8982

Accelerating Dynamic Binary Translation with GPUs

Chung Hwan Kim, Srikanth Manikarnike, Vaibhav Sharma, Eric Eide, Robert Ricci
School of Computing, University of Utah
School of Computing Poster Competition, University of Utah, 2011
@article{kim2011accelerating,

   title={Accelerating Dynamic Binary Translation with GPUs},

   author={Kim, Chung Hwan and Manikarnike, Srikanth and Sharma, Vaibhav and Eide, Eric and Ricci, Robert},

   year={2011}

}

Download Download (PDF)   View View   Source Source   

511

views

Binary translation is the emulation of one instruction set by another through translation of code. In binary translation sequences of instructions are translated from the source to the target instruction set. Dynamic binary translation (DBT) looks at a short sequence of code – typically on the order of a single basic block – then translate it. Code is only translated as it is discovered and when possible, and jump instructions are made to point to already translated and saved code. In this project, in addition to the existing sequential translator, we propose to use a supplementary translator implemented on GPUs to accelerate DBT.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Like us on Facebook

HGPU group

218 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1401 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: 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 12.2
  • SDK: 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 © 2010-2015 hgpu.org

All rights belong to the respective authors

Contact us: