The slowdown in transistor scaling and the end of Moore’s law indicate a need to invest in new computing paradigms; specialized hardware devices, such as FPGAs and ASICs, are a promising solution as they can achieve high processing capabilities and energy efficiency. However, a major barrier to the global success of specialized computing is the difficulty of hardware design. High-level synthesis (HLS) tools generate digital hardware designs from high-level programming languages (e.g., C/C++) and promise to liberate designers from low-level hardware description details. Yet, HLS tools are still acceptable only for certain classes of applications and criticized for the difficulty of extracting the desired level of performance: generating good circuits still requires tedious code restructuring and hardware design expertise. In this talk, I will present a new HLS methodology that produces dynamically scheduled, dataflow circuits out of C/C++ code; the resulting circuits achieve good performance out-of-the-box and realize behaviors that are beyond the capabilities of standard HLS tools. I will describe mathematical models to optimize the performance and area of the resulting circuits, as well as techniques to achieve characteristics that standard HLS cannot support, such as out-of-order memory accesses and speculative execution. These contributions redefine the HLS paradigm by introducing characteristics of modern superscalar processors to hardware designs; such behaviors are key for specialized computing to be successful in new contexts and broader application domains.