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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

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A uniform approach for programming distributed heterogeneous computing systems.

Ivan Grasso¹, Simone Pellegrini², Biagio Cosenza²

¹Institute of Computer Science, University of Innsbruck, Austria ; Barcelona Supercomputing Center, Barcelona, Spain.

Journal of Parallel and Distributed Computing

|April 7, 2015

Summary

This summary is machine-generated.

libWater simplifies developing applications for large, heterogeneous compute clusters. This OpenCL extension improves performance and scaling by optimizing communication and data transfers.

Keywords:

Distributed computing Heterogeneous computing MPI OpenCL Programming model Runtime system

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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

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Area of Science:

High-Performance Computing (HPC)
Parallel and Distributed Computing

Background:

Scientific community increasingly uses large-scale, heterogeneous compute clusters (CPUs and GPUs).
Developing applications for these systems is challenging due to complex programming paradigms.

Purpose of the Study:

Introduce libWater, a library extension for OpenCL.
Simplify development of distributed applications on heterogeneous systems.

Main Methods:

libWater provides a transparent interface abstracting distributed architectures.
Runtime system tracks dependencies via event synchronization to build a DAG of commands.
Automatic optimizations include collective communication pattern detection and device-host-device copy removal.

Main Results:

libWater demonstrated improved performance and scaling across three different compute clusters.
Evaluated on various test applications and configurations.

Conclusions:

libWater effectively simplifies heterogeneous distributed application development.
The library enhances performance and scalability in HPC environments.