In the broad sense, heterogeneous computing refers to systems that use more than one kind of processor or cores. Different processors in a heterogeneous system incorporate specialized processing capabilities to handle particular tasks, which allow designers to maximize some performance metric, such as latency, throughput, or energy efficiency. Modern technologies available in the market include traditional multi-core general purpose CPUs, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), and general-purpose graphics processing units (GPUs). Mixing and matching traditional and unconventional cores break away from the conventional evolutionary processor design path, posing new challenges and opportunities in high-performance computing.

 

With the widely advertised end of Moore's Law, heterogeneous computing has been recognized as a short-term enabler for coping with the ever-increasing and evolving demands of Big Data, Internet-of-Things, machine learning, etc. This talk will present a general overview of the main concepts related to heterogeneous and specialized computing architectures, and discuss experiences and case studies related to the use of these technologies in multiple application domains.