[1] Roy, A., Jingye, X., Chowdhury, H.: Multi-core processors: a new way forward and challenges in microelectronics. In: International Conference on ICM 2008, pp. 454–457 (2008)

[2] Wang, L., Tao, J., von Laszewski, G.: Multicores in cloud computing: research challenges for applications. J. Comput. 5(6), 958–964 (2010)

[3] Nesmachnow, S., Dorronsoro, B., Pecero, J., Bouvry, P.: Energy-aware scheduling on multicore heterogeneous grid computing systems. J. Grid Comput. 11, 1–28 (2013). Springer, Netherlands

[4] NVIDIA: The Benefits of Multiple CPU Cores in Mobile Devices (2011)

[5] Sanati, B., Cheng, A.M.K.: maximizing job benefits on multiprocessor systems using a greedy algorithm. SIGBED Rev. 5, 3:1–3:4 (2008)

[6] Jeet, R., Garg, U.: selective scheduling based on number of processor cores for parallel processing. Int. J. Sci. Res. (IJSR) 4, 1666–1669 (2015)

[7] Papazachos, Z.C., Karatza, H.D.: Gang scheduling in multi-core clusters implementing migrations. Future Gener. Comput. Syst. 27, 1153–1165 (2011)

[8] Xuan, T.T., Do, T.V.: Job scheduling in a computational cluster with multicore processors. In: Nguyen, T.B., Do, T.V., Le Thi, H.A., Nguyen, N.T. (eds.) Advanced Computational Methods for Knowledge Engineering. AISC, vol. 453, pp. 75–84. Springer, Heidelberg (2016). doi: 10.1007/978-3-319-38884-7_6

[9] Grochowski, E., Ronen, R., Shen, J., Wang, P.: Best of both latency and throughput. In: Proceedings of IEEE International Conference on Computer Design: VLSI in Computers and Processors ICCD 2004, pp. 236–243 (2004)

[10] Ellision, B., Minas, L.: Energy Efficiency for Information Technology: How to Reduce Power Consumption in Servers and Data Centers. Intel press, Oakland (2009)

[11] Qi, X., Zhu, D.-K.: Energy efficient block-partitioned multicore processors for parallel applications. J. Comput. Sci. Technol. 26(3), 418–433 (2011)

[12] NVIDIA: Variable SMP - A Multi-Core CPU Architecture for Low Power and High Performance, Technical report, NVIDIA’s Project Kal-El, NVIDIA Corporation (2012)

[13] Shieh, W.-Y., Pong, C.-C.: Energy and transition-aware runtime task scheduling for multicore processors. J. Parallel Distrib. Comput. 73, 1225–1238 (2013)

[14] Lammie, M., Brenner, P., Thain, D.: Scheduling grid workloads on multicor clusters to minimize energy and maximize performance. In: 2009 10th IEEE/ACM International Conference on Grid Computing, pp. 145–152, October 2009

[15] Utrera, G., Tabik, S., Corbalan, J., Labarta, J.: A job scheduling approach for multi-core clusters based on virtual malleability. In: Kaklamanis, C., Papatheodorou, T., Spirakis, P.G. (eds.) Euro-Par 2012. LNCS, vol. 7484, pp. 191–203. Springer, Heidelberg (2012). doi: 10.1007/978-3-642-32820-6_20

[16] Zikos, S., Karatza, H.D.: Performance and energy aware cluster-level scheduling of compute-intensive jobs with unknown service times. Simul. Model. Pract. Theor. 19(1), 239–250 (2011)

[17] Do, T.V., Vu, B.T., Tran, X.T., Nguyen, A.P.: A generalized model for investigating scheduling schemes in computational clusters. Simul. Model. Pract. Theor. 37, 30–42 (2013)

[18] Standard Performance Evaluation Corporation. http://www.spec.org/

[19] SPEC, Acer Incorporated Acer $$AR380 F2$$ , July 2012. http://www.spec.org/power_ssj2008/results/res2012q3/power_ssj2008-20120525-00481.html

[20] SPEC, Fujitsu FUJITSU Server PRIMERGY tx1330 m1, July 2015. https://www.spec.org/power_ssj2008/results/res2015q1/power_ssj2008-20150116-00684.html

[21] SPEC, Acer Incorporated Altos r360 f2, July 2013. https://www.spec.org/power_ssj2008/results/res2013q3/power_ssj2008-20130619-00617.html

[22] SPEC, Fujitsu FUJITSU Server PRIMERGY tx1330 m2, January 2016. https://www.spec.org/power_ssj2008/results/res2016q1/power_ssj2008-20151214-00707.html