A cost-effective critical path approach for service priority selections in grid computing economy

2006 ◽  
Vol 42 (3) ◽  
pp. 1628-1640 ◽  
Author(s):  
Mei Lin ◽  
Zhangxi Lin
Keyword(s):  
Grid Computing ◽  
Critical Path ◽  
Cost Effective ◽  
Service Priority

scholarly journals Power and Area Efficient Clock Stretching and Critical Path Reshaping for Error Resilience

2019 ◽  
Vol 9 (1) ◽  
pp. 5
Author(s):  
Mini Jayakrishnan ◽  
Alan Chang ◽  
Tony Tae-Hyoung Kim
Keyword(s):  
Critical Path ◽  
Error Resilience ◽  
Cost Effective ◽  
Advanced Technology ◽  
Worst Case ◽  
Flip Flop ◽  
Smart Products ◽  
Run Time ◽  
Critical Paths ◽  
And Performance

Energy efficient semiconductor chips are in high demand to cater the needs of today’s smart products. Advanced technology nodes insert high design margins to deal with rising variations at the cost of power, area and performance. Existing run time resilience techniques are not cost effective due to the additional circuits involved. In this paper, we propose a design time resilience technique using a clock stretched flip-flop to redistribute the available slack in the processor pipeline to the critical paths. We use the opportunistic slack to redesign the critical fan in logic using logic reshaping, better than worst case sigma corner libraries and multi-bit flip-flops to achieve power and area savings. Experimental results prove that we can tune the logic and the library to get significant power and area savings of 69% and 15% in the execute pipeline stage of the processor compared to the traditional worst-case design. Whereas, existing run time resilience hardware results in 36% and 2% power and area overhead respectively.

scholarly journals Dynamic Fault-Tolerant Workflow Scheduling with Hybrid Spatial-Temporal Re-Execution in Clouds

Information ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 169 ◽  
Author(s):  
Na Wu ◽  
Decheng Zuo ◽  
Zhan Zhang
Keyword(s):  
Large Scale ◽  
Fault Tolerant ◽  
Critical Path ◽  
High Reliability ◽  
Low Cost ◽  
Cost Effective ◽  
Scientific Workflow ◽  
Workflow Scheduling ◽  
Workflow Execution ◽  
Computing Environments

Improving reliability is one of the major concerns of scientific workflow scheduling in clouds. The ever-growing computational complexity and data size of workflows present challenges to fault-tolerant workflow scheduling. Therefore, it is essential to design a cost-effective fault-tolerant scheduling approach for large-scale workflows. In this paper, we propose a dynamic fault-tolerant workflow scheduling (DFTWS) approach with hybrid spatial and temporal re-execution schemes. First, DFTWS calculates the time attributes of tasks and identifies the critical path of workflow in advance. Then, DFTWS assigns appropriate virtual machine (VM) for each task according to the task urgency and budget quota in the phase of initial resource allocation. Finally, DFTWS performs online scheduling, which makes real-time fault-tolerant decisions based on failure type and task criticality throughout workflow execution. The proposed algorithm is evaluated on real-world workflows. Furthermore, the factors that affect the performance of DFTWS are analyzed. The experimental results demonstrate that DFTWS achieves a trade-off between high reliability and low cost objectives in cloud computing environments.

scholarly journals Experiences with distributed computing for meteorological applications: Grid computing and Cloud computing

2015 ◽  
Vol 8 (2) ◽  
pp. 1171-1199 ◽  
Author(s):  
F. Schüller ◽  
S. Ostermann ◽  
R. Prodan ◽  
G. J. Mayr
Keyword(s):  
Distributed Computing ◽  
Grid Computing ◽  
High Performance ◽  
Cost Effective ◽  
Use Case ◽  
The Core ◽  
Wide Range ◽  
Different Characteristics ◽  
Performance Computing ◽  
Computing Capacity

Abstract. Experiences with three practical meteorological applications with different characteristics are used to highlight the core computer science aspects and applicability of distributed computing to meteorology. Presenting Cloud and Grid computing this paper shows use case scenarios fitting a wide range of meteorological applications from operational to research studies. The paper concludes that distributed computing complements and extends existing high performance computing concepts and allows for simple, powerful and cost effective access to computing capacity.

scholarly journals Cost Effective Implementation of Fixed Point Adders for LUT based FPGAs using Technology Dependent Optimizations

2015 ◽  
Vol 19 (1) ◽  
pp. 14 ◽  
Author(s):  
Burhan Khurshid ◽  
Roohie Naaz
Keyword(s):  
Fixed Point ◽  
Critical Path ◽  
Minimum Cost ◽  
Cost Effective ◽  
Path Delay ◽  
Field Programmable ◽  
Programmable Gate Arrays ◽  
Volume Production ◽  
On Chip ◽  
The Cost

Modern day field programmable gate arrays(FPGAs) have very huge and versatile logic resources resulting inthe migration of their application domain from prototypedesigning to low and medium volume production designing.Unfortunately most of the work pertaining to FPGAimplementations does not focus on the technology dependentoptimizations that can implement a desired functionality withreduced cost. In this paper we consider the mapping of simpleripple carry fixed-point adders (RCA) on look-up table (LUT)based FPGAs. The objective is to transform the given RCABoolean network into an optimized circuit netlist that canimplement the desired functionality with minimum cost. Weparticularly focus on 6-input LUTs that are inherent in all themodern day FPGAs. Technology dependent optimizations arecarried out to utilize this FPGA primitive efficiently and theresult is compared against various adder designs. Theimplementation targets the XC5VLX30-3FF324 device fromXilinx Virtex-5 FPGA family. The cost of the circuit is expressedin terms of the resources utilized, critical path delay and theamount of on-chip power dissipated. Our implementation resultsshow a reduction in resources usage by at least 50%; increase inspeed by at least 10% and reduction in dynamic powerdissipation by at least 30%. All this is achieved without anytechnology independent (architectural) modification.

scholarly journals Experiences with distributed computing for meteorological applications: grid computing and cloud computing

2015 ◽  
Vol 8 (7) ◽  
pp. 2067-2078 ◽  
Author(s):  
F. Oesterle ◽  
S. Ostermann ◽  
R. Prodan ◽  
G. J. Mayr
Keyword(s):  
Distributed Computing ◽  
Grid Computing ◽  
High Performance ◽  
Cost Effective ◽  
Use Case ◽  
The Core ◽  
Wide Range ◽  
Different Characteristics ◽  
Performance Computing ◽  
Computing Capacity

Abstract. Experiences with three practical meteorological applications with different characteristics are used to highlight the core computer science aspects and applicability of distributed computing to meteorology. Through presenting cloud and grid computing this paper shows use case scenarios fitting a wide range of meteorological applications from operational to research studies. The paper concludes that distributed computing complements and extends existing high performance computing concepts and allows for simple, powerful and cost-effective access to computing capacity.

scholarly journals Cost-Effective Resource Provisioning for Real-Time Workflow in Cloud

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Lei Wu ◽  
Ran Ding ◽  
Zhaohong Jia ◽  
Xuejun Li
Keyword(s):  
Big Data ◽  
Data Management ◽  
Real Time ◽  
Critical Path ◽  
Cost Effective ◽  
Resource Provisioning ◽  
Complex Data ◽  
Volume Data ◽  
Workflow Execution ◽  
Time Requirements

In the era of big data, mining and analysis of the enormous amount of data has been widely used to support decision-making. This complex process including huge-volume data collecting, storage, transmission, and analysis could be modeled as workflow. Meanwhile, cloud environment provides sufficient computing and storage resources for big data management and analytics. Due to the clouds providing the pay-as-you-go pricing scheme, executing a workflow in clouds should pay for the provisioned resources. Thus, cost-effective resource provisioning for workflow in clouds is still a critical challenge. Also, the responses of the complex data management process are usually required to be real-time. Therefore, deadline is the most crucial constraint for workflow execution. In order to address the challenge of cost-effective resource provisioning while meeting the real-time requirements of workflow execution, a resource provisioning strategy based on dynamic programming is proposed to achieve cost-effectiveness of workflow execution in clouds and a critical-path based workflow partition algorithm is presented to guarantee that the workflow can be completed before deadline. Our approach is evaluated by simulation experiments with real-time workflows of different sizes and different structures. The results demonstrate that our algorithm outperforms the existing classical algorithms.

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