Ana Lucia Varbanescu

Latest

• The paper 'PEIR: Modeling Performance in Neural Information Retrieval' was accepted at ECIR 2025.
• The paper 'Analyzing Per-Application Energy Consumption in a Multi-Application Computing Continuum' was accepted at IEEE FMEC '24.
• The paper 'Distillation vs. Sampling for Efficient Training of Learning to Rank Models' was accepted at ACM ICTIR '24.
• The paper 'Using Evolutionary Algorithms to Find Cache-Friendly Generalized Morton Layouts for Arrays' was accepted for ACM/SPEC ICPE '24.
• Analyzing Per-Application Energy Consumption in a Multi-Application Computing Continuum
• Distillation vs. Sampling for Efficient Training of Learning to Rank Models
• Using Evolutionary Algorithms to Find Cache-Friendly Generalized Morton Layouts for Arrays
• The paper 'Systematically Exploring High-Performance Representations of Vector Fields Through Compile-Time Composition' was nominated for the Best Paper Award at ACM/SPEC ICPE 2023!
• The paper 'Systematically Exploring High-Performance Representations of Vector Fields Through Compile-Time Composition' was accepted at ACM/SPEC ICPE 2023.
• The paper 'Modelling Performance Loss due to Thread Imbalance in Stochastic Variable-Length SIMT Workloads' was accepted for MASCOTS '22.
• The paper 'Building Fine-Grained Analytical Performance Models for Complex Scientific Applications' was accepted at PPAM '22.
• The paper 'ParClick: A Scalable Algorithm for EM-based Click Models' was accepted for the ACM Web Conference '22.
• EnergyLabels
• Analytical Performance Estimation for Large-Scale Reconfigurable Dataflow Platforms
• High Performance Computing - 36th International Conference, ISC High Performance 2021, Virtual Event, June 24 - July 2, 2021, Proceedings
• ICPE '21: ACM/SPEC International Conference on Performance Engineering, Virtual Event, France, April 19-21, 2021
• ICPE '21: ACM/SPEC International Conference on Performance Engineering, Virtual Event, France, April 19-21, 2021, Companion Volume
• The future is big graphs: a community view on graph processing systems
• The paper 'μ-Genie: A Framework for Memory-Aware Spatial Processor Architecture Co-Design Exploration' was accepted for Euromicro DSD 2020.
• The paper 'A Sampling-Based Tool for Scaling Graph Datasets' was accepted for ACM/SPEC ICPE 2020.
• (μ)-Genie: A Framework for Memory-Aware Spatial Processor Architecture Co-Design Exploration
• A Sampling-Based Tool for Scaling Graph Datasets
• Designing and building application-centric parallel memories
• A Beginner's Guide to Estimating and Improving Performance Portability
• Exploring HPC and Big Data Convergence: A Graph Processing Study on Intel Knights Landing
• EXTRA: an open platform for reconfigurable architectures
• HLS Support for Polymorphic Parallel Memories
• MAX-PolyMem: High-Bandwidth Polymorphic Parallel Memories for DFEs
• Mix-and-Match: A Model-Driven Runtime Optimisation Strategy for BFS on GPUs
• Performance Estimation for Exascale Reconfigurable Dataflow Platforms
• Performance Prediction for Large-Scale Heterogeneous Platforms
• Towards Application-Centric Parallel Memories
• AstroHPC'12 foreword
• A4MMC foreword
• Towards an effective unified programming model for many-cores
• Building high-resolution sky images using the Cell/B.E.
• Radioastronomy image synthesis on the cell/B.E.