text: The multi-GPU open-source package QCDGPU for lattice Monte Carlo simulations of pure SU(N) gluody- namics in external magnetic field at finite temperature and O(N) model is developed. The code is implemented in OpenCL, tested on AMD and NVIDIA GPUs, AMD and Intel CPUs and may run on other OpenCL-compatible devices. The pack- age contains minimal external library dependencies and is OS platform-independent. It is optimized for heterogeneous computing due to the possibility of dividing the lattice into non-equivalent parts to hide the difference in performances of the devices used. QCDGPU has client-server part for distributed simulations. The package is designed to produce lattice gauge configurations as well as to analyze previously generated ones. QCDGPU may be executed in fault-tolerant mode. Monte Carlo procedure core is based on PRNGCL library for pseudo-random numbers generation on OpenCL-compatible devices, which contains several most popular pseudo-random number generators.
  @cite_1: Abstract The speed, bandwidth and cost characteristics of today's PC graphics cards make them an attractive target as general purpose computational platforms. High performance can be achieved also for lattice simulations but the actual implementation can be cumbersome. This paper outlines the architecture and programming model of modern graphics cards for the lattice practitioner with the goal of exploiting these chips for Monte Carlo simulations. Sample code is also given.
summary: The first paper relating application of GPUs in HEP lattice simulations was published in 2007 @cite_1 . The authors of this work used OpenGL as programming language and for the first time denoted the need to store lattice data in the form of four-component vectors. Shortly after of the publication, NVIDIA unveiled a new architecture CUDA and OpenGL ceased to be used as a GPGPU-computation language in further works.