GooFit: A library for massively parallelising maximum-likelihood fits

R. Andreassen, B. T. Meadows, M. de Silva, M. D. Sokoloff, K. Tomko
University of Cincinnati, Physics Department, ML0011, Cincinnati OH 45221-0011, USA
arXiv:1311.1753 [cs.DC], (7 Nov 2013)

   author={Andreassen}, R. and {Meadows}, B.~T. and {de Silva}, M. and {Sokoloff}, M.~D. and {Tomko}, K.},

   title={"{GooFit: A library for massively parallelising maximum-likelihood fits}"},

   journal={ArXiv e-prints},




   keywords={Computer Science – Distributed, Parallel, and Cluster Computing, Computer Science – Mathematical Software},




   adsnote={Provided by the SAO/NASA Astrophysics Data System}


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


Fitting complicated models to large datasets is a bottleneck of many analyses. We present GooFit, a library and tool for constructing arbitrarily-complex probability density functions (PDFs) to be evaluated on nVidia GPUs or on multicore CPUs using OpenMP. The massive parallelisation of dividing up event calculations between hundreds of processors can achieve speedups of factors 200-300 in real-world problems.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

You must be logged in to post a comment.

* * *

* * *

* * *

Free GPU computing nodes at

Registered users can now run their OpenCL application at 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 11.4
  • SDK: AMD APP SDK 2.8
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 5.0.35, AMD APP SDK 2.8

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 will be treated according to our Privacy Policy

HGPU group © 2010-2014

All rights belong to the respective authors

Contact us: