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New model-based methods and algorithms for performance and energy optimization of data parallel applications on homogeneous multicore clusters
Modern homogeneous parallel platforms are composed of tightly integrated multicore CPUs.
This tight integration has resulted in the cores contending for various shared on-chip …
This tight integration has resulted in the cores contending for various shared on-chip …
A novel data-partitioning algorithm for performance optimization of data-parallel applications on heterogeneous HPC platforms
Modern HPC platforms have become highly heterogeneous owing to tight integration of
multicore CPUs and accelerators (such as Graphics Processing Units, Intel Xeon Phis, or …
multicore CPUs and accelerators (such as Graphics Processing Units, Intel Xeon Phis, or …
Model-based optimization of EULAG kernel on Intel Xeon Phi through load imbalancing
Load balancing is a widely accepted technique for performance optimization of scientific
applications on parallel architectures. Indeed, balanced applications do not waste processor …
applications on parallel architectures. Indeed, balanced applications do not waste processor …
A hierarchical data-partitioning algorithm for performance optimization of data-parallel applications on heterogeneous multi-accelerator NUMA nodes
Modern HPC platforms are highly heterogeneous with tight integration of multicore CPUs
and accelerators (such as Graphics Processing Units, Intel Xeon Phis, or Field …
and accelerators (such as Graphics Processing Units, Intel Xeon Phis, or Field …
Execution of compound multi‐kernel OpenCL computations in multi‐CPU/multi‐GPU environments
F Soldado, F Alexandre… - … and Computation: Practice …, 2016 - Wiley Online Library
Current computational systems are heterogeneous by nature, featuring a combination of
CPUs and graphics processing units (GPUs). As the latter are becoming an established …
CPUs and graphics processing units (GPUs). As the latter are becoming an established …
Parallel data partitioning algorithms for optimization of data-parallel applications on modern extreme-scale multicore platforms for performance and energy
Data partitioning algorithms aiming to minimize the execution time and the energy of
computations in self-adaptable data-parallel applications on modern extreme-scale …
computations in self-adaptable data-parallel applications on modern extreme-scale …
[PDF][PDF] Heterogeneous parallel computing: from clusters of workstations to hierarchical hybrid platforms
A Lastovetsky - Supercomputing frontiers and innovations, 2014 - superfri.org
Heterogeneous Parallel Computing: from Clusters of Workstations to Hierarchical Hybrid
Platforms Introduction Page 1 Heterogeneous Parallel Computing: from Clusters of …
Platforms Introduction Page 1 Heterogeneous Parallel Computing: from Clusters of …
Model-based optimization of MPDATA on Intel Xeon Phi through load imbalancing
A Lastovetsky, L Szustak, R Wyrzykowski - ar** of API calls
Embodiments are directed to a heterogeneous system for dynamically map** library calls
to one of a plurality of processing platforms. The plurality of processing platforms include a …
to one of a plurality of processing platforms. The plurality of processing platforms include a …