Computing High Resolution Explicit Corridor Maps using Parallel Technologies

R. Bonfiglioli
Utrecht University
Utrecht University, 2013

   title={Computing High Resolution Explicit Corridor Maps using Parallel Technologies},

   author={Bonfiglioli, R and Geraerts, RJ},



Download Download (PDF)   View View   Source Source   Source codes Source codes




This work investigates the approximated construction of Explicit Corridor Maps (ECMs). An ECM is a type of Navigation Mesh: a geometrical structure describing the walkable space of an environment that is used to speed-up the path-finding and crowd simulation operations occurring in the environment. Additional geometrical routines that take advantage of the GPGPU model are presented, which improve the current construction method by increasing the number of computations performed on the GPU and reducing the amount of data transferred back to the CPU. At the same time, a multi-tiled construction approach is presented, which almost frees the geometrical computation from its current main constraint, resolution, allowing high-resolution ECMs to be produced; moreover, we show that this approach can benefit optimally from CPU-parallelism. Both a GPGPU-aided and a CPU-parallel implementation are tested: experiments show that high-resolution ECMs can be computed, and that the new implementations often outperform the original one.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Follow us on Twitter

HGPU group

1585 peoples are following HGPU @twitter

Like us on Facebook

HGPU group

303 people like HGPU on Facebook

* * *

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

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: