Data-parallel applications, such as data analytics, machine learning, and\nscientific computing, are placing an ever-growing demand on floating-point\noperations per second on emerging systems. With increasing integration density,\nthe quest for energy efficiency becomes the number one design concern. While\ndedicated accelerators provide high energy efficiency, they are\nover-specialized and hard to adjust to algorithmic changes. We propose an\narchitectural concept that tackles the issues of achieving extreme en…