Tim Hegeman

Ph.D. student, Vrije Universiteit Amsterdam
Project Lead Grade10 project
Tech Lead Graphalytics project

Research Focus
Identification and analysis of bottlenecks and performance issues for graph-processing systems/Long-term interest in big data systems

Contact

Links

Publications

Publications
GradeML: Towards Holistic Performance Analysis for Machine Learning Workflows
HotCloudPerf 2021
PDF
Grade10: A Framework for Performance Characterization of Distributed Graph Processing
IEEE International Conference on Cluster Computing (CLUSTER)
PDF
The Workflow Trace Archive: Open-Access Data from Public and Private Computing Infrastructures
IEEE Transactions on Parallel and Distributed Systems (TPDS) 2020
PDF
Massivizing Computer Systems: a Vision to Understand, Design, and Engineer Computer Ecosystems through and beyond Modern Distributed Systems
International Conference on Distributed Computing Systems 2018
PDF
Granula: Toward Fine-grained Performance Analysis of Large-scale Graph Processing Platforms.
GRADES@SIGMOD/PODS 2017: 8:1-8:6
PDF
Towards the Next Generation of Large-Scale Network Archives.
Euro-Par Workshops 2016: 571-579
PDF
LDBC Graphalytics: A Benchmark for Large-Scale Graph Analysis on Parallel and Distributed Platforms
PVLDB 9(13): 1317-1328 (2016)
V for Vicissitude: The Challenge of Scaling Complex Big Data Workflows
CCGRID 2014: 927-932
PDF
Mnemos: Self-Expressive Management of Business-Critical Workloads in Virtualized Datacenters
IEEE Computer 48(7): 46-54 (2015)
PDF
Towards Benchmarking IaaS and PaaS Clouds for Graph Analytics.
WBDB 2014: 109-131
PDF
The BTWorld use case for big data analytics: Description, MapReduce logical workflow, and empirical evaluation
2013, IEEE International Conference on Big Data (IEEE BigData)
PDF

Master Thesis
Experimental Performance Analysis of Graph Analytics Frameworks

Bachelor Thesis
Nebu: A topology-aware deployment system for reliable virtualized multi-cluster environments

Literature Survey
Survey of Graph Analysis Applications