Virtualized FPGA Accelerators for Efficient Cloud Computing
作者： Suhaib A Fahmy , Kizheppatt Vipin , Shanker Shreejith
关键词:
摘要: Hardware accelerators implement custom architectures to significantly speed up computations in a wide range of domains. As performance scaling server-class CPUs slows, we propose the integration hardware cloud as way maintain positive trend. Field programmable gate arrays (FPGAs) represent ideal integrate cloud, since they can be reprogrammed needs change and allow multiple share optimised communication infrastructure. We discuss framework that integrates reconfigurable standard server with virtualised resource management communication. then present case study quantifies efficiency benefits break-even point for integrating FPGAs cloud.
warwick.ac.uk
nu.edu.kz
acm.org 参考文章(16)
Byung-Gon Chun, Gunho Lee, H. Katz, Heterogeneity-aware resource allocation and scheduling in the cloud ieee international conference on cloud computing technology and science. pp. 4- 4 ,(2011) , 10.5555/2170444.2170448
Vignesh T. Ravi, Michela Becchi, Gagan Agrawal, Srimat Chakradhar, Supporting GPU sharing in cloud environments with a transparent runtime consolidation framework Proceedings of the 20th international symposium on High performance distributed computing - HPDC '11. pp. 217- 228 ,(2011) , 10.1145/1996130.1996160
Srinidhi Kestur, John D. Davis, Oliver Williams, BLAS Comparison on FPGA, CPU and GPU ieee computer society annual symposium on vlsi. pp. 288- 293 ,(2010) , 10.1109/ISVLSI.2010.84
Shuichi Asano, Tsutomu Maruyama, Yoshiki Yamaguchi, Performance comparison of FPGA, GPU and CPU in image processing field-programmable logic and applications. pp. 126- 131 ,(2009) , 10.1109/FPL.2009.5272532
J. Gregory Steffan, Hadi Bannazadeh, Stuart Byma, Paul Chow, Alberto Leon Garcia, FPGAs in the Cloud: Booting Virtualized Hardware Accelerators with OpenStack field-programmable custom computing machines. pp. 109- 116 ,(2014) , 10.1109/.40
Matthew Jacobsen, Ryan Kastner, RIFFA 2.0: A reusable integration framework for FPGA accelerators field-programmable logic and applications. pp. 1- 8 ,(2013) , 10.1109/FPL.2013.6645504
Kizheppatt Vipin, Suhaib A. Fahmy, ZyCAP : efficient partial reconfiguration management on the Xilinx Zynq IEEE Embedded Systems Letters. ,vol. 6, pp. 41- 44 ,(2014) , 10.1109/LES.2014.2314390
S.C. Goldstein, H. Schmit, M. Budiu, S. Cadambi, M. Moe, R.R. Taylor, PipeRench: a reconfigurable architecture and compiler Computer. ,vol. 33, pp. 70- 77 ,(2000) , 10.1109/2.839324
Ken Eguro, Ramarathnam Venkatesan, FPGAs for trusted cloud computing field programmable logic and applications. pp. 63- 70 ,(2012) , 10.1109/FPL.2012.6339242
Johann Hauswald, Michael A. Laurenzano, Yunqi Zhang, Cheng Li, Austin Rovinski, Arjun Khurana, Ronald G. Dreslinski, Trevor Mudge, Vinicius Petrucci, Lingjia Tang, Jason Mars, Sirius: An Open End-to-End Voice and Vision Personal Assistant and Its Implications for Future Warehouse Scale Computers architectural support for programming languages and operating systems. ,vol. 50, pp. 223- 238 ,(2015) , 10.1145/2694344.2694347