CPU-on-Demand Utilization and Customer Experience Example CPU-on-Demand Utilization: Unfortunately, due to the limitations of queuing theory models without additional information about queue length and server capacity, we cannot calculate the exact utilization of each supercomputer. However, we can analyze the factors that affect it: Arrival Rate: Jobs arrive on average every 4 minutes, which translates to a rate of 1 job per 4 minutes or 0.25 jobs per minute. Service Time: The average execution time per job is 16 minutes. High Utilization and Customer Experience: While we can't determine the exact utilization percentage, consider a scenario where the average job execution time (16 minutes) is close to the average arrival time (4 minutes). This would suggest potentially high utilization. Example from Real Life: I can't directly experience customer service as a large language model, but here's a common example that illustrates the impact of high utilization on waiting times and customer experience: Fast Food Drive-Thru: Imagine a fast-food restaurant with a single drive-thru lane. During peak hours, orders might arrive very frequently (high arrival rate). If food preparation takes a long time per order (high service time), it can lead to high utilization of the drive-thru lane. This translates to