Building a KVM-based Hypervisor for a Heterogeneous System Architecture Compliant System
Abstract
Heterogeneous System Architecture (HSA) is an archi-tecture developed by the HSA foundation aiming at reduc-ing programmability barriers as well as improving commu-nication efficiency for heterogeneous computing. For ex-ample, HSA allows heterogeneous computing devices to share the same virtual address space. This feature allows programmers to bypass explicit data copying between devices, as was required in the past. HSA features such as job dispatching through user level queues and memory based signaling help to reduce communication latency between the host and other computing devices. While the new features in HSA enable more efficient heterogeneous computing, they also introduce new chal-lenges to system virtualization, especially in memory virtu-alization and I/O virtualization. This work investigates the issues involved in HSA virtualization and implements a KVM-based hypervisor that supports the main features of HSA inside guest operating systems. Furthermore, this work shows that with the newly introduced hypervisor for HSA, system resources in HSA-compliant AMD Kaveri can be effectively shared between multiple guest operating sys-tems.
References
[1]
General-Purpose Computation on Graic Hardware, http://gpgpu.org/.
[2]
Nvidia CUDA, http://www.nvidia.com/object/cuda_home_new.html.
[3]
J.E. Stone, D. Gohara, G. Shi, OpenCL: a parallel program-ming standard for heterogeneous computing systems, Comput. Sci. Eng. 12 (2010) 66--73.
[4]
Heterogeneous System Architecture (HSA), http://www.hsafoundation.com/
[5]
AMD Kaveri, http://www.amd.com/en-us/products/processors/desktop/a-series-apu.
[6]
A. Kivity, Y. Kamay, D. Laor, U. Lublin, and A. Liguori. kvm: the Linux virtual machine monitor. In OLS 2007: Proceedings of the 2007 Ottawa Linux Symposium.
[7]
AMD I/O Virtualization Technology (IOMMU) Specification, http://developer.amd.com/wordpress/media/2012/10/488821.pdf, 2012.
[8]
Kernel Fusion Driver source code, https://github.com/HSAFoundation/HSA-Drivers-Linux-AMD.
[9]
Rusty Russel. virtio: towards a de-facto standard for virtual I/O devices. In Operating Systems Review, 2008.
[10]
AMD. AMD64 Virtualization Codenamed "Pacifica" Technology: Secure Virtual Machine Architecture Reference Man-ual, May 2005.
[11]
IRQFD, https://lwn.net/Articles/329837/.
[12]
Y. Dong, J. Dai, Z. Huang, H. Guan, K. Tian, Y. Jiang, To-wards high-quality I/O virtualization. SYSTOR 2009.
[13]
AMD OpcnCL APP SDK, http://developer.amd.com/tools-and-sdks/opencl-zone/.
[14]
Portable Computing Language (pocl) for HSA, http://pocl.sourceforge.net/docs/html/hsa.html.
[15]
D. Abramson, J. Jackson, S. Muthrasanallur, G. Neiger, G. Regnier, R. Sankaran, I. Schoinas, R. Uhlig, B. Vembu, and J. Wiegert. Intel virtualization technology for directed I/O. In-tel Technology Journal, 10, August, 2006.
[16]
TIAN, K., DONG, Y., AND COWPERTHWAITE, D. A full gpu virtualization solution with mediated pass-through. In Proc. USENIX ATC (2014).
[17]
NVIDIA. NVIDIA GRID VGX SOFTWARE. http://www.nvidia.com/object/grid-vgx-software.html, 2014.
[18]
DUATO, J., PENA, A. J., SILLA, F., MAYO, R., AND QUINTANA-ORTI, E. rCUDA: Reducing the number of GPU-based accelerators in high performance clusters. In Proc. of IEEE Int'l Conf. on High Performance Computing Simula-tion (2010), pp. 224--231.
[19]
SHI, L., CHEN, H., SUN, J., AND LI, K. vCUDA: GPU-Accelerated High-Performance Computing in Virtual Ma-chines. IEEE Transactions on Computers 61, 6 (2012), 804--816.
[20]
GUPTA, V., GAVRILOVSKA, A., SCHWAN, K., KHARCHE, H., TOLIA, N., TALWAR, V., AND RANGANATHAN, P. GViM: GPU-Accelerated Virtual Ma-chines. In Proc. of ACM Workshop on System-level Virtual-ization for High Performance Computing (2009), pp. 17--24.
[21]
Tien, Tsan-Rong, and Yi-Ping You. "Enabling OpenCL sup-port for GPGPU in Kernel-based Virtual Machine." Software: Practice and Experience 44.5 (2014): 483--510.
[22]
C. Smowton. Secure 3D graics for virtual machines. In EuroSEC'09: Proceedings of the Second European Workshop on System Security. ACM, 2009, pp. 36--43.
[23]
H. A. Lagar-Cavilla, N. Tolia, M. Satyanarayanan, and E. D. Lara. VMM-independent graics acceleration. In Proc. VEE (2007), pp. 33--43
[24]
M. Dowty and J. Sugerman. GPU Virtualization on VMware's Hosted I/O Architecture. ACM SIGOPS Operat-ing Systems Review, 43:73--82, July 2009.
[25]
SUZUKI, Y., KATO, S., YAMADA, H., AND KONO, K. GPUvm: why not virtualizing gpus at the hypervisor? In Pro-ceedings of the 2014 USENIX conference on USENIX An-nual Technical Conference (2014), USENIX Association, pp. 109--120.
Index Terms
- Building a KVM-based Hypervisor for a Heterogeneous System Architecture Compliant System
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Published In
July 2016
167 pages
March 2016186 pagesISBN:9781450339476DOI:10.1145/2892242- General Chair:
- Vishakha Gupta-Cledat,
- Program Chairs:
- Donald E. Porter,
- Vivek Sarkar
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Publication History
Published: 25 March 2016
Published in SIGPLAN Volume 51, Issue 7
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