In order to increase computing performance, current and future computer architechtures are parallel. However, modern multi-core CPUs (2-16 cores) uses up to 80% of its resources on non-computational tasks. At the same time, dedicated stream accelerators that contain hundreds of lightweight cores are available. Such stream accelerators are designed for high computational throughput, while sacrificing complexity, thus disabling their ability to run operating systems. They are typically managed by traditional cores to offload resource-intensive operations. Most applications contain a mixture of tasks, some are best suited for multi-cores and others for streaming accelerators, and will ultimately perform best on heterogeneous architectures.
Heterogeneous computing aims to combine the parallelism of traditional multi-core CPUs and accelerator cores to deliver unprecedented levels of performance for simulation and visualization.
We work directly with design of algorithms and their efficient implementation on modern GPU architectures. This requires a deep understanding of the hardware and the problem area.[Read more]
We work with advanced visualization techniques for interactive visualization of large scientific datasets. The mere size of 3D datasets makes it a challenge to achieve realtime visualization[Read more]
We work with integrating the power of a supercomputer into mobile devices, such as laptops and iPhones, by the use of cloud computing. Efficient use of scalable GPU resources in a cloud is a challenging research task.[Read more]
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Trond R Hagen, Research ManagerSINTEF ICT, Dept. Applied MathematicsP.O. Box 124 BlindernNO-0314 Oslo, NorwayPhone: +4722067779 More
