9410

GPU Programming for Physics Applications

Matthew Grossman
Middlebury College
Middlebury College, 2013
@phdthesis{grossman2013gpu,

   title={GPU PROGRAMMING FOR PHYSICS APPLICATIONS},

   author={Grossman, Matthew},

   year={2013},

   school={Middlebury College}

}

Download Download (PDF)   View View   Source Source   

320

views

The development of increasingly powerful and low cost massively parallel processors, known as GPUs, has created new opportunities for high speed and high precision computational work in physics. GPUs are extremely well suited to solving computationally intense problems at speeds much greater than traditional processors. They are now found in most personal computers, with research grade models available at reasonable prices. This makes a wide variety of previously intractably computationally intense problems solvable at a personal workstation. In this thesis I explore how these massively parallel processors work on both the hardware and software level, and the types of problems they are capable of solving better than traditional processors. Then, I move on to develop parallel programming solutions to computing the logistic map and solving ordinary differential equations. I evaluate how much of a speed advantage the GPU gives over the CPU and the limiting factors on the speed of the GPU implementations.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Like us on Facebook

HGPU group

128 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1194 peoples are following HGPU @twitter

Featured events

* * *

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: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • 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: AMD APP SDK 2.9
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: nVidia GeForce GTX 560 Ti 2GB, 822MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.2
  • SDK: nVidia CUDA Toolkit 6.0.1, AMD APP SDK 2.9

Completed OpenCL project should be uploaded via User dashboard (see instructions and example there), compilation and execution terminal output logs will be provided to the user.

The information send to hgpu.org will be treated according to our Privacy Policy

HGPU group © 2010-2014 hgpu.org

All rights belong to the respective authors

Contact us: