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Amrit Panda
Stream processing has emerged as an important model of computation especially in the context of multimedia and communication sub-systems of embedded System-on-Chip (SoC) architectures. The dataflow nature of streaming applications allows them to be most naturally expressed as a set of kernels iteratively operating on continuous streams of data. The kernels are computationally intensive and […]
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Antonio J. Pena, Carlos Reano, Federico Silla, Rafael Mayo, Enrique S. Quintana-Orti, Jose Duato
In this paper we detail the key features, architectural design, and implementation of rCUDA, an advanced framework to enable remote and transparent GPGPU acceleration in HPC clusters. rCUDA allows decoupling GPUs from nodes, forming pools of shared accelerators, which brings enhanced flexibility to cluster configurations. This opens the door to configurations with fewer accelerators than […]
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Lan Vu, Hari Sivaraman, Rishi Bidarkar
Graphics Processing Units (GPU) have become important components in high performance computing (HPC) systems for their massively parallel computing capability and energy efficiency. Virtualization technologies are increasingly applied to HPC to reduce administration costs and improve system utilization. However, virtualizing the GPU to support general purpose computing presents many challenges because of the complexity of […]
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Yusuke Suzuki, Shinpei Kato, Hiroshi Yamada, Kenji Kono
Graphics processing units (GPUs) provide orders-of-magnitude speedup for compute-intensive data-parallel applications. However, enterprise and cloud computing domains, where resource isolation of multiple clients is required, have poor access to GPU technology. This is due to lack of operating system (OS) support for virtualizing GPUs in a reliable manner. To make GPUs more mature system citizens, […]
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Yousuf Sait I, Vijayalakshmi R
With the dawn of virtualization and Infrastructureas-a-Service (IaaS), the comprehensive technical computing community is in view of the use of clouds for their technical computing needs. This is due to the relative scalability, ease of use, advanced user milieu customization abilities clouds provide, as well as many novel computing archetypes available for data-intensive applications. However, […]
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Andrew J. Younge, John Paul Walters, Stephen Crago, Geoffrey C. Fox
With the advent of virtualization and Infrastructure-as-a-Service (IaaS), the broader scientific computing community is considering the use of clouds for their technical computing needs. This is due to the relative scalability, ease of use, advanced user environment customization abilities clouds provide, as well as many novel computing paradigms available for data-intensive applications. However, there is […]
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John Paul Walters, Andrew J. Younge, Dong-In Kang, Ke-Thia Yao, Mikyung Kang, Stephen P. Crago, Geoffrey C. Fox
As more scientific workloads are moved into the cloud, the need for high performance accelerators increases. Accelerators such as GPUs offer improvements in both performance and power efficiency over traditional multi-core processors; however, their use in the cloud has been limited. Today, several common hypervisors support GPU passthrough, but their performance has not been systematically […]
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A. Castello, J. Duato, R. Mayo, A. J. Pena, E. S. Quintana-Orti, V. Roca, F. Silla
Many current high-performance clusters include one or more GPUs per node in order to dramatically reduce application execution time, but the utilization of these accelerators is usually far below 100%. In this context, remote GPU virtualization can help to reduce acquisition costs as well as the overall energy consumption. In this paper, we investigate the […]
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Clementine Maurice, Christoph Neumann, Olivier Heen, Aurelien Francillon
General-Purpose computing on Graphics Processing Units (GPGPU) combined to cloud computing is already a commercial success. However, there is little literature that investigates its security implications. Our objective is to highlight possible information leakage due to GPUs in virtualized and cloud computing environments. We provide insight into the different GPU virtualization techniques, along with their […]
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Andrew J. Younge, John Paul Walters, Steve Crago, Geoffrey C. Fox
With the advent of virtualization and Infrastructure-as-a-Service (IaaS), the broader scientific computing community is considering the use of clouds for their technical computing needs. This is due to the relative scalability, ease of use, advanced user environment customization abilities clouds provide, as well as many novel computing paradigms available for data-intensive applications. However, there is […]
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Mathias Gottschlag, Marius Hillenbrand, Jens Kehne, Jan Stoess, Frank Bellosa
Over the last few years, running high performance computing applications in the cloud has become feasible. At the same time, GPGPUs are delivering unprecedented performance for HPC applications. Cloud providers thus face the challenge to integrate GPGPUs into their virtualized platforms, which has proven difficult for current virtualization stacks. In this paper, we present LoGV, […]
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Samuel Schlachter, Stephen Herbein, Michela Taufer, Shuching Ou, Sandeep Patel, Jeremy S. Logan
Efficiently studying Sodium Dodecyl Sulfate (SDS) molecules’ formations in the presence of different molar concentrations on high-end GPU clusters whose nodes share accelerators exposes us to several challenges, including the need to dynamically adapt the job lengths. Neither virtualization nor lightweight OS solutions can easily support generality, portability, and maintainability in concert. Our solution complements […]
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