10162

Domain Specific Languages for High Performance Computing

Alejandro Fernandez Suarez
Universitat Politecnica de Catalunya (UPC) – BarcelonaTech
Universitat Politecnica de Catalunya, 2013
@article{fernandez2013domain,

   title={Domain Specific Languages for High Performance Computing},

   author={Fern{‘a}ndez Su{‘a}rez, Alejandro},

   year={2013},

   publisher={Universitat Polit{‘e}cnica de Catalunya}

}

Download Download (PDF)   View View   Source Source   

1551

views

High Performance Computing (HPC) relies completely on complex parallel, heterogeneous architectures and distributed systems which are hard and error-prone to exploit, even for HPC specialists. Further and further knowledge on runtime systems, dependency tracking, memory transaction optimization and many other techniques are a must-have requirement to produce high quality software capable of exploiting every single bit of power an HPC system has to o er. On the other hand, domain experts like geologists or biologists are usually not technology-aware enough to produce the best software for these complex systems. Nowadays, the only way to successfully exploit an HPC system requires that computer and domain experts work closely towards producing applications to solve domain problems. Domain experts have the knowledge on the domain algorithms, while computer experts know how to efficiently map these algorithms on HPC systems. This project proposes a framework that eases most of the processes related to the production of Domain Specific Languages (DSLs) that run on top of accelerator-based heretogeneous architectures. By using DSLs, domain experts can develop their applications using their own high level language, focusing only on their hard-enough issues. Meanwhile, computer experts stay only improving the implementation of these DSLs to make the most out of an HPC platform. This way, we keep each expert focused as much as possible on its natural domain of expertise.
VN:F [1.9.22_1171]
Rating: 5.0/5 (3 votes cast)
Domain Specific Languages for High Performance Computing, 5.0 out of 5 based on 3 ratings

* * *

* * *

Like us on Facebook

HGPU group

128 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1189 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: