {Order-independent constraint-based causal structure learning for gaussian distribution models using GPUs}, year = 2018 }
Schmidt, C., Dreseler, M., Akin, B., Roy, A.: A Case for Hardware-Supported Sub-Cache Line Accesses.Data Management on New Hardware (DaMoN), in conjunction with SIGMOD (2018).
[ BibTeX ] [ DOI ] [ Download ]

@inproceedings{schmidt2018hardwaresupported, author = {Schmidt, Christopher and Dreseler, Markus and Akin, Berkin and Roy, Amithaba}, booktitle = {Data Management on New Hardware (DaMoN), in conjunction with SIGMOD}, keywords = {hyrise}, title = {A Case for Hardware-Supported Sub-Cache Line Accesses}, year = 2018 }
Schwarz, C., Schmidt, C.: Interactive Product Cost Simulation on Coprocessors.HPI Future SOC Lab: Proceedings 2015. pp. 103-107 (2017).
[ BibTeX ]

@inproceedings{schwarz2017interactive, author = {Schwarz, Christian and Schmidt, Christopher}, booktitle = {HPI Future SOC Lab: Proceedings 2015}, keywords = {in-memory_database product_cost_calculation business_data_processing enterprise_coprocessing}, pages = {103-107}, title = {Interactive Product Cost Simulation on Coprocessors}, year = 2017 }
Schwarz, C., Schmidt, C., Hopstock, M., Sinzig, W., Plattner, H.: Efficient Calculation and Simulation of Product Cost Leveraging In-Memory Technology and Coprocessors.The Sixth International Conference on Business Intelligence and Technology (BUSTECH 2016) (2016).
[ BibTeX ]

@conference{Christian2016a, author = {Schwarz, Christian and Schmidt, Christopher and Hopstock, Michael and Sinzig, Werner and Plattner, Hasso}, booktitle = {The Sixth International Conference on Business Intelligence and Technology (BUSTECH 2016)}, keywords = {in-memory_database product_cost_calculation business_data_processing enterprise_coprocessing}, title = {Efficient Calculation and Simulation of Product Cost Leveraging In-Memory Technology and Coprocessors}, year = 2016 }

Christopher Hagedorn

Name at Birth: Christopher Schmidt

Research Assistant, PhD Candidate

Research

Parallel Execution Strategies for Causal Structure Learning on GPUs

Teaching Activities

Publications

Open Positions

News

19.11.2020 | Best Paper Award received at CSEE&T 2020

28.07.2020 | "An Experimental Evaluation of Index Selection Algorithms" published in PVLDB

04.05.2020 | "Quantifying TPC-H Choke Points and Their Optimizations" published in PVLDB

01.05.2020 | Change of Chair Representation

03.03.2020 | Best Master Thesis in Education Technologies 2019

Literature

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