Javier Garcia Blas

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Massively parallel architectures are mainly based on a parallel heterogeneous setup. They are composed by different computing devices that speed up specific code regions, named kernels. These kernels are usually executed offline in the corresponding devices. Porting applications to a specific heterogeneous platform is a costly task in terms of time and(More)
With the emergence of heterogeneous architectures, developing parallel software has become an increasingly complex task. The ability of using multiple devices in a single application, such as CPUs, accelerators, or coprocessors, has turned the implementation and optimization tasks into a challenging process, which comes along with a variety of difficulties.(More)
Current storage trends dictate placing fast storage devices in all servers and using them as a single distributed storage system. In this converged model where storage and compute resources co-exist in the same server, the role of the network is becoming more important: network overhead is becoming a main limitation to improving storage performance. In our(More)
The increasing data demands of applications from various domains and the decreasing relative power cost of CPU computation have gradually exposed data movement cost as the prominent factor of energy consumption in computing systems. The traditional organization of the computer system software into a layered stack, while providing a straightforward(More)
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