13,808 research outputs found
QuickCast: Fast and Efficient Inter-Datacenter Transfers using Forwarding Tree Cohorts
Large inter-datacenter transfers are crucial for cloud service efficiency and
are increasingly used by organizations that have dedicated wide area networks
between datacenters. A recent work uses multicast forwarding trees to reduce
the bandwidth needs and improve completion times of point-to-multipoint
transfers. Using a single forwarding tree per transfer, however, leads to poor
performance because the slowest receiver dictates the completion time for all
receivers. Using multiple forwarding trees per transfer alleviates this
concern--the average receiver could finish early; however, if done naively,
bandwidth usage would also increase and it is apriori unclear how best to
partition receivers, how to construct the multiple trees and how to determine
the rate and schedule of flows on these trees. This paper presents QuickCast, a
first solution to these problems. Using simulations on real-world network
topologies, we see that QuickCast can speed up the average receiver's
completion time by as much as while only using more
bandwidth; further, the completion time for all receivers also improves by as
much as faster at high loads.Comment: [Extended Version] Accepted for presentation in IEEE INFOCOM 2018,
Honolulu, H
A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing
Data Grids have been adopted as the platform for scientific communities that
need to share, access, transport, process and manage large data collections
distributed worldwide. They combine high-end computing technologies with
high-performance networking and wide-area storage management techniques. In
this paper, we discuss the key concepts behind Data Grids and compare them with
other data sharing and distribution paradigms such as content delivery
networks, peer-to-peer networks and distributed databases. We then provide
comprehensive taxonomies that cover various aspects of architecture, data
transportation, data replication and resource allocation and scheduling.
Finally, we map the proposed taxonomy to various Data Grid systems not only to
validate the taxonomy but also to identify areas for future exploration.
Through this taxonomy, we aim to categorise existing systems to better
understand their goals and their methodology. This would help evaluate their
applicability for solving similar problems. This taxonomy also provides a "gap
analysis" of this area through which researchers can potentially identify new
issues for investigation. Finally, we hope that the proposed taxonomy and
mapping also helps to provide an easy way for new practitioners to understand
this complex area of research.Comment: 46 pages, 16 figures, Technical Repor
End-host based mechanisms for implementing Flow Scheduling in GridNetworks
In Grids, transfer jobs and network resources need to be managed in a more deterministic way than in the Internet. New approaches like flow scheduling are proposed and studied as alternatives to traditional QoS and reservation proposals. To enable such flow scheduling approaches, run-time mechanisms controlling flow sending time and rate have to be implemented in the data plane. This paper quantify and compares in a range of latency conditions, such end-host based mechanisms combined with transport protocols to instantiate different scheduling strategies. We show that, in high speed network, a single-rate scheduling strategy implemented by an AIMD-based protocol with packet pacing mechanism offers predictable performance and is insensitive to latency. This paper also highlights the limits of other strategies and rate limitation mechanisms like token bucket which may present unpredictability and other drawbacks
Datacenter Traffic Control: Understanding Techniques and Trade-offs
Datacenters provide cost-effective and flexible access to scalable compute
and storage resources necessary for today's cloud computing needs. A typical
datacenter is made up of thousands of servers connected with a large network
and usually managed by one operator. To provide quality access to the variety
of applications and services hosted on datacenters and maximize performance, it
deems necessary to use datacenter networks effectively and efficiently.
Datacenter traffic is often a mix of several classes with different priorities
and requirements. This includes user-generated interactive traffic, traffic
with deadlines, and long-running traffic. To this end, custom transport
protocols and traffic management techniques have been developed to improve
datacenter network performance.
In this tutorial paper, we review the general architecture of datacenter
networks, various topologies proposed for them, their traffic properties,
general traffic control challenges in datacenters and general traffic control
objectives. The purpose of this paper is to bring out the important
characteristics of traffic control in datacenters and not to survey all
existing solutions (as it is virtually impossible due to massive body of
existing research). We hope to provide readers with a wide range of options and
factors while considering a variety of traffic control mechanisms. We discuss
various characteristics of datacenter traffic control including management
schemes, transmission control, traffic shaping, prioritization, load balancing,
multipathing, and traffic scheduling. Next, we point to several open challenges
as well as new and interesting networking paradigms. At the end of this paper,
we briefly review inter-datacenter networks that connect geographically
dispersed datacenters which have been receiving increasing attention recently
and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial
Enabling preemptive multiprogramming on GPUs
GPUs are being increasingly adopted as compute accelerators in many domains, spanning environments from mobile systems to cloud computing. These systems are usually running multiple applications, from one or several users. However GPUs do not provide the support for resource sharing traditionally expected in these scenarios. Thus, such systems are unable to provide key multiprogrammed workload requirements, such as responsiveness, fairness or quality of service. In this paper, we propose a set of hardware extensions that allow GPUs to efficiently support multiprogrammed GPU workloads. We argue for preemptive multitasking and design two preemption mechanisms that can be used to implement GPU scheduling policies. We extend the architecture to allow concurrent execution of GPU kernels from different user processes and implement a scheduling policy that dynamically distributes the GPU cores among concurrently running kernels, according to their priorities. We extend the NVIDIA GK110 (Kepler) like GPU architecture with our proposals and evaluate them on a set of multiprogrammed workloads with up to eight concurrent processes. Our proposals improve execution time of high-priority processes by 15.6x, the average application turnaround time between 1.5x to 2x, and system fairness up to 3.4x.We would like to thank the anonymous reviewers, Alexan-
der Veidenbaum, Carlos Villavieja, Lluis Vilanova, Lluc Al-
varez, and Marc Jorda on their comments and help improving
our work and this paper. This work is supported by Euro-
pean Commission through TERAFLUX (FP7-249013), Mont-
Blanc (FP7-288777), and RoMoL (GA-321253) projects,
NVIDIA through the CUDA Center of Excellence program,
Spanish Government through Programa Severo Ochoa (SEV-2011-0067) and Spanish Ministry of Science and Technology
through TIN2007-60625 and TIN2012-34557 projects.Peer ReviewedPostprint (author’s final draft
C-MOS array design techniques: SUMC multiprocessor system study
The current capabilities of LSI techniques for speed and reliability, plus the possibilities of assembling large configurations of LSI logic and storage elements, have demanded the study of multiprocessors and multiprocessing techniques, problems, and potentialities. Evaluated are three previous systems studies for a space ultrareliable modular computer multiprocessing system, and a new multiprocessing system is proposed that is flexibly configured with up to four central processors, four 1/0 processors, and 16 main memory units, plus auxiliary memory and peripheral devices. This multiprocessor system features a multilevel interrupt, qualified S/360 compatibility for ground-based generation of programs, virtual memory management of a storage hierarchy through 1/0 processors, and multiport access to multiple and shared memory units
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