Computers, as we know them, are disappearing. Instead of stand-alone devices for word processing or browsing the web, computers are rapidly becoming integrated into everything from smart phones and smart meters to autonomous planes, trains, and automobiles. These compute engines are embedded to imbue these objects with intelligence to interact with the world independently, or to provide value-added services to the human-machine interface. The quest for real-time, autonomous intelligent systems requires new architectures that enable software productivity, and still yield high performance, predictable and low-latency execution, with ultra-low power consumption. In particular, power efficiency is essential to support mobility or autonomous operation for long periods of time. The Stillwater KPU is a distributed data flow processor that offers performance/power densities of 50GFlops/Watt @40nm and 100GFlops/Watt @28nm. It supports fine-grain parallel execution of the inherent parallelism of the algorithm. Because the processing elements are data flow machines they do away with the instruction fetch and decode pipeline of a sequential processor. A typical KPU processing element is 60% smaller than an equivalent sequential processor. Finally, the KPU does not require cache hierarchies to reduce memory latency, reducing the die size of a typical system by 50% or more.