Página 1 dos resultados de 69 itens digitais encontrados em 0.050 segundos
Resultados filtrados por Publicador: Universidade Cornell

‣ Electricity Demand and Energy Consumption Management System

Sarmiento, Juan Ojeda
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
58.372637%
This project describes the electricity demand and energy consumption management system and its application to Southern Peru smelter. It is composed of an hourly demand-forecasting module and of a simulation component for a plant electrical system. The first module was done using dynamic neural networks with backpropagation training algorithm; it is used to predict the electric power demanded every hour, with an error percentage below of 1%. This information allows efficient management of energy peak demands before this happen, distributing the raise of electric load to other hours or improving those equipments that increase the demand. The simulation module is based in advanced estimation techniques, such as: parametric estimation, neural network modeling, statistic regression and previously developed models, which simulates the electric behavior of the smelter plant. These modules facilitate electricity demand and consumption proper planning, because they allow knowing the behavior of the hourly demand and the consumption patterns of the plant, including the bill components, but also energy deficiencies and opportunities for improvement, based on analysis of information about equipments, processes and production plans, as well as maintenance programs. Finally the results of its application in Southern Peru smelter are presented.

‣ On the Value and Limits of Multi-level Energy Consumption Static Analysis for Deeply Embedded Single and Multi-threaded Programs

Georgiou, Kyriakos; Kerrison, Steve; Eder, Kerstin
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 23/10/2015 Português
Relevância na Pesquisa
58.73728%
There is growing interest in lowering the energy consumption of computation. Energy transparency is a concept that makes a program's energy consumption visible from software to hardware through the different system layers. Such transparency can enable energy optimizations at each layer and between layers, and help both programmers and operating systems make energy aware decisions. The common methodology of extracting the energy consumption of a program is through direct measurement of the target hardware. This usually involves specialized equipment and knowledge most programmers do not have. In this paper, we examine how existing methods for static resource analysis and energy modeling can be utilized to perform Energy Consumption Static Analysis (ECSA) for deeply embedded programs. To investigate this, we have developed ECSA techniques that work at the instruction set level and at a higher level, the LLVM IR, through a novel mapping technique. We apply our ECSA to a comprehensive set of mainly industrial benchmarks, including single-threaded and also multi-threaded embedded programs from two commonly used concurrency patterns, task farms and pipelines. We compare our ECSA results to hardware measurements and predictions obtained based on simulation traces. We discuss a number of application scenarios for which ECSA results can provide energy transparency and conclude with a set of new research questions for future work.; Comment: 29 pages...

‣ Modeling and visualizing networked multi-core embedded software energy consumption

Kerrison, Steve; Eder, Kerstin
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 09/09/2015 Português
Relevância na Pesquisa
58.14502%
In this report we present a network-level multi-core energy model and a software development process workflow that allows software developers to estimate the energy consumption of multi-core embedded programs. This work focuses on a high performance, cache-less and timing predictable embedded processor architecture, XS1. Prior modelling work is improved to increase accuracy, then extended to be parametric with respect to voltage and frequency scaling (VFS) and then integrated into a larger scale model of a network of interconnected cores. The modelling is supported by enhancements to an open source instruction set simulator to provide the first network timing aware simulations of the target architecture. Simulation based modelling techniques are combined with methods of results presentation to demonstrate how such work can be integrated into a software developer's workflow, enabling the developer to make informed, energy aware coding decisions. A set of single-, multi-threaded and multi-core benchmarks are used to exercise and evaluate the models and provide use case examples for how results can be presented and interpreted. The models all yield accuracy within an average +/-5 % error margin.

‣ Static analysis of energy consumption for LLVM IR programs

Grech, Neville; Georgiou, Kyriakos; Pallister, James; Kerrison, Steve; Morse, Jeremy; Eder, Kerstin
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
58.19555%
Energy models can be constructed by characterizing the energy consumed by executing each instruction in a processor's instruction set. This can be used to determine how much energy is required to execute a sequence of assembly instructions, without the need to instrument or measure hardware. However, statically analyzing low-level program structures is hard, and the gap between the high-level program structure and the low-level energy models needs to be bridged. We have developed techniques for performing a static analysis on the intermediate compiler representations of a program. Specifically, we target LLVM IR, a representation used by modern compilers, including Clang. Using these techniques we can automatically infer an estimate of the energy consumed when running a function under different platforms, using different compilers. One of the challenges in doing so is that of determining an energy cost of executing LLVM IR program segments, for which we have developed two different approaches. When this information is used in conjunction with our analysis, we are able to infer energy formulae that characterize the energy consumption for a particular program. This approach can be applied to any languages targeting the LLVM toolchain...

‣ Inferring Parametric Energy Consumption Functions at Different Software Levels: ISA vs. LLVM IR

Liqat, Umer; Georgiou, Kyriakos; Kerrison, Steve; Lopez-Garcia, Pedro; Gallagher, John P.; Hermenegildo, Manuel V.; Eder, Kerstin
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 04/11/2015 Português
Relevância na Pesquisa
58.258867%
The static estimation of the energy consumed by program executions is an important challenge, which has applications in program optimization and verification, and is instrumental in energy-aware software development. Our objective is to estimate such energy consumption in the form of functions on the input data sizes of programs. We have developed a tool for experimentation with static analysis which infers such energy functions at two levels, the instruction set architecture (ISA) and the intermediate code (LLVM IR) levels, and reflects it upwards to the higher source code level. This required the development of a translation from LLVM IR to an intermediate representation and its integration with existing components, a translation from ISA to the same representation, a resource analyzer, an ISA-level energy model, and a mapping from this model to LLVM IR. The approach has been applied to programs written in the XC language running on XCore architectures, but is general enough to be applied to other languages. Experimental results show that our LLVM IR level analysis is reasonably accurate (less than 6.4% average error vs. hardware measurements) and more powerful than analysis at the ISA level. This paper provides insights into the trade-off of precision versus analyzability at these levels.; Comment: 22 pages...

‣ Minimizing Energy Consumption of MPI Programs in Realistic Environment

Guermouche, Amina; Triquenaux, Nicolas; Pradelle, Benoit; Jalby, William
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
68.110576%
Dynamic voltage and frequency scaling proves to be an efficient way of reducing energy consumption of servers. Energy savings are typically achieved by setting a well-chosen frequency during some program phases. However, determining suitable program phases and their associated optimal frequencies is a complex problem. Moreover, hardware is constrained by non negligible frequency transition latencies. Thus, various heuristics were proposed to determine and apply frequencies, but evaluating their efficiency remains an issue. In this paper, we translate the energy minimization problem into a mixed integer program that specifically models most current hardware limitations. The problem solution then estimates the minimal energy consumption and the associated frequency schedule. The paper provides two different formulations and a discussion on the feasibility of each of them on realistic applications.