Fluid: An Asynchronous High-level Synthesis Tool for Complex Program Structures

Rui Li, Lincoln Berkley, Yihang Yang, and Rajit Manohar

Current high-level synthesis (HLS) tools that generate synchronous logic construct a state machine that schedules program operations in each clock cycle. Rather than this centralized approach, we are developing an HLS methodology tailored to high-performance asynchronous dataflow circuits building on prior work in dataflow synthesis. We propose a new solution to dataflow circuit generation needed when translating real-world programs with complex control flow. We implement our approach in the LLVM compiler framework, and show that our generated circuits achieve better performance in throughput and energy compared to a number of existing HLS tools. We also quantify the benefits of dataflow graph optimizations on the quality of the generated circuits