Algorithms and Architectures for Parallel Processing

Volume 7439 of the series Lecture Notes in Computer Science pp 114-128

A Multi-GPU Programming Library for Real-Time Applications

  • Sebastian SchaetzAffiliated withBiomedNMR Forschungs GmbH, Max Planck Institute for biophysical Chemistry
  • , Martin UeckerAffiliated withDepartment of Electrical Engineering and Computer Sciences, University of California

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We present MGPU, a C++ programming library targeted at single-node multi-GPU systems. Such systems combine disproportionate floating point performance with high data locality and are thus well suited to implement real-time algorithms. We describe the library design, programming interface and implementation details in light of this specific problem domain. The core concepts of this work are a novel kind of container abstraction and MPI-like communication methods for intra-system communication. We further demonstrate how MGPU is used as a framework for porting existing GPU libraries to multi-device architectures. Putting our library to the test, we accelerate an iterative non-linear image reconstruction algorithm for real-time magnetic resonance imaging using multiple GPUs. We achieve a speed-up of about 1.7 using 2 GPUs and reach a final speed-up of 2.1 with 4 GPUs. These promising results lead us to conclude that multi-GPU systems are a viable solution for real-time MRI reconstruction as well as signal-processing applications in general.


GPGPU multi-GPU hardware-aware algorithm real-time signal-processing MRI iterative image reconstruction