HLScope: High-Level Performance Debugging for FPGA Designs

2017 ◽  
Author(s):  
Young-Kyu Choi ◽  
Jason Cong
Keyword(s):  
Performance Debugging ◽  
High Level ◽  
Level Performance

scholarly journals Enhanced Round-Robin Algorithm in the Cloud Computing Environment for Optimal Task Scheduling

Computers ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 63
Author(s):  
Fahd Alhaidari ◽  
Taghreed Zayed Balharith
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Critical Role ◽  
Turnaround Time ◽  
Round Robin ◽  
Computing Systems ◽  
Time Quantum ◽  
Dynamic Time ◽  
High Level ◽  
Level Performance

Recently, there has been significant growth in the popularity of cloud computing systems. One of the main issues in building cloud computing systems is task scheduling. It plays a critical role in achieving high-level performance and outstanding throughput by having the greatest benefit from the resources. Therefore, enhancing task scheduling algorithms will enhance the QoS, thus leading to more sustainability of cloud computing systems. This paper introduces a novel technique called the dynamic round-robin heuristic algorithm (DRRHA) by utilizing the round-robin algorithm and tuning its time quantum in a dynamic manner based on the mean of the time quantum. Moreover, we applied the remaining burst time of the task as a factor to decide the continuity of executing the task during the current round. The experimental results obtained using the CloudSim Plus tool showed that the DRRHA significantly outperformed the competition in terms of the average waiting time, turnaround time, and response time compared with several studied algorithms, including IRRVQ, dynamic time slice round-robin, improved RR, and SRDQ algorithms.

High level performance metrics for FPGA-based multiprocessor systems

2010 ◽  
Vol 67 (6) ◽  
pp. 417-431 ◽  
Author(s):  
Marta Beltrán ◽  
Antonio Guzmán ◽  
Fernando Sevillano
Keyword(s):  
Performance Metrics ◽  
Multiprocessor Systems ◽  
High Level ◽  
Level Performance

scholarly journals A Methodology for Generation of Performance Models for the Sizing of Analog High-Level Topologies

VLSI Design ◽  
2011 ◽  
Vol 2011 ◽  
pp. 1-17
Author(s):  
Soumya Pandit ◽  
Chittaranjan Mandal ◽  
Amit Patra
Keyword(s):  
Regression Function ◽  
Support Vector ◽  
Detailed Knowledge ◽  
Performance Models ◽  
Construction Time ◽  
Level Model ◽  
The Individual ◽  
High Level ◽  
Sequence Generator ◽  
Level Performance

This paper presents a systematic methodology for the generation of high-level performance models for analog component blocks. The transistor sizes of the circuit-level implementations of the component blocks along with a set of geometry constraints applied over them define the sample space. A Halton sequence generator is used as a sampling algorithm. Performance data are generated by simulating each sampled circuit configuration through SPICE. Least squares support vector machine (LS-SVM) is used as a regression function. Optimal values of the model hyper parameters are determined through a grid search-based technique and a genetic algorithm- (GA-) based technique. The high-level models of the individual component blocks are combined analytically to construct the high-level model of a complete system. The constructed performance models have been used to implement a GA-based high-level topology sizing process. The advantages of the present methodology are that the constructed models are accurate with respect to real circuit-level simulation results, fast to evaluate, and have a good generalization ability. In addition, the model construction time is low and the construction process does not require any detailed knowledge of circuit design. The entire methodology has been demonstrated with a set of numerical results.

A Model for Performance-Intelligent Design Advisors

1993 ◽  
Author(s):  
R. Grant Reed ◽  
Robert H. Sturges
Keyword(s):  
Intelligent Design ◽  
Specific Design ◽  
Design Information ◽  
Domain Specific ◽  
Computer Based ◽  
Level Design ◽  
And Performance ◽  
High Level ◽  
Level Performance ◽  
Inputs And Outputs

Abstract We consider a design advisor to be performance-intelligent when its suggestions do not conflict with high level performance-related goals of the design under study. We address the problem of representing non-domain-specific design Information at a high level and describe coupling it to the inputs and outputs of design critics and their suggestion mechanisms. High level design Information represented in a function-based structure with linked allocations is shown to interact with a domain-specific design critic in three instances, viz.: allocation refinement, goal matching with a supported function, and performance-intelligent tradeoffs. Examples of manual and computer-based procedures are discussed.

The Effectiveness of Online Task Support vs. Instructor-Led Training

2011 ◽  
pp. 77-100 ◽  
Author(s):  
Ji-Ye Mao ◽  
Bradley R. Brown
Keyword(s):  
Mental Models ◽  
Mental Model ◽  
Performance Difference ◽  
Model Completeness ◽  
Task Support ◽  
Microsoft Access ◽  
Novice Users ◽  
The Difference ◽  
High Level ◽  
Level Performance

This study investigates the effectiveness of online task support (the wizard type in particular) relative to instructor-led training, and explores the underlying cognitive process in terms of the development of mental models. Ninety-two novice users of Microsoft Access were either trained by an experienced instructor or performed exercises with online task support, and then completed a variety of performance-based tests. Analysis shows that users of online task support tended to outperform instructor-trained individuals on high-level tasks, whereas the performance difference on low-level tasks was not significant. The cognitive processes underlying the difference are also noteworthy. Task support users were more likely to develop conceptual mental models as opposed to procedural ones, which accounted for their better high-level performance. Mental model completeness was also found to be closely associated with performance on both low and high-level tasks. These findings offer support for increased use of online task support.

Strength, Conditioning, and Nutritional Considerations for High-Level Performers

2020 ◽  
Vol 9 (1) ◽  
pp. 31-40
Author(s):  
Richard B. Kreider
Keyword(s):  
Performance Enhancement ◽  
Professional Preparation ◽  
Sport Nutrition ◽  
Future Trends ◽  
Strength And Conditioning ◽  
Career Opportunities ◽  
High Level ◽  
Program Components ◽  
The Impact ◽  
Level Performance

Strength, conditioning, and nutrition play an important role in preparing athletes to perform to the best of their ability. For this reason, nearly all competitive teams employ strength and conditioning specialists to prepare their athletes for competition, and most teams have sport dietitians and/or nutrition consultants as part of their performance-enhancement team. Academic and professional preparation of strength and conditioning and sport-nutrition specialists in kinesiology programs has opened up a number of career opportunities for students and scholars. In addition, advances in technology have enhanced the ability of strength and conditioning specialists and sport nutritionists to monitor athletes during training and competition. This paper provides an overview of the history, professional preparation, program components, and general principals of strength and conditioning and sport nutrition and the impact they have had on high-level performance, as well as future trends in these fields.

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