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config.ini
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[Output_data]
# path of the directory to store to the output in
output_dir: ./trial_results
print_output: True
# Output directory for the Constraint problem and assignment
cons_output: ./cons
[GA_type]
# options of the type of Meta-Heuristic strategy to be used
# This option can be used to make the choice between the normal GA and Repair strategy based GA
# normal_GA - This option can be used to run the DSE with normal GA
# dpll_GA - This option can be used to run the DSE with the Repair strategy based approach
# both - This option enables runs with both DSE runs and compares the outputs
# default value for this parameter is 'both'
run_type: both
# This option is used to decide whether the DSE time of the PB strat should be equated with the time of the Normal GA
# PB strat takes longer for each evaluation than the Normal GA.
# True - Equate the DSE time
# False - Don't equate the DSE time, keep the number of generations same
equate_time: False
# This option is used to select between the kind of objectives to run the DSE for
# energy - This option corresponds to a unconstrained run with energy as the single objective
# time - This option corresponds to a unconstrained run with time as the single objective
# unconstrained - This option corresponds to unconstrained DSE run with multiple objectives
# constrained - This option corresponds to energy constrained or time constrained run with multiple objectives.
# default value is 'constrained'
objective_type: constrained
#enabling baseline takes values True and false
baseline_enabled: False
# energy baseline in uW
#baseline_value_energy: 200
# Time in uS
#baseline_value_time: 3000
# Option only used for constrained meta-heuristic
# Value of user constraint with respect to minimum value of a particular objective
# currently unused
# if objective scale is 0, the constraints are not considered.
objective_scale_energy: 10
objective_scale_time: 10
[Input_data]
# task graph to use
# e3s - E3S benchmark to be used
# synthetic - Synthetic Task graph used
tgff: e3s
# number of tasks in synthetic task graph
num_tasks: 25
#
e3s_path: ./a.tgff
# The path to the tgff binary
tgff_path: ./tgff-3.6/tgff
# The output directory for the artificial task graph
output_path: ./tg_generated
# Name of the artificial task graph generated
output_name: tg_20
#Value of seed used by the tgff generator
seed_value: 64
#path of the template file for the tgff template
template: ./template.tgff
[PE_data]
# The length of the NOC
length: 2
# The breadth of the NOC
breadth: 2
# List to determine which PE in the list is
# Select the PE_type corresponding to each value in the PE_list
# 1 - AMD 133 Mhz core
# 2 - AMD 400 Mhz core
# 3 - AMD 500 Mhz core
# 4 - IBM 266 Mhz core
# 5 - IBM 500 Mhz core
# 6 - NEC VR 5432 167 Mhz core
# The following array is a flattened array which represents a NxM matrix
# The values in this list can take any value from 1 to 6
PE_matrix: (1,2,1,2,)
[Cross_Layer_parameters]
# Number of DVFS levels
# The number of DVFS levels vary from processor to processor
# Each dvfs level corresponds to the DVFS level of 1 of the 6 PE types mentioned in the list above
# The array is 6 numbers long.
# The first number corresponds to the number of DVFS level of the 1 - AMD 133 Mhz core, the second corresponds to the 2 - AMD 400 Mhz core and so on.
# num_dvfs: (1,8,10,8,10,2)
num_dvfs: 8
# Maximum number of implementations for each task of implementations of each task
num_implementations: 5
[Meta_data]
# Number of individuals in each generation for single objective optimization
single_ind: 10
# Number of individuals in each generation for multi-objective optimization
multi_ind: 100
# Number of Generations of in the DSE
gen: 20