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A Systematic Comparison of Dynamic Load Balancing Algorithms for Massively Parallel Rigid Particle Dynamics
As compute power increases with time, more involved and larger simulatio...
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Proactive Load Balancing in Heterogeneous Cellular Networks
Recent exponential growth of data over cellular networks has cause the p...
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DLBFoam: An open-source dynamic load balancing model for fast reacting flow simulations in OpenFOAM
Computational load imbalance due to direct integration of chemical kinet...
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An Adaptive Load Balancer For Graph Analytical Applications on GPUs
Load balancing graph analytics workloads on GPUs is difficult because of...
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Distributed-Memory Load Balancing with Cyclic Token-based Work-Stealing Applied to Reverse Time Migration
Reverse time migration (RTM) is a prominent technique in seismic imaging...
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SPH-EXA: Enhancing the Scalability of SPH codes Via an Exascale-Ready SPH Mini-App
Numerical simulations of fluids in astrophysics and computational fluid ...
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Beam-tracing domain decomposition method for urban acoustic pollution
This paper covers the fast solution of large acoustic problems on low-re...
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Exploiting Parallelism on Shared Memory in the QED Particle-in-Cell Code PICADOR with Greedy Load Balancing
State-of-the-art numerical simulations of laser plasma by means of the Particle-in-Cell method are often extremely computationally intensive. Therefore there is a growing need for development of approaches for efficient utilization of resources of modern supercomputers. In this paper, we address the problem of a substantially non-uniform and dynamically varying distribution of macroparticles in a computational area in simulating quantum electrodynamic (QED) cascades. We propose and evaluate a load balancing scheme for shared memory systems, which allows subdividing individual cells of the computational domain into work portions with subsequent dynamic distribution of these portions between OpenMP threads. Computational experiments on 1D, 2D, and 3D QED simulations show that the proposed scheme outperforms the previously developed standard and custom schemes in the PICADOR code by 2.1 to 10 times when employing several Intel Cascade Lake CPUs.
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