A comparison between the usage of free and proprietary solutions for General-purpose computing on GPUs (GPGPU)
In this research project, we explore the usage of open-source and proprietary solutions for performing general-purpose computing on graphics processing units (GPGPU). We begin by categorizing projects them according to their descriptions using unsupervised machine learning. Then, we compare the performance and usability of the solutions in each category, proposing enhancements to better support the development of open-source GPGPU tooling.
Barker, M., Chue Hong, N. P., Katz, D. S., Lamprecht, A.-L., Martinez-Ortiz, C., Psomopoulos, F., Harrow, J., Castro, L. J., Gruenpeter, M., Martinez, P. A., et al. (2022). Introducing the fair principles for research software. Scientific Data, 9(1):1–6.
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Carver, J. C., Weber, N., Ram, K., Gesing, S., and Katz, D. S. (2022). A survey of the state of the practice for research software in the united states. PeerJ Computer Science, 8:e963.
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Katz, D. S., McInnes, L. C., Bernholdt, D. E., Mayes, A. C., Hong, N. P. C., Duckles, J., Gesing, S., Heroux, M. A., Hettrick, S., Jimenez, R. C., et al. (2018). Community organizations: Changing the culture in which research software is developed and sustained. Computing in Science & Engineering, 21(2):8–24.
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Wilson, G., Aruliah, D. A., Brown, C. T., Chue Hong, N. P., Davis, M., Guy, R. T., Haddock, S. H., Huff, K. D., Mitchell, I. M., Plumbley, M. D., et al. (2014). Best practices for scientific computing. PLoS biology, 12(1):e1001745.
Zheng, Z., Wang, L., Xu, J., Wu, T., Wu, S., and Tao, X. (2018). Measuring and predicting the relevance ratings between floss projects using topic features. In Proceedings of the Tenth Asia-Pacific Symposium on Internetware, pages 1–10.