Newsletter

Newsletter
 

Academia


Today's students are tomorrow's scientists, engineers, analysts, researchers, developers, and pioneers in industry, government, and academia. And it is here, in the education of undergraduates and postgraduate students that AccelerEyes began and still remains with a strong focus.


ArrayFire in Course Instruction

The use of ArrayFire in higher education and research is growing deep roots all over the globe. The world's most prominent universities and research institutions, such as Princeton, Caltech, Harvard, Oxford, Max Planck, MIT, Stanford, and many others use AccelerEyes' software, both for research and in course instruction.

Because of its unrivaled ability to streamline the process of innovation, ArrayFire is easily integrated into the academic framework.


Example Applications

ArrayFire can help educate students and support research in many application areas including:

  • Mathematics
  • Statistics
  • Image Processing
  • Signal Processing
  • Optimization
  • Financial Analytics
  • And much more...

Accelerating LTE Simulation
Tsinghua University
Speedup: 3X


lte system

Accelerating LTE Simulation

Authors: Yuan Gao, Yin Sun, Chun Hui Zhou, Xin Su, Xi Bin Xu, Shi Dong Zhou, Tsinghua University
Speedup: 3X

Fast simulations are a driving force in several research projects. However, the accompanying long simulation times can tend to be a drag in many of these projects. In this article, we shall bring up the example of the work on 3GPP LTE System Simulation by Yuan Gao et al (from Tsinghua University, Beijing) and demonstrate how the use of AccelerEyes software can significantly improve the simulator performance and lead to faster validation times in simulation projects.

Last Updated: 8 Aug 2011

High Performance Compressive Sensing
Rice University
Speedup: 5X


Great Wall of China

High Performance Compressive Sensing

Authors: Nabor Reyna and Wotao Yin from Rice University
Speedup: 5X

This work deals with reconstruction of signals using partial Fourier matrices (RecPF). The major computational components of the algorithm involve shrinkage and FFTs. AccelerEyes software is employed to accelerate this compute-heavy code.

Last Updated: 27 Jul 2011

Power System Simulations
Indian Institute of Technology, Roorkee, India
Speedup: 35X


power flow image

Power Flow on the GPU

Authors: Indian Institute of Technology, Roorkee
Speedup: 35X

Power flow studies are one of the most important aspects of power system planning and operation. The power flow reveals the sinusoidal steady state characteristics of the entire system - voltages, real and reactive power generated, and absorbed and line losses- elucidating the voltage magnitudes and angles at each bus, the generation of each generating unit, and real and reactive power losses in the system. All this is necessary to ensure the security, economy, and control of electrical energy distribution. Learn how AccelerEyes software can deliver magnitudes of performance improvement over CPU-based solutions.

 

Last Updated: 18 Apr 2010

Antenna Array Simulations
University of Naples Federico II
Speedup: 4.5X


Echo Generators

Design and simulate echo generators

Authors: A. Capozzoli, C. Curcio, A. Liseno at University of Naples Federico II
Speedup: 24X

Antenna array design involves repeated simulation to tune the many parameters involved, and waiting around for simulations to finish is no fun. Offloading the optimization problem onto the GPU cuts that time down significantly. In their recent paper, Capozzoli, Curcio, and Liseno of University of Naples Federico II demonstrated how a simple modification to their echo generator array simulation took advantage of the GPU to bring immediate speedups.

Last Updated: 20 Jul 2011

Laplace Transform Inversion
Acunum Algorithms and Solutions
Speedup: 3.8X


Laplace Transform Inversion on the GPU

Laplace Transform Inversion on the GPU

Authors: Patrick Kano and Moysey Brio at Acunum Algorithms and Solutions
Speedup: 3.8X

The numerical inversion of the Laplace transform is a long standing problem due its implicit ill-posedness. Patrick Kano and Moysey Brio of Acunum Algorithms and Solutions, with their experience in computational methods and algorithm development, found a solution that not only works, but is very fast.

Last Updated: 13 May 2011

Compressed Sensing for Image Reconstruction
College of Engineering, Roorkee, India
Speedup: 8X


Compressed Sensing Algorithms

Compressed Sensing Algorithms

Authors: Kuldeep Yadav, Ankush Mittal, M.A. Ansar and Avi Srivastava, College of Engineering, Roorkee, India
Speedup: 8X

Compressed sensing is very critical in the areas of medical image reconstruction, image acquisition or sensor networks. An algorithm for compressed sensing developed using a Basis Pursuit Algorithm shows over 8X speedup when run on an NVIDIA GPU.

Last Updated: 5 May 2011

Fat/Water Reconstruction for Medical Images
Case Western Reserve University
Speedup: 11.6X


Fat/Water Reconstruction

Improved Fat/Water Reconstruction Algorithm

Authors: D. H. Johnson, S. Narayan, C. A. Flask and D. L. Wilson, Case Western Reserve University
Speedup:11.6X

Case Western Reserve University researchers turned to GPUs running AccelerEyes software to develop a fast and robust version of the "Iterative Decomposition of water and fat with an Echo Asymmetry and Least-squares" (IDEAL) reconstruction algorithm. This algorithm uses a lot of Image Processing algorithms for reconstruction, and was shown to achieve very high speedups.

Last Updated: 25 Mar 2011