Talks
2024
• Aleš Zamuda “Deployment of Randomised Optimisation Algorithms Benchmarking in DAPHNE” (HiPEAC’24 workshop: EVEREST + DAPHNE: Workshop on Design and Programming High- performance, distributed, reconfigurable and heterogeneous platforms for extreme-scale analytics)
• Patrick Damme “EVEREST + DAPHNE: Workshop on Design and Programming High- performance, distributed, reconfigurable and heterogeneous platforms for extreme-scale analytics (at HiPEAC 2024)”
• Jonas H. Müller Korndörfer “HiPEAC, EVEREST + DAPHNE: Workshop on Design and Programming High- performance, distributed, reconfigurable and heterogeneous platforms for extreme-scale analytics” (HIPEAC 24)
• Florina M. Ciorba “Leogang HPC Workshop”
Events, we have organized or co-organized:
• Alexander Krause “F4HD: FPGA/xPU Accelerators for Future HPC and Datacenter” (HiPEAC Workshop)
• Aleš Zamuda “DAPHNE Symposium” (University of Maribor)
• Wolfgang Lehner “DFG-funded SPP 2037 priority program on “Scalable Data Management for Future Hardware”
• Pınar Tözün, Raghavendra Selvan “Session at D3A conference”
• Matthias Boehm, Patrick Damme “EVEREST+DAPHNE” (HIPEAC 24)
2023
• Patrick Damme “Optimizing Tensor Computations: From Applications to Compilation and Runtime Techniques” (CDMS@VLDB 2023)
• Patrick Damme “Enabling Integrated Data Analysis Pipelines on Heterogeneous Hardware through Holistic Extensibility” (2nd Workshop on Novel Data Management Ideas on Heterogeneous Hardware Architectures (NoDMC@BTW 2023))
• Matthias Boehm “System Infrastructure for Data-centric ML Pipelines” (Seminar of the Large-scale Data and Systems Group at Imperial Collage London)
• Matthias Boehm “System Infrastructure for Data-centric ML Pipelines” (Friedrich-Schiller-Universität Jena)
• Matthias Boehm “System Infrastructure for Data-centric ML Pipelines” (HPI Lecture Series on Database Research)
• Matthias Boehm “System Infrastructure for Data-centric ML Pipelines” (Dresdner Datenbankforum at HTW Dresden)
• Matthias Boehm “System Infrastructure for Data-centric ML Pipelines” (ADBIS 2023)
• Matthias Boehm “System Infrastructure for Data-centric ML Pipelines” (CASTOR Software Days 2023)
• Matthias Boehm, Matteo Interlandi, Chris Jermaine “Optimizing Tensor Computations: From Applications to Compilation and Runtime Techniques” (SIGMOD 2023)
• Matthias Boehm “System Infrastructure for Data-centric ML Pipelines – Balancing Automation and Manual Control” (IBM Data Science Denmark)
• Matthias Boehm “System Infrastructure for Data-centric ML Pipelines – Balancing Automation and Manual Control” (TAFF Talks TU Delft)
• Matthias Boehm “Learned Multiplexing of Redundancy-exploiting Techniques for Data-centric ML Pipelines” (FLML Workshop Rice University)
• Matthias Boehm “Towards Holistic Redundancy Exploitation for Data-centric ML Pipelines” (ITU Copenhagen RAD workshop)
• Pınar Tözün “Different Scales of Resource-Aware Deep Learning and How to Tackle Them” (Systems Group, ETH Zurich)
• Pınar Tözün “Different Scales of Resource-Aware Deep Learning and How to Tackle Them” (Systems Group, ETH Zurich)
• Pınar Tözün “Different Scales of Resource-Aware Deep Learning and How to Tackle Them” (DIAS lab, EPFL)
• Pınar Tözün “Different Scales of Resource-Aware Deep Learning and How to Tackle Them” (eXascale Infolab, University of Fribroug)
• Pınar Tözün “Different Scales of Resource-Aware Deep Learning and How to Tackle Them” (Databricks, Amsterdam)
• Pınar Tözün “Different Scales of Resource-Aware Deep Learning and How to Tackle Them” (INDE Lab, University of Amsterdam)
• Pınar Tözün “Different Scales of Resource-Aware Deep Learning and How to Tackle Them” (Database Architectures Group, CWI)
• Pınar Tözün “Different Scales of Resource-Aware Deep Learning and How to Tackle Them” (Systems Group, TU Darmstadt)
• Pınar Tözün “Different Scales of Resource-Aware Deep Learning and How to Tackle Them” (Chair for Database Systems, TU Munich 2023)
• Pınar Tözün “Different Scales of Resource-Aware Deep Learning and How to Tackle Them” (Snowflake, Berlin 2023)
• Pınar Tözün “Different Scales of Resource-Aware Deep Learning and How to Tackle Them” (DIMA, TU Berlin 2023)
• Pınar Tözün “Different Scales of Resource-Aware Deep Learning and How to Tackle Them” (HPI Data & AI Cluster Retreat 2023)
• Pınar Tözün “Different Scales of Resource-Aware Deep Learning and How to Tackle Them” (BIFOLD Summer School 2023 on Artificial Intelligence and Ecological Sustainability 2023)
• Aleš Zamuda “Evolutionary Optimization Algorithms & Large-Scale Machine Learning” (DAPHNE TEC-USE CASE Workshop)
• Aleš Zamuda “EuroHPC Al in DAPHNE and Text Summarization” (Invited Talk, Sala Ada Lovelace, University of Alicante)
• Aleš Zamuda “SORS: EuroHPC AI in DAPHNE” (Severo Ochoa Research Seminars, Barcelona Supercomputing Center)
• Christoph Brücke “TPCx-AI – An Industry Standard Benchmark for Artificial Intelligence and Machine Learning Systems” (VLDB23)
• Maximilian Böther “Analyzing Vectorized Hash Tables Across CPU Architectures” (VLDB23)
• Thomas Bodner “BabelMR: A Polyglot Framework for Serverless MapReduce” (VLDB23)
• Lawrence Benson “Evaluating SIMD Compiler-Intrinsics for Database Systems” (VLDB23)
• Mark Dokter “Tech Adoption Scenarios for Data and AI 2030” (BDVA/LeADS, online)
• Mark Dokter, Bernhard Peischl “From “Big” to “Extreme”, or how to increase the value of data analytics” (Dataweek 2023, Lulea, Sweden)
• Florina M. Ciorba “Multilevel Scheduling in Action for Data Analysis Pipelines with DAPHNE” (The Resource-Aware Data Science at IT University of Copenhagen)
• Florina M. Ciorba “Automated Scheduling Algorithm Selection in OpenMP” (The Leogang HPC Workshop)
• Florina M. Ciorba “Automated Scheduling Algorithm Selection in OpenMP” (Scheduling Variable Capacity Resources for Sustainability Workshop)
• Florina M. Ciorba, Ahmed Eleliemy “Multilevel Scheduling relection on DAPHNE” (Dagstuhl Seminar 23171)
• Pınar Tözün “Dimensions of Hardware Parallelism and Exploiting Them for Transaction Processing” (VLDB Summer School 2023)
• Aleš Zamuda “HPC Deployment / Use Cases” (High Performance Embedded Architectures and Compilers (HiPEAC) 2023, workshop “EVEREST + DAPHNE: Workshop on Design and Programming High-performance, distributed, reconfigurable and heterogeneous platforms for extreme-scale analytics”)
• Aleš Zamuda “Integrated data analysis pipelines for large-scale data management, HPC, and machine learning” (BDV ICT-51 Projects Workshop 2)
• Matthias Boehm “DAPHNE Overview” (EVEREST+DAPHNE workshop at HiPEAC)
• Patrick Damme “DAPHNE Hands-on Lab” (EVEREST+DAPHNE at HiPEAC)
• Patrick Damme “DAPHNE Hands-on Lab” (EVEREST+DAPHNE at HiPEAC)
• Ahmed Eleliemy “DAPHNE Multilevel Scheduling relection on DAPHNE” (EVEREST+DAPHNE at HiPEAC)
• Aleš Zamuda“DAPHNE HPC Deployment / Use Cases” (EVEREST+DAPHNE at HiPEAC)
• Matthias Boehm “System Infrastructure for Data-centric ML Pipelines” (Tech talk series at Apple; hosted by Sanjana Sahayaraj)
Events, we have organized or co-organized:
• Matthias Boehm (co-chair) “DEEM: Workshop on data management for end-to-end machine learning” (DEEM@SIGMOD’23)
• Matthias Boehm (co-chair) “A Tutorial Workshop on ML for Systems and Systems for ML” (BTW’23 workshops)
• Pınar Tözün (organizer) “Resource-Aware Data Science (RAD) Day” (NA)
• Matthias Boehm (co-chair) “EVEREST + DAPHNE: Workshop on Design and Programming High-performance, distributed, reconfigurable and heterogeneous platforms for extreme-scale analytics” (EVEREST+DAPHNE@HiPEAC’23)
• Matthias Boehm (co-chair) “49th International Conference on Very Large Data Bases” (VLDB 2023)
• Florina M. Ciorba (co-organizer) “Driving HPC Operations With Holistic Monitoring and Operational Data Analytics” (Dagstuhl Seminar 23171)
• Florina M. Ciorba (co-organizer) “Monitoring & Operational Data Analytics” (4th ISC HPC International Workshop on “Monitoring & Operational Data Analytics”)
• Aleš Zamuda (organizer, hybridization) “The Genetic and Evolutionary Computation Conference” (GECCO 2023)
2022
• Matthias Boehm “Optimizing Compiler Infrastructure for Data-centric ML Pipelines” (Cornell Database Seminar)
• Matthias Boehm “The Data and ML Research we need to do over the next decade” (Data Epoch Podcast, Episode 7)
• Philippe Bonnet “Principles of Database and SSD Co-Design” (DFG SSP Summer School)
• Aleš Zamuda “DAPHNE meets ICT-Standardization” (BDV ICT-51 Projects Workshop)
• Aleš Zamuda “DAPHNE: Integrated Data Analysis Pipelines for Large-Scale Data Management, HPC and Machine Learning” (31st International Electrotechnical and Computer Science Conference)
• Aleš Zamuda “DAPHNE: Integrated Data Analysis Pipelines for Large-Scale Data Management, HPC and Machine Learning” (IEEE Slovenia CIS Annual Chapter Meeting with Technical Presentations during ERK 2022 (Portorož, Slovenia))
• Lawrence Benson “Darwin: Scale-In Stream Processing” (CIDR)
• Lawrence Benson “Viper: An Efficient Hybrid PMem-DRAM Key-Value Store” (VLDB)
• Tobias Maltenberger and Ivan Ilic “Evaluating Multi-GPU Sorting with Modern Interconnects” (SIGMOD)
• Pınar Tözün “Micro-architectural Analysis of a Learned Index” (aiDM Workshop (co-located with ACM SIGMOD))
• Pınar Tözün “Peaceful Co-habitation on GPUs for Deep Learning” (Microsoft GSL Talk Series)
• Pınar Tözün “Sustainable Use of Hardware” (IT University of Copenhagen – Climate IT Video Series)
• Aleš Zamuda “DAPHNE: Integrated Data Analysis Pipelines for Large-Scale Data Management, HPC and Machine Learning” [poster] (31st International Electrotechnical and Computer Science Conference)
• Patrick Damme, et al “DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines” (International Symposium on Parallel and Distributed Computing, ISPDC)
• Florina M. Ciorba “Multilevel Scheduling and Load Balancing in Scientific Applications” (NHR4CES)
• Matthias Boehm, et al “DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines” (HiPEAC)
• Matthias Boehm “Optimizing Compiler Infrastructure for Data-centric ML Pipelines” (Microsoft GSL Talk Series)
• Pinar Tözün “Hardware-Conscious Machine Learning” (Dagstuhl Seminar)
• Tobias Maltenberger and Till Lehmann “Evaluating In-Memory Hash Joins on Persistent Memory” (EDBT)
• Nils Strassenburg “Efficiently Managing Deep Learning Models in a Distributed Environment” (EDBT)
• Matthias Boehm, et al “DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines” (German Spring DB Symposium)
• Pinar Tözün “Toward Hardware-Conscious Data Science” (German Spring DB Symposium)
• Florina Ciorba “Scheduling of Integrated Data Analysis Pipelines” (Leogang HPC Workshop)
• Matthias Boehm, et al “DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines” (EVEREST workshop at HiPEAC)
• Matthias Boehm, et al “DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines” (Conference on Innovative Data Systems Research, CIDR)
Events, we have organized or co-organized:
• Matthias Boehm “DEEM: Workshop on data management for end-to-end machine learning” (DEEM@SIGMOD’22)
• Aleš Zamuda “The Genetic and Evolutionary Computation Conference” (Virtualisation Chair; The Genetic and Evolutionary Computation Conference (GECCO))
• Pınar Tözün “9th International Workshop on Database Testing” (Workshop Co-Organizer; DBTest)
• Florina M. Ciorba “Database Indexing and Query Processing” (Co-Organizer; Dagstuhl Seminar)
• Florina M. Ciorba “MODA: Monitoring and Operational Data Analytics” (Workshop Co-Organizer; ISC High Performance)
• Florina M. Ciorba “Swiss Chapter Women in HPC” (Platform for Advancing Scientific Computing)
• Florina M. Ciorba “21st IEEE International Symposium on Parallel and Distributed Computing” (General Chair; ISPDC)
• Florina M. Ciorba “51st International Conference on Parallel Processing” (Technical Program Co-Chair; ICPP)
2021
• Ahmed Eleliemy “Don’t Compete, Let’s Cooperate: A Cooperative Scheduling Approach” (The Platform for Advanced Scientific Computing (PASC))
• Björn Daase “Maximizing Persistent Memory Bandwidth Utilization for OLAP Workloads” (SIGMOD)
• Ahmed Eleliemy “A Resourceful Coordination Approach for Multilevel Scheduling” (International Conference on High Performance Computing & Simulation (HPCS))
• Wolfgang Lehner “Academia meets industry: Is there more than polishing the round ball?” (SAP Open House Event E33)
• Matthias Boehm “Data Independence in Machine Learning Pipelines and Data Science Workflows” (ETH/Stanford Workshop on Data-centric AI)
• Wolfgang Lehner “ScaleUp, ScaleOut, …: „ScaleFlex“ for the Next-Generation Database engines?” (Huawei STW2021, Strategy and Technology Workshop)
• Tilmann Rabl “Benchmarking Integrated Data Analysis Pipelines” (Huawei Strategy and Technology Workshop)
• Ilin Tolovski “A Survey of Big Data, High Performance Computing, and Machine Learning Benchmarks” (TPCTC @VLDB)
• Florina M. Ciorba “Multilevel Scheduling and Load Balancing in Scientific Applications” (University of Delaware)
• Aleš Zamuda “Monitoring and Operational Data Analytics from a User Perspective at First EuroCC HPC Vega Supercomputer and Nation-wide in Slovenia” (MODA at ISC High Performance Digital)
• Wolfgang Lehner “Flexible Vector Processing for Database Engines” (Huawei ACM SIGMOD/PODS)
• Maximilian Böther, Otto Kißig, Lawrence Benson, Tilmann Rabl: “Drop It In Like It’s Hot: An Analysis of Persistent Memory as a Drop-in Replacement for NVMe SSDs” (International Workshop on Data Management on New Hardware)
• Alberto Lerner, Philippe Bonnet “Not your Grandpa’s SSD: Storage in the co-Design Era” (International Conference on Management of Data, Sigmod)
• Matthias Boehm ”Big-Data, Cloud and Machine Learning as a key-enabler for the European Automotive Eco-System” (BDVA Data Week)
• Pınar Tözün “Data-Intensive Systems in the Microsecond Era” (Waterloo Data Systems Seminars, 2020-2021; Data Processing on Modern Hardware Lectures, TU Munich, 2021; Dutch Seminar on Data Systems Design)
Events, we have organized or co-organized:
• Matthias Boehm “DEEM: Workshop on data management for end-to-end machine learning” (DEEM@SIGMOD’21)
• Florina M. Ciorba “MODA: Monitoring and Operational Data Analytics” (ISC High Performance Digital)
• Florina M. Ciorba “Heterogeneity in Computing” (IPDPS)