10546

Kokkos: Enabling performance portability across manycore architectures

H. Carter Edwards, Christian R. Trott
Sandia National Laboratories, PO Box 5800 / MS 1318, Albuquerque NM, 87185
XSCALE, 2013
@article{edwards2013kokkos,

   title={Kokkos: Enabling performance portability across manycore architectures},

   author={Edwards, H Carter and Trott, Christian R},

   year={2013}

}

The manycore revolution in computational hardware can be characterized by increasing thread counts, decreasing memory per thread, and architecture specific performance constraints for memory access patterns. High performance computing (HPC) on emerging manycore architectures requires codes to exploit every opportunity for thread-level parallelism and satisfy conflicting performance constraints. We developed the Kokkos C++ library to provide scientific and engineering codes with a user accessible manycore performance portable programming model. The two foundational abstractions of Kokkos are (1) dispatch work to a manycore device for parallel execution and (2) manage multidimensional arrays with polymorphic layouts. The integration of these abstractions enables users’ code to satisfy multiple architecture specific memory access pattern performance constraints without having to modify their source code. In this paper we describe the Kokkos abstractions, summarize its application programmer interface (API), and present performance results for a molecular dynamics computational kernel and finite element mini-application.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

Like us on Facebook

HGPU group

149 people like HGPU on Facebook

Follow us on Twitter

HGPU group

1239 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: