scholarly journals Available Task-Level Parallelism on the Cell BE

2009 ◽  
Vol 17 (1-2) ◽  
pp. 59-76 ◽  
Author(s):  
Alejandro Rico ◽  
Alex Ramirez ◽  
Mateo Valero
Keyword(s):  
Power Efficiency ◽  
Chip Multiprocessors ◽  
Programming Model ◽  
Heterogeneous Systems ◽  
Fundamental Aspect ◽  
Suitable Model ◽  
Task Management ◽  
Working Set ◽  
The Impact ◽  
Order Execution

There is a clear industrial trend towards chip multiprocessors (CMP) as the most power efficient way of further increasing performance. Heterogeneous CMP architectures take one more step along this power efficiency trend by using multiple types of processors, tailored to the workloads they will execute. Programming these CMP architectures has been identified as one of the main challenges in the near future, and programming heterogeneous systems is even more challenging. High-level programming models which allow the programmer to identify parallel tasks, and the runtime management of the inter-task dependencies, have been identified as a suitable model for programming such heterogeneous CMP architectures. In this paper we analyze the performance of Cell Superscalar, a task-based programming model for the Cell Broadband Engine Architecture, in terms of its scalability to higher number of on-chip processors. Our results show that the low performance of the PPE component limits the scalability of some applications to less than 16 processors. Since the PPE has been identified as the limiting element, we perform a set of simulation studies evaluating the impact of out-of-order execution, branch prediction and larger caches on the task management overhead. We conclude that out-of-order execution is a very desirable feature, since it increases task management performance by 50%. We also identify memory latency as a fundamental aspect in performance, while the working set is not that large. We expect a significant performance impact if task management would run using a fast private memory to store the task dependency graph instead of relying on the cache hierarchy.

scholarly journals Simulation of 2-Coil and 4-Coil Magnetic Resonance Wearable WPT Systems

Proceedings ◽  
2021 ◽  
Vol 68 (1) ◽  
pp. 13
Author(s):  
Yixuan Sun ◽  
Stephen Beeby
Keyword(s):  
Power Efficiency ◽  
Power Transmission ◽  
Rotation Angle ◽  
Wireless Power ◽  
Peak Efficiency ◽  
Frequency Splitting ◽  
At Resonance ◽  
Higher Power ◽  
The Impact ◽  
Proper Frequency

This paper presents the COMSOL simulations of magnetically coupled resonant wireless power transfer (WPT), using simplified coil models for embroidered planar two-coil and four-coil systems. The power transmission of both systems is studied and compared by varying the separation, rotation angle and misalignment distance at resonance (5 MHz). The frequency splitting occurs at short separations from both the two-coil and four-coil systems, resulting in lower power transmission. Therefore, the systems are driven from 4 MHz to 6 MHz to analyze the impact of frequency splitting at close separations. The results show that both systems had a peak efficiency over 90% after tuning to the proper frequency to overcome the frequency splitting phenomenon at close separations below 10 cm. The four-coil design achieved higher power efficiency at separations over 10 cm. The power efficiency of both systems decreased linearly when the axial misalignment was over 4 cm or the misalignment angle between receiver and transmitter was over 45 degrees.

scholarly journals Efficient Operative Cost Reduction in Distribution Grids Considering the Optimal Placement and Sizing of D-STATCOMs Using a Discrete-Continuous VSA

2021 ◽  
Vol 11 (5) ◽  
pp. 2175
Author(s):  
Oscar Danilo Montoya ◽  
Walter Gil-González ◽  
Jesus C. Hernández
Keyword(s):  
Objective Function ◽  
Reactive Power ◽  
Programming Model ◽  
Search Algorithm ◽  
Solution Space ◽  
Distribution Networks ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Solution Vector ◽  
The Impact

The problem of reactive power compensation in electric distribution networks is addressed in this research paper from the point of view of the combinatorial optimization using a new discrete-continuous version of the vortex search algorithm (DCVSA). To explore and exploit the solution space, a discrete-continuous codification of the solution vector is proposed, where the discrete part determines the nodes where the distribution static compensator (D-STATCOM) will be installed, and the continuous part of the codification determines the optimal sizes of the D-STATCOMs. The main advantage of such codification is that the mixed-integer nonlinear programming model (MINLP) that represents the problem of optimal placement and sizing of the D-STATCOMs in distribution networks only requires a classical power flow method to evaluate the objective function, which implies that it can be implemented in any programming language. The objective function is the total costs of the grid power losses and the annualized investment costs in D-STATCOMs. In addition, to include the impact of the daily load variations, the active and reactive power demand curves are included in the optimization model. Numerical results in two radial test feeders with 33 and 69 buses demonstrate that the proposed DCVSA can solve the MINLP model with best results when compared with the MINLP solvers available in the GAMS software. All the simulations are implemented in MATLAB software using its programming environment.

scholarly journals The Impact of Alternative Payment Arrangements on the Performance of Florida Sugarcane Cooperatives

1984 ◽  
Vol 16 (2) ◽  
pp. 99-108
Author(s):  
Rigoberto A. Lopez ◽  
Thomas H. Spreen
Keyword(s):  
Collective Behavior ◽  
Programming Model ◽  
Critical Role ◽  
Payment Systems ◽  
Cooperative Play ◽  
The Impact

AbstractPayment arrangements among members of a cooperative play a critical role in the performance of the cooperative. The impact of three payment systems is assessed for Florida sugarcane cooperatives through a bi-level programming model which incorporates both individual and collective behavior.

scholarly journals A Mixed Integer Linear Programming Method for Simultaneous Multi-Periodic Train Timetabling and Routing on a High-Speed Rail Network

2020 ◽  
Vol 12 (3) ◽  
pp. 1131
Author(s):  
Wenliang Zhou ◽  
Xiaorong You ◽  
Wenzhuang Fan
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
High Speed ◽  
Programming Model ◽  
Mixed Integer ◽  
High Speed Rail ◽  
Train Timetabling ◽  
Train Timetable ◽  
The Impact

To avoid conflicts among trains at stations and provide passengers with a periodic train timetable to improve service level, this paper mainly focuses on the problem of multi-periodic train timetabling and routing by optimizing the routes of trains at stations and their entering time and leaving time on each chosen arrival–departure track at each visited station. Based on the constructed directed graph, including unidirectional and bidirectional tracks at stations and in sections, a mixed integer linear programming model with the goal of minimizing the total travel time of trains is formulated. Then, a strategy is introduced to reduce the number of constraints for improving the solved efficiency of the model. Finally, the performance, stability and practicability of the proposed method, as well as the impact of some main factors on the model are analyzed by numerous instances on both a constructed railway network and Guang-Zhu inter-city railway; they are solved using the commercial solver WebSphere ILOG CPLEX (International Business Machines Corporation, New York, NY, USA). Experimental results show that integrating multi-periodic train timetabling and routing can be conducive to improving the quality of a train timetable. Hence, good economic and social benefits for high-speed rail can be achieved, thus, further contributing to the sustained development of both high-speed railway systems and society.

scholarly journals Fertilizer distribution flows and logistic costs in Brazil: changes and benefits arising from investments in port terminals

2018 ◽  
Vol 21 (3) ◽  
pp. 407-422 ◽  
Author(s):  
Débora da Costa Simões ◽  
José Vicente Caixeta-Filho ◽  
Udatta S. Palekar
Keyword(s):  
Linear Programming ◽  
Programming Model ◽  
Mato Grosso ◽  
Port Development ◽  
Full Capacity ◽  
Port System ◽  
Infrastructure Investments ◽  
Port Infrastructure ◽  
The Impact ◽  
A Current

This study analyzes the impact of anticipated investments to alter Brazilian port infrastructure on fertilizer flows and fertilizer transportation logistics costs using a linear programming model designed for the task. The most notable among these investments are directed toward accelerating port development in Brazil’s “Northern-Arc”, thereby increasing fertilizer supply to new markets opening throughout the country’s expanding agricultural frontier, particularly in northern Mato Grosso state, while increasing supply to existing markets. Results from model runs show that the anticipated port infrastructure investments should ensure nationwide fertilizer logistics savings of US$ 845 million over the 2017 through 2025 period. Although these estimated benefits are outstanding, the study indicates that further expansion of Brazil’s port system, particularly in the Northern-Arc, presents additional opportunities. Model projections were that in 2025, after all planned infrastructure improvements are operational, port terminals will be near full capacity, which should make planning for future projects a current priority.

scholarly journals Smart Caching at CMS: applying AI to XCache edge services

2020 ◽  
Vol 245 ◽  
pp. 04024
Author(s):  
Daniele Spiga ◽  
Diego Ciangottini ◽  
Mirco Tracolli ◽  
Tommaso Tedeschi ◽  
Daniele Cesini ◽  
...  
Keyword(s):  
National Level ◽  
Data Access ◽  
Analysis Data ◽  
Technical Solution ◽  
Early Results ◽  
Lake Model ◽  
Geographically Distributed ◽  
Computing Centers ◽  
Working Set ◽  
The Impact

The projected Storage and Compute needs for the HL-LHC will be a factor up to 10 above what can be achieved by the evolution of current technology within a flat budget. The WLCG community is studying possible technical solutions to evolve the current computing in order to cope with the requirements; one of the main focus is resource optimization, with the ultimate aim of improving performance and efficiency, as well as simplifying and reducing operation costs. As of today the storage consolidation based on a Data Lake model is considered a good candidate for addressing HL-LHC data access challenges. The Data Lake model under evaluation can be seen as a logical system that hosts a distributed working set of analysis data. Compute power can be “close” to the lake, but also remote and thus completely external. In this context we expect data caching to play a central role as a technical solution to reduce the impact of latency and reduce network load. A geographically distributed caching layer will be functional to many satellite computing centers that might appear and disappear dynamically. In this talk we propose a system of caches, distributed at national level, describing both deployment and results of the studies made to measure the impact on the CPU efficiency. In this contribution, we also present the early results on novel caching strategy beyond the standard XRootD approach whose results will be a baseline for an AI-based smart caching system.

scholarly journals The Impact of SARS-CoV-2 on Sperm Cryostorage, Theoretical or Real Risk?

Medicina ◽  
2021 ◽  
Vol 57 (9) ◽  
pp. 946
Author(s):  
George Anifandis ◽  
Tyl H Taylor ◽  
Christina I Messini ◽  
Katerina Chatzimeletiou ◽  
Alexandros Daponte ◽  
...  
Keyword(s):  
Human Reproduction ◽  
Fundamental Aspect ◽  
Sperm Cryopreservation ◽  
Sexually Transmitted ◽  
Oncological Patients ◽  
Real Risk ◽  
Human Reproductive ◽  
American Society ◽  
The Impact ◽  
Human Gametes

Cryopreservation of human gametes and embryos as well as human reproductive tissues has been characterized as an essential process and aspect of assisted reproductive technology (ART). Notably, sperm cryopreservation is a fundamental aspect of cryopreservation in oncological patients or patients undergoing gonadotoxic treatment. Given that there is a risk of contamination or cross-contamination, either theoretical or real, during the procedures of cryopreservation and cryostorage, both the European Society for Human Reproduction and Embryology (ESHRE) and the American Society for Reproductive Medicine (ASRM) have provided updated guidelines for preventing or reducing the contamination risk of sexually transmitted viruses. Given the ongoing and worldwide COVID-19 pandemic, there is considerable interest in what measures should be taken to mitigate SARS-CoV-2 contamination during cryopreservation and cryostorage of semen samples. The SARS-CoV-2 virus is the virus that causes COVID-19, and whose transmission and infection is mainly aerosol-mediated. Several ART professional societies, including ESHRE and ASRM have proposed measures to mitigate the spread of the SARS-CoV-2 virus. Whether the proposed safety directives are enough to mitigate the possible SARS-CoV-2-contamination of sperm samples during cryopreservation or whether the policies should be re-evaluated will be discussed in this review. Additionally, insights regarding the possible impact of COVID-19 vaccination on the safety of sperm cryopreservation will be discussed.

scholarly journals Impact of demand response on BIPV and district multi-energy systems design in Singapore and Switzerland

2021 ◽  
Vol 2042 (1) ◽  
pp. 012096
Author(s):  
Christoph Waibel ◽  
Shanshan Hsieh ◽  
Arno Schlüter
Keyword(s):  
Demand Response ◽  
Programming Model ◽  
Systems Design ◽  
Energy Systems ◽  
Mixed Integer ◽  
Peak Shaving ◽  
Climate Conditions ◽  
Building Integrated Photovoltaics ◽  
Energy Hub ◽  
The Impact

Abstract This paper demonstrates the impact of demand response (DR) on optimal multi-energy systems (MES) design with building integrated photovoltaics (BIPV) on roofs and façades. Building loads and solar potentials are assessed using bottom-up models; the MES design is determined using a Mixed-Integer Linear Programming model (energy hub). A mixed-use district of 170,000 m2 floor area including office, residential, retail, education, etc. is studied under current and future climate conditions in Switzerland and Singapore. Our findings are consistent with previous studies, which indicate that DR generally leads to smaller system capacities due to peak shaving. We further show that in both the Swiss and Singapore context, cost and emissions of the MES can be reduced significantly with DR. Applying DR, the optimal area for BIPV placement increases only marginally for Singapore (~1%), whereas for Switzerland, the area is even reduced by 2-8%, depending on the carbon target. In conclusion, depending on the context, DR can have a noticeable impact on optimal MES and BIPV capacities and should thus be considered in the design of future, energy efficient districts.

scholarly journals Task-based programming in COMPSs to converge from HPC to big data

2017 ◽  
Vol 32 (1) ◽  
pp. 45-60 ◽  
Author(s):  
Javier Conejero ◽  
Sandra Corella ◽  
Rosa M Badia ◽  
Jesus Labarta
Keyword(s):  
Big Data ◽  
High Performance ◽  
Programming Model ◽  
Good Alternative ◽  
Programming Models ◽  
Suitable Model ◽  
Advantages And Disadvantages ◽  
Big Data Applications ◽  
And Performance ◽  
The Right

Task-based programming has proven to be a suitable model for high-performance computing (HPC) applications. Different implementations have been good demonstrators of this fact and have promoted the acceptance of task-based programming in the OpenMP standard. Furthermore, in recent years, Apache Spark has gained wide popularity in business and research environments as a programming model for addressing emerging big data problems. COMP Superscalar (COMPSs) is a task-based environment that tackles distributed computing (including Clouds) and is a good alternative for a task-based programming model for big data applications. This article describes why we consider that task-based programming models are a good approach for big data applications. The article includes a comparison of Spark and COMPSs in terms of architecture, programming model, and performance. It focuses on the differences that both frameworks have in structural terms, on their programmability interface, and in terms of their efficiency by means of three widely known benchmarking kernels: Wordcount, Kmeans, and Terasort. These kernels enable the evaluation of the more important functionalities of both programming models and analyze different work flows and conditions. The main results achieved from this comparison are (1) COMPSs is able to extract the inherent parallelism from the user code with minimal coding effort as opposed to Spark, which requires the existing algorithms to be adapted and rewritten by explicitly using their predefined functions, (2) it is an improvement in terms of performance when compared with Spark, and (3) COMPSs has shown to scale better than Spark in most cases. Finally, we discuss the advantages and disadvantages of both frameworks, highlighting the differences that make them unique, thereby helping to choose the right framework for each particular objective.

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