P Systems Implementation on FPGA

The performance of P system simulators is key when deploying these models in real applications, or when pushing the limits of efficiency. In this concern, HPC is the key technology to accelerate the simulation of P systems, and specially, GPU computing is a good alternative since they provide a highly parallel device with a shared memory system and a flexible programming. GPUs are currently the enabling technology for trending areas such as Deep Learning. So far, many GPU simulators have been developed using CUDA, the first general-purpose programming model for GPUs. In this chapter, we introduce the concepts behind GPU computing and a taxonomy of GPU-based simulators: generic, specific, and adaptive simulation.