Euro-Par 2024 | Track 1: Programming, Compilers and Performance | International European Conference on Parallel and Distributed Computing Track 1: Programming, Compilers and PerformanceEuro-par

Track 1. Programming, Compilers and Performance

Chairs

Program Committee

  • Michela Becchi, North Carolina State University
  • Siegfried Benkner, University of Vienna
  • Jean-Baptiste Besnard, Paratools
  • Walter Binder, University of Lugano
  • Bruno Bodin, The University of Edinburgh
  • Joao Cardoso, University of Porto
  • Paul Carpenter, Barcelona Supercomputing Center
  • Jeronimo Castrillon, TU Dresden
  • Brad Chamberlain, 
  • Serena Curzel, Politecnico di Milano
  • Tom Deakin, University of Bristol
  • Bernhard Egger, Seoul National University
  • R Govindarajan, Indian Institute of Science
  • Giulia Guidi, Cornell University
  • Georg Hager, Erlangen Regional Computing Center
  • Abhinav Jangda, Microsoft Research
  • Seyong Lee, Oak Ridge National Laboratory
  • Stefano Markidis, KTH Royal Institute of Technology
  • Lucas Mello Schnorr, UFRGS
  • Ivy Peng, KTH Royal Institute of Technology
  • Istvan Reguly, Pázmány Péter Catholic University
  • Bernhard Scholz, The University of Sydney
  • Cristina Silvano, Politecnico di Milano
  • Giuseppe Tagliavini, University of Bologna
  • Nathan Tallent, Pacific Northwest National Laboratory
  • Miwako Tsuji, RIKEN R-CCS
  • Antonino Tumeo, Pacific Northwest National Laboratory
  • Didem Unat, Koç University
  • Hans Vandierendonck, Queen's University Belfast
  • Ana Lucia Varbanescu, University of Amsterdam
  • Veronica Vergara Larrea, Oak Ridge National Laboratory
  • Sotirios Xydis, National Technical University of Athens

Focus

  • High level programming models and tools for multi-/many-core and heterogeneous architectures
  • Programming environments, interoperable tool environments
  • Productivity and performance portability
  • Compiling for multithreaded/multi-core and heterogeneous processors/architectures
  • Compiling for emerging architectures (low-power accelerator hardware, reconfigurable hardware, processors in memory)
  • Iterative, just-in-time, feedback-oriented, dynamic, and machine-learning-based compilation
  • Static and dynamic program analysis
  • Program transformation systems
  • Interaction between compiler, runtime system, hardware, and operating system
  • Compiler, run-time, and architectural support for dynamic adaptation
  • Compilers for domain-specific languages
  • Instrumentation, monitoring, evaluation and prediction of non-functional program behaviour
  • Auto-tuning and multi-objective code optimization
  • Verification and validation of performance models
  • Power consumption modelling and prediction
  • Performance modelling and simulation of emerging exascale systems

In cooperation

Organized by

Supported by