Abstract
The acceleration of inexpensive ARM-based computing nodes with high-end CUDA enabled GPGPUs hosted on x86 64 machines using the GVirtuS general-purpose virtualization service is a novel approach to hierarchical parallelism. In this paper we draw the vision of a possible hierarchical remote workload distribution among different devices. Preliminary, but promising, performance evaluation data suggests that the developed technology is suitable for real world applications.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Di Lauro R., Lucarelli, F., Montella, R.: SIaaS-sensing instrument as a service using cloud computing to turn physical instrument into ubiquitous service. In: 2012 IEEE 10th International Symposium on Parallel and Distributed Processing with Applications (ISPA), pp. 861–862. IEEE (2012)
Duato, J., Pena, A.J., Silla, F., Mayo, R., Quintana-Ort, E.S.: rCUDA: reducing the number of GPU-based accelerators in high performance clusters. In: 2010 International Conference on High Performance Computing and Simulation (HPCS), pp. 224–231. IEEE, June 2010
Foster, I., Zhao, Y., Raicu, I., Lu, S.: Cloud computing and grid computing 360-degree compared. In: Grid Computing Environments Workshop, GCE 2008, pp. 1–10. IEEE, November 2008
Giunta, G., Montella, R., Agrillo, G., Coviello, G.: A GPGPU transparent virtualization component for high performance computing clouds. In: D’Ambra, P., Guarracino, M., Talia, D. (eds.) Euro-Par 2010, Part I. LNCS, vol. 6271, pp. 379–391. Springer, Heidelberg (2010)
Giunta, G., Montella, R., Laccetti, G., Isaila, F., Blas, J.G.: A GPU accelerated high performance cloud computing infrastructure for grid computing based virtual environmental laboratory. In: Constantinescu, Z. (ed.) Advances in Grid Computing, pp. 35–43. InTech (2011). ISBN: 978-953-307-301-9
Gupta, V., Gavrilovska, A., Schwan, K., Kharche, H., Tolia, N., Talwar, V., Ranganathan, P.: GViM: GPU-accelerated virtual machines. In: Proceedings of the 3rd ACM Workshop on System-level Virtualization for High Performance Computing, pp. 17–24. ACM, March 2009
Yang, C.T., Huang, C.L., Lin, C.F.: Hybrid CUDA, OpenMP, and MPI parallel programming on multicore GPU clusters. Comput. Phys. Commun. 182(1), 266–269 (2011)
Younge, A.J., Walters, J.P., Crago, S., Fox, G.C.: Evaluating GPU passthrough in Xen for high performance cloud computing. In: Parallel & Distributed Processing Symposium Workshops (IPDPSW), 2014 IEEE International, pp. 852–859. IEEE (2014)
Laccetti, G., Montella, R., Palmieri, C., Pelliccia, V.: The high performance internet of things: using GVirtuS to share high-end GPUs with ARM based cluster computing nodes. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Waśniewski, J. (eds.) PPAM 2013, Part I. LNCS, vol. 8384, pp. 734–744. Springer, Heidelberg (2014)
Montella, R., Foster, I.: Using hybrid grid/cloud computing technologies for environmental data elastic storage, processing, and provisioning. In: Furht, B., Escalante, A. (eds.) Handbook of Cloud Computing, pp. 595–618. Springer, Heidelberg (2010)
Montella, R., Coviello, G., Giunta, G., Laccetti, G., Isaila, F., Blas, J.G.: A general-purpose virtualization service for HPC on cloud computing: an application to GPUs. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Waśniewski, J. (eds.) PPAM 2011, Part I. LNCS, vol. 7203, pp. 740–749. Springer, Heidelberg (2012)
Montella, R., Giunta, G., Laccetti, G.: Virtualizing high-end GPGPUs on ARM clusters for the next generation of high performance cloud computing. Cluster Comput. 17(1), 139–152 (2014)
Montella, R., Kelly, D., Xiong, W., Brizius, A., Elliott, J., Madduri, R., Maheshwari, K., Porter, C., Vilter, P., Wilde, M., Zhang, M., Foster, I.: FACE-IT: a science gateway for food security research. In: Concurrency and Computation: Practice and Experience (2015). doi:10.1002/cpe.3540
Pham, Q., Malik, T., Foster, I., Di Lauro, R., Montella, R.: SOLE: linking research papers with science objects. In: Groth, P., Frew, J. (eds.) IPAW 2012. LNCS, vol. 7525, pp. 203–208. Springer, Heidelberg (2012)
Shi, L., Chen, H., Sun, J., Li, K.: vCUDA: GPU-accelerated high-performance computing in virtual machines. IEEE Trans. Comput. 61(6), 804–816 (2012)
Acknowledgement
This research was supported in part by the Grant Agreement number: 644312 RAPID H2020-ICT-2014/H2020-ICT-2014-1Heterogeneous Secure Multi-level Remote Acceleration Service for Low-Power Integrated Systems and Devices.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Montella, R. et al. (2016). Virtualizing CUDA Enabled GPGPUs on ARM Clusters. In: Wyrzykowski, R., Deelman, E., Dongarra, J., Karczewski, K., Kitowski, J., Wiatr, K. (eds) Parallel Processing and Applied Mathematics. Lecture Notes in Computer Science(), vol 9574. Springer, Cham. https://doi.org/10.1007/978-3-319-32152-3_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-32152-3_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-32151-6
Online ISBN: 978-3-319-32152-3
eBook Packages: Computer ScienceComputer Science (R0)