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Perry H. Wang, Jamison D. Collins, Gautham N. Chinya, Hong Jiang, Xinmin Tian, Milind Girkar, Nick Y. Yang, Guei Y. Lueh, Hong Wang
Future mainstream microprocessors will likely integrate specialized accelerators, such as GPUs, onto a single die to achieve better performance and power efficiency. However, it remains a keen challenge to program such a heterogeneous multicore platform, since these specialized accelerators feature ISAs and functionality that are significantly different from the general purpose CPU cores. In this […]
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Gautham N. Chinya, Jamison D. Collins, Perry H. Wang, Hong Jiang, Guei Y. Lueh, Thomas A. Piazza, Hong Wang
In this paper, we introduce Bothnia, an extension to the Intel production graphics driver to support a shared virtual memory heterogeneous multithreading programming model. With Bothnia, the Intel graphics device driver can support both the traditional 3D graphics rendering software stack and a new class of heterogeneous multithreaded applications, which can use both IA (Intel […]
Michael D. Linderman, Jamison D. Collins, Hong Wang, Teresa H. Meng
In this paper we propose the Merge framework, a general purpose programming model for heterogeneous multi-core systems. The Merge framework replaces current ad hoc approaches to parallel programming on heterogeneous platforms with a rigorous, library-based methodology that can automatically distribute computation across heterogeneous cores to achieve increased energy and performance efficiency. The Merge framework provides […]
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