Exemplo n.º 1
0
 def set_service_profiles(self):
     self.arrival_profiles[images.pi_function] = \
         expovariate_arrival_profile(constant_rps_profile(self.rps))
     self.arrival_profiles[images.tf_gpu_function] = \
         expovariate_arrival_profile(constant_rps_profile(self.rps))
     # set arrival profiles
     self.arrival_profiles[images.fio_function] = \
         expovariate_arrival_profile(constant_rps_profile(self.rps))
Exemplo n.º 2
0
    def set_mixed_profiles(self):
        self.arrival_profiles[images.resnet50_inference_function] = \
            expovariate_arrival_profile(constant_rps_profile(self.rps))

        self.arrival_profiles[images.mobilenet_inference_function] = \
            expovariate_arrival_profile(constant_rps_profile(self.rps))

        self.arrival_profiles[images.speech_inference_function] = \
            expovariate_arrival_profile(constant_rps_profile(self.rps))

        self.arrival_profiles[images.resnet50_training_function] = \
            expovariate_arrival_profile(constant_rps_profile(0.1))

        self.arrival_profiles[images.resnet50_preprocessing_function] = \
            expovariate_arrival_profile(constant_rps_profile(1))
Exemplo n.º 3
0
    def setup(self, env: Environment):
        super().setup(env)
        deployments = self.deployments_per_name
        no_of_devices = len(env.topology.get_nodes())
        deployments[images.resnet50_inference_function].rps_threshold = 100
        deployments[images.resnet50_inference_function].scale_max = int(0.7 * no_of_devices)
        deployments[images.resnet50_inference_function].scale_factor = int(0.05 * no_of_devices)
        deployments[images.resnet50_inference_function].rps_threshold_duration = 10

        deployments[images.mobilenet_inference_function].rps_threshold = 70
        deployments[images.mobilenet_inference_function].scale_max = int(0.25 * no_of_devices)
        deployments[images.mobilenet_inference_function].scale_factor = 5
        deployments[images.mobilenet_inference_function].rps_threshold_duration = 10

        deployments[images.speech_inference_function].rps_threshold = 40
        deployments[images.speech_inference_function].scale_max = int(0.25 * no_of_devices)
        deployments[images.speech_inference_function].scale_factor = 5
        deployments[images.speech_inference_function].rps_threshold_duration = 15

        self.arrival_profiles[images.mobilenet_inference_function] = \
            expovariate_arrival_profile(constant_rps_profile(rps=100), max_ia=240)

        self.arrival_profiles[images.speech_inference_function] = \
            expovariate_arrival_profile(sine_rps_profile(env, max_rps=100, period=3600), max_ia=240)

        # set arrival profiles
        self.arrival_profiles[images.resnet50_inference_function] = \
            expovariate_arrival_profile(sine_rps_profile(env, max_rps=300, period=3600), max_ia=240)

        # set arrival profiles
        self.arrival_profiles[images.resnet50_preprocessing_function] = \
            expovariate_arrival_profile(sine_rps_profile(env, max_rps=10, period=3600), max_ia=240)

        # set arrival profiles
        self.arrival_profiles[images.resnet50_training_function] = \
            expovariate_arrival_profile(sine_rps_profile(env, max_rps=1, period=240), max_ia=240)