Kurniawan, Daniar H, Putri, Rani Ayu, Qin, Peiran, Zulkifli, Kahfi S, Sinurat, Ray_A O, Bhimani, Janki, Madireddy, Sandeep, Kistijantoro, Achmad Imam, and Gunawi, Haryadi S. Heimdall: Optimizing Storage I/O Admission with Extensive Machine Learning Pipeline. Retrieved from https://par.nsf.gov/biblio/10636351. Web. doi:10.1145/3689031.3717496.

Kurniawan, Daniar H, Putri, Rani Ayu, Qin, Peiran, Zulkifli, Kahfi S, Sinurat, Ray_A O, Bhimani, Janki, Madireddy, Sandeep, Kistijantoro, Achmad Imam, & Gunawi, Haryadi S. Heimdall: Optimizing Storage I/O Admission with Extensive Machine Learning Pipeline. Retrieved from https://par.nsf.gov/biblio/10636351. https://doi.org/10.1145/3689031.3717496

Kurniawan, Daniar H, Putri, Rani Ayu, Qin, Peiran, Zulkifli, Kahfi S, Sinurat, Ray_A O, Bhimani, Janki, Madireddy, Sandeep, Kistijantoro, Achmad Imam, and Gunawi, Haryadi S. "Heimdall: Optimizing Storage I/O Admission with Extensive Machine Learning Pipeline". Country unknown/Code not available: ACM. https://doi.org/10.1145/3689031.3717496. https://par.nsf.gov/biblio/10636351.

@article{osti_10636351,
place = {Country unknown/Code not available}, title = {Heimdall: Optimizing Storage I/O Admission with Extensive Machine Learning Pipeline}, url = {https://par.nsf.gov/biblio/10636351}, DOI = {10.1145/3689031.3717496}, abstractNote = {}, journal = {}, publisher = {ACM}, author = {Kurniawan, Daniar H and Putri, Rani Ayu and Qin, Peiran and Zulkifli, Kahfi S and Sinurat, Ray_A O and Bhimani, Janki and Madireddy, Sandeep and Kistijantoro, Achmad Imam and Gunawi, Haryadi S}, }