Performance analysis challenges and framework for high-performance reconfigurable computing

Reconfigurable computing (RC) applications employing both microprocessors and FPGAs have potential for large speedup when compared with traditional (software) parallel applications. However, this potential is marred by the additional complexity of these dual-paradigm systems, making it difficult to identify performance bottlenecks and achieve desired performance. Performance analysis concepts and tools are well researched and widely available for traditional parallel applications but are lacking in RC, despite being of great importance due to the applications’ increased complexity. In this paper, we explore challenges and present new techniques in automated instrumentation, runtime measurement, and visualization of RC application behavior. We also present ideas for integration with conventional performance analysis tools to create a unified tool for RC applications as well as our initial framework for FPGA instrumentation and measurement. Results from a case study are provided using a prototype of this new tool.