Effects of Topology-Aware Allocation Policies on Scheduling Performance

Pascual, José Antonio; Navaridas, Javier; Miguel-Alonso, José

doi:10.1007/978-3-642-04633-9_8

Cited by 25 publications

(12 citation statements)

References 12 publications

(22 reference statements)

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“…To improve the cloud utilization, we could equally rely on a non-FIFO policy, e.g. by using back-filling, reservations, or a jointly-optimal allocation of multiple tenants [32]. Fault Tolerance.…”

Section: Discussionmentioning

confidence: 99%

“…Network isolation. Specific high-dimensional tori super-computers like IBM BlueGene, Cray XE6, and the Fujitsu K-computer provide scheduling techniques to isolate tenants [31][32][33]. However, they all rely on forming an isolated cube on 3 out of the 5-or 6dimensional torus space, and thus cannot be used in clouds with fat-tree topologies.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Links as a Service (LaaS): Guaranteed Tenant Isolation in the Shared Cloud

Zahavi

Shpiner

Rottenstreich

et al. 2019

IEEE J. Select. Areas Commun.

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The most demanding tenants of shared clouds require complete isolation from their neighbors, in order to guarantee that their application performance is not affected by other tenants. Unfortunately, while shared clouds can offer an option whereby tenants obtain dedicated servers, they do not offer any network provisioning service, which would shield these tenants from network interference.In this paper, we introduce Links as a Service (LaaS), a new abstraction for cloud service that provides isolation of network links. Each tenant gets an exclusive set of links forming a virtual fat-tree, and is guaranteed to receive the exact same bandwidth and delay as if it were alone in the shared cloud. Consequently, each tenant can use the forwarding method that best fits its application. Under simple assumptions, we derive theoretical conditions for enabling LaaS without capacity over-provisioning in fat-trees. New tenants are only admitted in the network when they can be allocated hosts and links that maintain these conditions. LaaS is implementable with common network gear, tested to scale to large networks and provides full tenant isolation at the worst cost of a 10% reduction in the cloud utilization.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Links as a Service (LaaS): Guaranteed Tenant Isolation in the Shared Cloud

Zahavi

Shpiner

Rottenstreich

et al. 2019

IEEE J. Select. Areas Commun.

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“…The ARM-Micro-Cluster, composed by 8 Firefly-RK3399 single-boards, is based on Ubuntu 18.04 Linux and scheduled using SLURM [27]. The interconnect is based on Gigabit Ethernet, and the storage system is a device shared via NFS.…”

Section: Arm-micro-clustermentioning

confidence: 99%

Performance and Energy Footprint Assessment of FPGAs and GPUs on HPC Systems Using Astrophysics Application

et al. 2020

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New challenges in Astronomy and Astrophysics (AA) are urging the need for a large number of exceptionally computationally intensive simulations. "Exascale" (and beyond) computational facilities are mandatory to address the size of theoretical problems and data coming from the new generation of observational facilities in AA. Currently, the High Performance Computing (HPC) sector is undergoing a profound phase of innovation, in which the primary challenge to the achievement of the "Exascale" is the power-consumption. The goal of this work is to give some insights about performance and energy footprint of contemporary architectures with a real astrophysical application in an HPC context. We use a state-of-theart N-body application that we re-engineered and optimized to exploit the heterogeneous underlying hardware fully. We quantitatively evaluate the impact of computation on energy consumption when running on four different platforms. Two of them represent the current HPC systems (Intel-based and equipped with NVIDIA GPUs), one is a micro-cluster based on ARM-MPSoC, and one is a "prototype towards Exascale" equipped with ARM-MPSoCs tightly coupled with FPGAs. We investigate the behaviour of the different devices where the high-end GPUs excel in terms of time-to-solution while MPSoC-FPGA systems outperform GPUs in power consumption. Our experience reveals that considering FPGAs for computationally intensive application seems very promising, as their performance is improving to meet the requirements of scientific applications. This work can be a reference for future platforms development for astrophysics applications where computationally intensive calculations are required.

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“…The auction mechanism is similar to our previous work on multi‐unit non‐discriminatory combinatorial auctions. In , a quasi‐contiguous approach is used to reduce the severe scheduling inefficiencies and demonstrated using the INSEE simulator .…”

Section: Related Workmentioning

confidence: 99%

A new auction‐based scheduler for heterogeneous systems with moldable generic resources support

Soner

Özturan

2015

Concurrency and Computation

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SUMMARYSlurm resource management system is used on many TOP500 supercomputers. We present a new auctionbased heterogeneous cluster scheduler plug-in called AUCSCHED2. AUCSCHED2 contributes two major enhancements: the first is the extension of Slurm to support generic resource moldability by specification of resource ranges. The generic resources include accelerators like graphics processing unit or Xeon Phi. The current version of Slurm supports specification of node ranges but not of generic resource ranges. Such a feature can be very useful to run-time auto-tuning applications and systems that can make use of variable number of generic resources. The second enhancement involves the implementation of a new integer programming formulation in AUCSCHED2 that drastically reduces the number of variables. This allows faster solution and larger number of bids to be generated. Slurm emulation results are presented for the heterogeneous 1408 node Tsubame supercomputer, which has 12 cores and three graphics processing units on each of its nodes. AUCSCHED2 is available at https://github.com/aucsched/aucsched2.

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Effects of Topology-Aware Allocation Policies on Scheduling Performance

Cited by 25 publications

References 12 publications

Links as a Service (LaaS): Guaranteed Tenant Isolation in the Shared Cloud

Links as a Service (LaaS): Guaranteed Tenant Isolation in the Shared Cloud

Performance and Energy Footprint Assessment of FPGAs and GPUs on HPC Systems Using Astrophysics Application

A new auction‐based scheduler for heterogeneous systems with moldable generic resources support

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