Research Group on Natural Computing

GPUs constitute nowadays a solid alternative for
high performance computing, and the advent of CUDA/OpenCL
allow programmers a friendly model to accelerate a broad range
of applications. The way GPUs exploit parallelism differ from
multi-core CPUs, which raises new challenges to take advantage
of its tremendous computing power. In this respect, P systems or
Membrane Systems provide a high-level computational modeling
framework that combines the structure and dynamic aspects
of biological systems while being inherently parallel and non-
deterministic. In this work, we implement on GPUs the simula-
tion for a solution provided by Membrane Computing to solve the
Satisfiability (SAT) problem. The overall speed up reaches 100x
versus a sequential CPU, with an additional 16x due to CUDA
optimizations. A promising scalability is also proven on more
sophisticated GPU clusters and/or demanding problem sizes.