Multi-Objective Local Instruction Scheduling for GPGPU Applications

2012 ◽  
Author(s):  
Constantin Timm ◽  
Frank Weichert ◽  
Peter Marwedel ◽  
Heinrich Müller
Keyword(s):  
Instruction Scheduling ◽  
Multi Objective

ANALYSIS AND TOOLS FOR THE DESIGN OF VLIW EMBEDDED SYSTEMS IN A MULTI-OBJECTIVE SCENARIO

2007 ◽  
Vol 16 (05) ◽  
pp. 819-846
Author(s):  
VINCENZO CATANIA ◽  
MAURIZIO PALESI ◽  
DAVIDE PATTI
Keyword(s):  
Embedded Systems ◽  
Instruction Scheduling ◽  
Design Flow ◽  
System Level ◽  
Instruction Level Parallelism ◽  
Accurate Estimation ◽  
Subsequent Stage ◽  
Multi Objective ◽  
Trade Offs ◽  
Starting Point

The use of Application-Specific Instruction-set Processors (ASIP) in embedded systems is a solution to the problem of increasing complexity in the functions these systems have to implement. Architectures based on Very Long Instruction Word (VLIW) have found fertile ground in multimedia electronic appliances thanks to their ability to exploit high degrees of Instruction Level Parallelism (ILP) with a reasonable trade-off in complexity and silicon costs. In this case the ASIP specialization involves a complex interaction between hardware- and software-related issues. In this paper we propose tools and methodologies to cope efficiently with this complexity from a multi-objective perspective. We present EPIC-Explorer, an open platform for estimation and system-level exploration of an EPIC/VLIW architecture. We first analyze the possible design objectives, showing that it is necessary, given the fundamental role played by the VLIW compiler in instruction scheduling, to evaluate the appropriateness of ILP-oriented compilation on a case-by-case basis. Then, in the architecture exploration phase, we will use a multi-objective genetic approach to obtain a set of Pareto-optimal configurations. Finally, by clustering the configurations thus obtained, we extract those representing possible trade-offs between the objectives, which are used as a starting point for evaluation via more accurate estimation models at a subsequent stage in the design flow.

Multi-Objective Local Instruction Scheduling for GPGPU Applications

2011 ◽  
Author(s):  
Constantin Timm ◽  
Frank Weichert ◽  
Peter Marwedel ◽  
Heinrich Müller
Keyword(s):  
Instruction Scheduling ◽  
Multi Objective

Fuzzy multi-objective decision making approach for nuclear power plant installation

2020 ◽  
Vol 39 (5) ◽  
pp. 6339-6350
Author(s):  
Esra Çakır ◽  
Ziya Ulukan
Keyword(s):  
Linear Programming ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Energy Supply ◽  
Energy Demand ◽  
Nuclear Power ◽  
Power Plants ◽  
Total Duration ◽  
Objective Functions ◽  
Multi Objective

Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem.

Fuzzy multi-objective location and routing problem

2020 ◽  
Vol 39 (3) ◽  
pp. 3259-3273
Author(s):  
Nasser Shahsavari-Pour ◽  
Najmeh Bahram-Pour ◽  
Mojde Kazemi
Keyword(s):  
Firefly Algorithm ◽  
High Reliability ◽  
Research Area ◽  
Nsga Ii ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Allocation ◽  
Multi Objective ◽  
Location Routing ◽  
The Cost

The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems.

Solving Fully Fuzzy Multi-Objective Linear Programming Problems

2012 ◽  
Vol 3 (4) ◽  
pp. 1-6 ◽  
Author(s):  
M.Jayalakshmi M.Jayalakshmi ◽  
◽  
P.Pandian P.Pandian
Keyword(s):  
Linear Programming ◽  
Multi Objective ◽  
Linear Programming Problems
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