Abstract
Computational accelerators such as GPUs, FPGAs and many-core accelerators can dramatically improve the performance of computing systems and catalyze highly demanding applications. Many scientific and commercial applications are beginning to integrate computational accelerators in their code. However, programming accelerators for high performance remains a challenge, resulting from the restricted architectural features of accelerators compared to general purpose CPUs. Moreover, software must conjointly use conventional CPUs with accelerators to support legacy code and benefit from general purpose operating system services. The objective of this topic is to provide a forum for exchanging new ideas and findings in the domain of accelerator-based computing.
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© 2013 Springer-Verlag Berlin Heidelberg
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Maruyama, N., Kobbelt, L., Balaji, P., Puzovic, N., Thibault, S., Zhou, K. (2013). Topic 15: GPU and Accelerator Computing. In: Wolf, F., Mohr, B., an Mey, D. (eds) Euro-Par 2013 Parallel Processing. Euro-Par 2013. Lecture Notes in Computer Science, vol 8097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40047-6_79
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DOI: https://doi.org/10.1007/978-3-642-40047-6_79
Publisher Name: Springer, Berlin, Heidelberg
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