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Real-Time Workload Scheduling (RTWS) Algorithm for Cloud
2015
Journal of Information
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We proposed a real-time workload scheduling algorithm that does very well in reducing the number of initial clusters. ...
It can be used as a utility for executing large size of real-time programs. ...
In Sen [11] a Cost-Efficient Task Scheduling (CETS) algorithm for executing larger programs in the cloud is presented using two heuristic strategies for minimizing make-span and monetary cost. ...
doi:10.18488/journal.104/2015.1.1/104.1.36.52
fatcat:mg4h25fvevfnvbp63njxnkmfja
Co-scheduling algorithms for high-throughput workload execution
2015
Journal of Scheduling
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This paper investigates co-scheduling algorithms for processing a set of parallel applications. ...
Instead of executing each application one by one, using a maximum degree of parallelism for each of them, we aim at scheduling several applications concurrently. ...
This work was supported in part by the ANR RESCUE project. The research of Padma Raghavan was supported in part by the The Pennsylvania State University and grants from the U.S. ...
doi:10.1007/s10951-015-0445-x
fatcat:mbkk7zlelvfcvaojcb7lrh5y3m
Scheduling divisible workloads on heterogeneous platforms
2003
Parallel Computing
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In this paper, we discuss several algorithms for scheduling divisible workloads on heterogeneous systems. ...
This multi-round algorithm automatically performs resource selection, a difficult task that was previously left to the user. ...
This is in sharp contrast with the theory of task graph scheduling, which abounds in NP completeness theorems [9, 10] and in inapproximability results [11, 12] . ...
doi:10.1016/s0167-8191(03)00095-4
fatcat:icnokjr6bbe6xmkv6xmwx4j6qy
Analysis of Federated Scheduling for Integer-Valued Workloads
2022
Proceedings of the 30th International Conference on Real-Time Networks and Systems
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In this paper, we propose two new strategies for allocating unit-speed cores to tasks with integer workload and deadline values. ...
In federated scheduling of parallel real-time tasks on multiprocessor systems, high-utilization tasks are allocated dedicated processors on which they execute exclusively. ...
Thanks also to Sanjoy Baruah and Abhishek Singh for sharing their wealth of knowledge in the state-of-the-art. ...
doi:10.1145/3534879.3534892
fatcat:ssqzuf2nbbcrxgv2t3kwove6ja
Adaptive statistical scheduling of divisible workloads in heterogeneous systems
2009
Journal of Scheduling
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in a nondedicated multi-cluster system. ...
Structured as a task farm with different scheduling modes including adaptive single and multi-round scheduling, this novel divisible load theory approach comprises two phases, calibration and execution ...
Since the tasks in a divisible workload must be grouped in order to minimise communication costs in a distributed system, little attention is paid to partitioning using the application structure. ...
doi:10.1007/s10951-009-0138-4
fatcat:jze5qhnqhzbaxhov2z6j72ysyi
Practical Size-based Scheduling for MapReduce Workloads
[article]
2013
arXiv
pre-print
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The benefits of size-based scheduling disciplines are well recognized in a variety of contexts (computer networks, operating systems, etc...), yet, their practical implementation for a system such as Hadoop ...
system, including waiting and serving times - for realistic workloads that we generate according to production traces available in literature. ...
CONCLUSION The problem of scheduling jobs in parallel systems have received a lot of attention in the past, including works that attempted at producing elegant mathematical models of such systems with ...
arXiv:1302.2749v2
fatcat:acq4j6dk6belvhaiqipki5pjbi
Deep Learning Workload Scheduling in GPU Datacenters: Taxonomy, Challenges and Vision
[article]
2022
arXiv
pre-print
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Recently, substantial schedulers are proposed to tailor for DL workloads in GPU datacenters. This paper surveys existing research efforts for both training and inference workloads. ...
More detailed summary with the surveyed paper and code links can be found at our project website: https://github.com/S-Lab-System-Group/Awesome-DL-Scheduling-Papers ...
Third, new scheduling systems are motivated by the emerging DL workloads and applications, as well as users' new requirements. DL workload scheduling in GPU datacenters remains premature. ...
arXiv:2205.11913v3
fatcat:fnbinueyijb4nc75fpzd6hzjgq
Task Scheduling for Highly Concurrent Analytical and Transactional Main-Memory Workloads
2013
Very Large Data Bases Conference
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In addition, we show that analytical queries should issue a low number of tasks in cases of high concurrency, to avoid excessive synchronization, communication and scheduling costs. ...
We integrate our scheduler into a commercial main-memory column-store, and show that it improves the performance of mixed workloads, by up to 12.5% for analytical queries and 370% for transactional queries ...
In highly concurrent analytical workloads with a large number of partitionable operations issuing tasks, granularity of tasks plays an important role in communication, synchronization, and scheduling costs ...
dblp:conf/vldb/PsaroudakisSMA13
fatcat:ml7j4t4borf57lvaq5worwhtlm
Topology-aware GPU scheduling for learning workloads in cloud environments
2017
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis on - SC '17
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This paper presents a new topology-aware workload placement strategy to schedule deep learning jobs on multi-GPU systems. ...
Workload schedulers must consider hardware topology and workload communication requirements in order to allocate CPU and GPU resources for optimal execution time and improved utilization in shared cloud ...
In this paper, we present an algorithm with two new scheduling policies for placing GPU workloads in modern multi-GPU systems. ...
doi:10.1145/3126908.3126933
dblp:conf/sc/AmaralPCSS17
fatcat:vu4i6hn7jbbtjou3f64bkbg4xa
Co-Scheduling Algorithms for High-Throughput Workload Execution
[article]
2013
arXiv
pre-print
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This paper investigates co-scheduling algorithms for processing a set of parallel applications. ...
Instead of executing each application one by one, using a maximum degree of parallelism for each of them, we aim at scheduling several applications concurrently. ...
This work was supported in part by the ANR RESCUE project. The research of Padma Raghavan was supported in part by the The Pennsylvania State University and grants from the U.S. ...
arXiv:1304.7793v1
fatcat:vvagewa77rhoni5yxeez3aak2y
Multitasking workload scheduling on flexible-core chip multiprocessors
2008
Proceedings of the 17th international conference on Parallel architectures and compilation techniques - PACT '08
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FCMPs introduce a new resource allocation and scheduling problem which must determine how many logical processors should be configured, how powerful each processor should be, and where/when each task should ...
While less of an issue for ACMPs, the fixed nature of both these architectures makes them vulnerable to mismatches between the granularity of the cores and the parallelism in the workload, which can cause ...
A slightly different version of this algorithm has been used in a number of studies on scheduling for parallel systems [7] . ...
doi:10.1145/1454115.1454142
dblp:conf/IEEEpact/GulatiKSKB08
fatcat:fhargenf5nbdbgoz6lwsnlknym
Multitasking workload scheduling on flexible core chip multiprocessors
2008
SIGARCH Computer Architecture News
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FCMPs introduce a new resource allocation and scheduling problem which must determine how many logical processors should be configured, how powerful each processor should be, and where/when each task should ...
While less of an issue for ACMPs, the fixed nature of both these architectures makes them vulnerable to mismatches between the granularity of the cores and the parallelism in the workload, which can cause ...
A slightly different version of this algorithm has been used in a number of studies on scheduling for parallel systems [7] . ...
doi:10.1145/1399972.1399981
fatcat:qb6ywen5q5cencktjmaebc4jhe
Cooperative GPGPU Scheduling for Consolidating Server Workloads
2018
IEICE transactions on information and systems
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Making GPUs a time-multiplexing resource is a key to consolidating GPGPU applications (apps) in multi-tenant cloud platforms. However, advanced GPGPU apps pose a new challenge for consolidation. ...
Graphics processing units (GPUs) have become an attractive platform for general-purpose computing (GPGPU) in various domains. ...
Acknowledgements This work was supported in part by the Japan Society for the Promotion of Science (JSPS KAKENHI 15J09761) and Japan Science and Technology Agency (JST CREST JPMJCR1683). ...
doi:10.1587/transinf.2018edp7027
fatcat:gmgxosap7nhxjanmgcv3uniw3y
Workload Scheduling on heterogeneous Mobile Edge Cloud in 5G networks to Minimize SLA Violation
[article]
2020
arXiv
pre-print
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In this paper, we consider a heterogeneous MEC network with numerous mobile users that send their tasks to MEC servers. Each task has a maximum acceptable response time. ...
A solution is to relocate the tasks among MEC servers, called Workload Migration. ...
Resource Management and Scheduling The focus of this group is on how to manage the system by proposing task scheduling and resource management techniques. ...
arXiv:2003.02820v2
fatcat:s65y54lmgrh4pbp742djmrnwti
Using runtime measured workload characteristics in parallel processor scheduling
[chapter]
1996
Lecture Notes in Computer Science
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We consider the use of runtime measured workload characteristics in parallel processor scheduling. ...
, schedulers that use runtime measurements of workload characteristics can significantly outperform schedulers that are oblivious to these characteristics. • Runtime measurements are sufficient for schedulers ...
Acknowledgments Mary Vernon provided insightful comments that helped with both the content and presentation of this work. ...
doi:10.1007/bfb0022293
fatcat:qtkl2t2c4zctzkc237cvcuu2wu
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