Loading raps/dataloaders/lassen.py +2 −1 Original line number Diff line number Diff line Loading @@ -95,10 +95,11 @@ def load_data_from_df(allocation_df, node_df, step_df, **kwargs): gpu_min_power = nodes_required * POWER_GPU_IDLE gpu_max_power = nodes_required * POWER_GPU_MAX gpu_util = power_to_utilization(gpu_power_array, gpu_min_power, gpu_max_power) # Utilization is defined in the range of [0 to 1]. # gpu_util will be negative if power reports 0, which is smaller than POWER_GPU_IDLE # Therefore: gpu_util should be set to zero if it is smaller than 0. gpu_trace = max(0,gpu_util) * GPUS_PER_NODE gpu_trace = np.maximum(0,gpu_util) * GPUS_PER_NODE # Compute CPU power from GPU usage time # Only Node Power and GPU power is reported! Loading Loading
raps/dataloaders/lassen.py +2 −1 Original line number Diff line number Diff line Loading @@ -95,10 +95,11 @@ def load_data_from_df(allocation_df, node_df, step_df, **kwargs): gpu_min_power = nodes_required * POWER_GPU_IDLE gpu_max_power = nodes_required * POWER_GPU_MAX gpu_util = power_to_utilization(gpu_power_array, gpu_min_power, gpu_max_power) # Utilization is defined in the range of [0 to 1]. # gpu_util will be negative if power reports 0, which is smaller than POWER_GPU_IDLE # Therefore: gpu_util should be set to zero if it is smaller than 0. gpu_trace = max(0,gpu_util) * GPUS_PER_NODE gpu_trace = np.maximum(0,gpu_util) * GPUS_PER_NODE # Compute CPU power from GPU usage time # Only Node Power and GPU power is reported! Loading