TIM-8121 v1

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Dharb, G., Mansoor, N., Shahriat, S., & Ganguly, A. (2017). PaSE: A parallel speedup estimation framework for Network-on-Chip based multicore systems [Conference presentation]. 2017 Eighth International Green and Sustainable Computing Conference (IGSC), 1–6.

This resource demonstrates how parallel computing increases speedup.

Perez-Monte, C. F., Farias, F., Rizzi, S., Luciano, C., & Piccoli, M. F. (2018). Speedup in parallel rendering system with computational best-effort scheme. IEEE Latin America Transactions, Latin America Transactions, IEEE (Revista IEEE America Latina), IEEE Latin Am. Trans, 16(3), 987–995.

This resource demonstrates how parallel computing is used in graphics rendering to achieve speedup.

Costa, G. A. O. P., Bentes, C., Ferreira, R. S., Feitosa, R. Q., & Oliveira, D. A. B. (2017). Exploiting different types of parallelism in distributed analysis of remote sensing data. IEEE Geoscience and Remote Sensing Letters, Geoscience and Remote Sensing Letters, IEEE, IEEE Geosci. Remote Sensing Lett, 14(8), 1298–1302.

This resource explores task parallelism in addition to data parallelism and compares the two.