8944

Hybrid parallel programming – evaluation of OpenACC

Leonardo Piletti Chatain
Universidade Federal do Rio Grande do Sul. Instituto de Informatica
Universidade Federal do Rio Grande do Sul. Instituto de Informatica, 2012
@phdthesis{maillard2012hybrid,

   title={Hybrid Parallel Programming-Evaluation of OpenACC},

   author={Maillard, Nicolas},

   year={2012},

   school={UNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL}

}

Download Download (PDF)   View View   Source Source   

713

views

OpenACC is a new specification for a hybrid (CPU + GPU) parallel programming API, in which the programmer uses compiler directives to distribute the computation between the GPU and the CPU. With a similar paradigm to OpenMP, OpenACC presents clear advantages in terms of ease of programming. Regarding performance, however, a comparison between OpenACC and CUDA has not yet been made. This study aims to evaluate OpenACC, establishing a comparison with CUDA. Furthermore, this work aims to identify the main limitations of OpenACC, analyzing its impact on performance. The evaluation is made using three different benchmarks (matrix transpose, dot product and matrix multiplication), each one comprising several implementations. Our results show that, although being in some cases notably slower than optimized CUDA, OpenACC implementations can still benefit from significant performance improvements over serial programs executed on the CPU. Moreover, when compared with less optimized CUDA implementations, OpenACC is shown to provide competitive performance with a much simpler programming model.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Like us on Facebook

HGPU group

171 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1282 peoples are following HGPU @twitter

* * *

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: