A Comprehensive Survey of Domain-Specific Hardware Acceleration in Scientific Computing

Abstract

Technology progress has changed the way research and development tasks are done. The capability to perform intricate system modeling and simulation is now crucial in engineering, physics, chemistry, biology, and other industries relying on scientific computing. As these scientific computing workloads require quick and efficient execution, there is an increasing need for disruptive technology. This is where hardware accelerators enter the picture. These accelerators, capable of managing intricate systems modeling and simulation, hold promise for improving precision and dependability in research and development results, thereby saving time and resources. In this survey, we define, summarize, and analyze the accelerators required in different scientific computing domains. We have also proposed a taxonomy based on these aspects: implementation methods; types of implementations; host coupling; cost factors; and applications, grouped into five macro-categories. Then we observed and categorized the intersection of micro-architectures with differential equations in three areas in the scientific computing domain, like acceleration for higher-order nonlinear systems, acceleration based on differential equations using off-the-shelf accelerators, and finally acceleration using customized co-processors. Lastly, we finish the survey by giving a brief summary. We think that these methods will be useful for researchers who are aiming to make new hardware accelerators in the scientific computing area.