Using Approximate Computing for the Calculation of Inverse Matrix p-th Roots

M. Lass, T. Kühne, C. Plessl, Embedded Systems Letters (2017).

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Journal Article | English
Abstract
Approximate computing has shown to provide new ways to improve performance and power consumption of error-resilient applications. While many of these applications can be found in image processing, data classification or machine learning, we demonstrate its suitability to a problem from scientific computing. Utilizing the self-correcting behavior of iterative algorithms, we show that approximate computing can be applied to the calculation of inverse matrix p-th roots which are required in many applications in scientific computing. Results show great opportunities to reduce the computational effort and bandwidth required for the execution of the discussed algorithm, especially when targeting special accelerator hardware.
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Embedded Systems Letters
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Lass M, Kühne T, Plessl C. Using Approximate Computing for the Calculation of Inverse Matrix p-th Roots. Embedded Systems Letters. 2017.
Lass, M., Kühne, T., & Plessl, C. (2017). Using Approximate Computing for the Calculation of Inverse Matrix p-th Roots. Embedded Systems Letters.
@article{Lass_Kühne_Plessl_2017, title={Using Approximate Computing for the Calculation of Inverse Matrix p-th Roots}, journal={Embedded Systems Letters}, publisher={IEEE}, author={Lass, Michael and Kühne, Thomas and Plessl, Christian}, year={2017}}
Lass, Michael, Thomas Kühne, and Christian Plessl. “Using Approximate Computing for the Calculation of Inverse Matrix P-Th Roots.” Embedded Systems Letters, 2017.
M. Lass, T. Kühne, and C. Plessl, “Using Approximate Computing for the Calculation of Inverse Matrix p-th Roots,” Embedded Systems Letters, 2017.
Lass, Michael, Thomas Kühne, and Christian Plessl. “Using Approximate Computing for the Calculation of Inverse Matrix P-Th Roots.” Embedded Systems Letters (2017): n. pag. Print.
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