Node level heterogeneous architectures have become attractive during the last decade for several reasons: compared to traditional symmetric CPUs, they offer high peak performance and are energy and/or cost efficient. With the increase of fine-grained parallelism in high-performance computing, as well as the introduction of parallelism in workstations, there is an acute need for a good overview and understanding of these architectures. We give an overview of the state-of-the-art in heterogeneous computing, focusing on three commonly found architectures: the Cell Broadband Engine Architecture, graphics processing units (GPUs), and field programmable gate arrays (FPGAs). We present a review of hardware, available software tools, and an overview of state-of-the-art techniques and algorithms. Furthermore, we present a qualitative and quantitative comparison of the architectures, and give our view on the future of heterogeneous computing.

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Abstract-We present a software framework that facilitates the development of OpenGL applications utilizing the limited GPU capacities of a portable client in combination with the high-end rendering hardware on a server. The resulting webapplication uses standard technologies and can be run on a wide variety of devices, such as smart phones, tablets and laptops. The framework is designed so that it is simple to make an existing OpenGL application into a web-application, gradually adding client-side rendering. Furthermore, it provides automatic network scaling to provide interactivity even on poor connections.