In order to support the expanding demands for processing power from emerging HPC applications within a pragmatic energy envelope, HPC systems incorporate accelerators. Towards this end, one promising approach is the employment of FPGAs and reconfigurable accelerators.
The main advantage of those devices is that they can be reconfigured at run-time to implement tailor-made application accelerators, achieving energy efficiency and/or performance that in most of cases is much higher compared to those of CPUs and GPUs. However, due to management and difficulty in programming and efficiently use the FPGA resources, the FPGA technology is not so widely accepted in the HPC community.
Thus, the project aims at providing guidelines to ease future development of FPGA applications on HPC systems. The goal of the OPTIMA project is to take advantage of FPGA-based High Performance Computing (HPC) systems to optimize academic and industrial software and applications.
The main project objective is the development of demonstrators that will prove the usefulness of deploying applications on HPC FPGA-based systems compared to other classical CPU + GPU HPC or cloud systems. Towards this end, OPTIMA targets to use, tune and evaluate FPGA-based platforms and their programming environments in order to optimize the implementation process of industrial and academic applications. Also, one more objective is the implementation of a set of libraries that are heavily utilized in industry, targeting FPGA-based platforms.
The most important impact on society is that OPTIMA proposes technologies that support the creation of new innovative applications, which will have more features than today’s solutions. OPTIMA will prove that the computing power and development tools required to create the next-gen HPC applications, such as futuristic scenarios for personalized medical treatments or vigilance in near-real-time, can be built around FPGA devices. Based on the OPTIMA outcomes, it will further be demonstrated that we can build HPC systems utilizing FPGAs that are much more energy efficient than current conventional CPU/GPU-based HPC systems while, at the same time, they offer more computational power for certain applications.
