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Applications

Leopoldo Noel Gaxiola Sanchez, Juan Jose Tapia Armenta, Victor Hugo Diaz Ramirez
The implementation of parallel genetic algorithms on a graphic processor GPU to solve the Travelling Salesman Problem instances is presented. Two versions of parallel genetic algorithms are implemented, a Parallel Genetic Algorithm with Islands Model and a Parallel Genetic Algorithm with Elite Island; the two versions were executed on a GPU. In both cases, each […]
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Weifeng Liu, Brian Vinter
Sparse matrix-vector multiplication (SpMV) is a central building block for scientific software and graph applications. Recently, heterogeneous processors composed of different types of cores attracted much attention because of their flexible core configuration and high energy efficiency. In this paper, we propose a compressed sparse row (CSR) format based SpMV algorithm utilizing both types of […]
Joris Cramwinckel
In this thesis we present a state-of-the-art approach to accelerate Monte Carlo valuations of embedded options. Due to regulations and improved risk management, nested simulations (scenarios in scenarios) are becoming increasingly important for institutional investors like: insurance companies, pension funds and housing corporations. Preferably one wishes to use a framework in which multiple related problems […]
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Omar Abdelkafi, Khalil Chebil, Mahdi Khemakhem
Real-world optimization problems are very complex and NP-hard. The modeling of such problems is in constant evolution in term of constraints and objectives and their resolution is expensive in computation time. With all this change, even metaheuristics, well known for their efficiency, begin to be overtaken by data explosion. Recently, Thanks to the publication of […]
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E. Coronado-Barrientos, G. Indalecio, A. Garcia-Loureiro
The present work is an analysis of the performance of the AXPY, DOT and SpMV functions using OpenCL. The code was tested on the NVIDIA Tesla S2050 GPU and Intel Xeon Phi 3120A coprocessor. Due to nature of the AXPY function, only two versions were implemented, the routine to be executed by the CPU and […]
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Sencer Nuri Yeralan, Timothy A. Davis, Sanjay Ranka
Sparse matrix factorization involves a mix of regular and irregular computation, which is a particular challenge when trying to obtain high-performance on the highly parallel general-purpose computing cores available on graphics processing units (GPUs). We present a sparse multifrontal QR factorization method that meets this challenge, and is up to eleven times faster than a […]
Reza Nakhjavani
The ever increasing complexity of scientific applications has led to utilization of new HPC paradigms such as Graphical Processing Units (GPUs). However, modifying applications to run on GPU is challenging. Furthermore, the speedup achieved by using GPUs has added a huge heterogeneity to HPC clusters. In this dissertation, we enabled NPAIRS, a neuro-imaging application, to […]
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Lena Oden
Today, GPUs and other parallel accelerators are widely used in high performance computing, due to their high computational power and high performance per watt. Still, one of the main bottlenecks of GPU-accelerated cluster computing is the data transfer between distributed GPUs. This not only affects performance, but also power consumption. Often, a data transfer between […]
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Mark Stephenson, Siva Kumar Sastry Hari, Yunsup Lee, Eiman Ebrahimi, Daniel R. Johnson, David Nellans, Mike O'Connor, Stephen W. Keckler
To aid application characterization and architecture design space exploration, researchers and engineers have developed a wide range of tools for CPUs, including simulators, profilers, and binary instrumentation tools. With the advent of GPU computing, GPU manufacturers have developed similar tools leveraging hardware profiling and debugging hooks. To date, these tools are largely limited by the […]
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Jonathan Jung
In this paper, we propose a new very simple numerical method for solving liquid-gas compressible flows on two dimensional cartesian meshes. For achieving high performance, the scheme is tested on recent multi-core processors and Graphics Processing Units (GPU), using the OpenCL environment. We describe how to install and to run the code CLBUBBLE for computing […]
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Weifeng Liu, Brian Vinter
General sparse matrix-matrix multiplication (SpGEMM) is a fundamental building block for numerous applications such as algebraic multigrid method (AMG), breadth first search and shortest path problem. Compared to other sparse BLAS routines, an efficient parallel SpGEMM implementation has to handle extra irregularity from three aspects: (1) the number of nonzero entries in the resulting sparse […]
Jack Edward Arnstein
Having learned a great deal about the problem and also the solutions over the course of this project, it is the opinion of the author that the method undertaken within this report is unsatisfactory for delivering performance enhancement over alternative approaches. Firstly the domain transfers result in reduced performance. For larger simulations these prove to […]
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Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

The platforms are

Node 1
  • GPU device 0: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
  • CPU: AMD Phenom II X6 @ 2.8GHz 1055T
  • RAM: 12GB
  • OS: OpenSUSE 13.1
  • SDK: nVidia CUDA Toolkit 6.5.14, AMD APP SDK 3.0
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.3
  • SDK: AMD APP SDK 3.0

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