Performance Analysis with High-Level Languages for High-Performance Reconfigurable Computing

High-Level Languages (HLLs) for FPGAs (Field-Programmable Gate Arrays) facilitate the use of reconfigurable computing resources for application developers by using familiar, higher-level syntax, semantics, and abstractions, typically enabling faster development times than with traditional Hardware Description Languages (HDLs). However, this abstraction is typically accompanied by some loss of performance as well as reduced transparency of application behavior, making it difficult to understand and improve application performance. While runtime tools for performance analysis are often featured in development with traditional HLLs for serial and parallel programming, HLL-based applications for FPGAs have an equal or greater need yet lack these tools. This paper presents a novel and portable framework for runtime performance analysis of HLL applications for FPGAs, including a prototype tool for performance analysis with Impulse C, a commercial HLL for FPGAs. As a case study, this tool is used to locate performance bottlenecks in a molecular dynamics application.